diff options
Diffstat (limited to 'libcuda/cuda_runtime_api.cc')
| -rw-r--r-- | libcuda/cuda_runtime_api.cc | 8240 |
1 files changed, 6464 insertions, 1776 deletions
diff --git a/libcuda/cuda_runtime_api.cc b/libcuda/cuda_runtime_api.cc index 9bdb993..fd05f55 100644 --- a/libcuda/cuda_runtime_api.cc +++ b/libcuda/cuda_runtime_api.cc @@ -2,16 +2,16 @@ // Changes Copyright 2009, Tor M. Aamodt, Ali Bakhoda and George L. Yuan // University of British Columbia -/* +/* * cuda_runtime_api.cc * - * Copyright © 2009 by Tor M. Aamodt, Wilson W. L. Fung, Ali Bakhoda, - * George L. Yuan and the University of British Columbia, Vancouver, + * Copyright © 2009 by Tor M. Aamodt, Wilson W. L. Fung, Ali Bakhoda, + * George L. Yuan and the University of British Columbia, Vancouver, * BC V6T 1Z4, All Rights Reserved. - * + * * THIS IS A LEGAL DOCUMENT BY DOWNLOADING GPGPU-SIM, YOU ARE AGREEING TO THESE * TERMS AND CONDITIONS. - * + * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE @@ -23,112 +23,118 @@ * CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE * POSSIBILITY OF SUCH DAMAGE. - * + * * NOTE: The files libcuda/cuda_runtime_api.c and src/cuda-sim/cuda-math.h * are derived from the CUDA Toolset available from http://www.nvidia.com/cuda - * (property of NVIDIA). The files benchmarks/BlackScholes/ and - * benchmarks/template/ are derived from the CUDA SDK available from - * http://www.nvidia.com/cuda (also property of NVIDIA). The files from - * src/intersim/ are derived from Booksim (a simulator provided with the - * textbook "Principles and Practices of Interconnection Networks" available - * from http://cva.stanford.edu/books/ppin/). As such, those files are bound by - * the corresponding legal terms and conditions set forth separately (original - * copyright notices are left in files from these sources and where we have - * modified a file our copyright notice appears before the original copyright - * notice). - * - * Using this version of GPGPU-Sim requires a complete installation of CUDA - * which is distributed seperately by NVIDIA under separate terms and + * (property of NVIDIA). The files benchmarks/BlackScholes/ and + * benchmarks/template/ are derived from the CUDA SDK available from + * http://www.nvidia.com/cuda (also property of NVIDIA). The files from + * src/intersim/ are derived from Booksim (a simulator provided with the + * textbook "Principles and Practices of Interconnection Networks" available + * from http://cva.stanford.edu/books/ppin/). As such, those files are bound by + * the corresponding legal terms and conditions set forth separately (original + * copyright notices are left in files from these sources and where we have + * modified a file our copyright notice appears before the original copyright + * notice). + * + * Using this version of GPGPU-Sim requires a complete installation of CUDA + * which is distributed seperately by NVIDIA under separate terms and * conditions. To use this version of GPGPU-Sim with OpenCL requires a * recent version of NVIDIA's drivers which support OpenCL. - * + * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions are met: - * + * * 1. Redistributions of source code must retain the above copyright notice, * this list of conditions and the following disclaimer. - * + * * 2. Redistributions in binary form must reproduce the above copyright notice, * this list of conditions and the following disclaimer in the documentation * and/or other materials provided with the distribution. - * + * * 3. Neither the name of the University of British Columbia nor the names of * its contributors may be used to endorse or promote products derived from * this software without specific prior written permission. - * - * 4. This version of GPGPU-SIM is distributed freely for non-commercial use only. - * + * + * 4. This version of GPGPU-SIM is distributed freely for non-commercial use + * only. + * * 5. No nonprofit user may place any restrictions on the use of this software, * including as modified by the user, by any other authorized user. - * - * 6. GPGPU-SIM was developed primarily by Tor M. Aamodt, Wilson W. L. Fung, - * Ali Bakhoda, George L. Yuan, at the University of British Columbia, + * + * 6. GPGPU-SIM was developed primarily by Tor M. Aamodt, Wilson W. L. Fung, + * Ali Bakhoda, George L. Yuan, at the University of British Columbia, * Vancouver, BC V6T 1Z4 */ /* * Copyright 1993-2007 NVIDIA Corporation. All rights reserved. * - * NOTICE TO USER: + * NOTICE TO USER: * - * This source code is subject to NVIDIA ownership rights under U.S. and - * international Copyright laws. Users and possessors of this source code - * are hereby granted a nonexclusive, royalty-free license to use this code + * This source code is subject to NVIDIA ownership rights under U.S. and + * international Copyright laws. Users and possessors of this source code + * are hereby granted a nonexclusive, royalty-free license to use this code * in individual and commercial software. * - * NVIDIA MAKES NO REPRESENTATION ABOUT THE SUITABILITY OF THIS SOURCE - * CODE FOR ANY PURPOSE. IT IS PROVIDED "AS IS" WITHOUT EXPRESS OR - * IMPLIED WARRANTY OF ANY KIND. NVIDIA DISCLAIMS ALL WARRANTIES WITH - * REGARD TO THIS SOURCE CODE, INCLUDING ALL IMPLIED WARRANTIES OF + * NVIDIA MAKES NO REPRESENTATION ABOUT THE SUITABILITY OF THIS SOURCE + * CODE FOR ANY PURPOSE. IT IS PROVIDED "AS IS" WITHOUT EXPRESS OR + * IMPLIED WARRANTY OF ANY KIND. NVIDIA DISCLAIMS ALL WARRANTIES WITH + * REGARD TO THIS SOURCE CODE, INCLUDING ALL IMPLIED WARRANTIES OF * MERCHANTABILITY, NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE. - * IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY SPECIAL, INDIRECT, INCIDENTAL, - * OR CONSEQUENTIAL DAMAGES, OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS - * OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE - * OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE - * OR PERFORMANCE OF THIS SOURCE CODE. + * IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY SPECIAL, INDIRECT, INCIDENTAL, + * OR CONSEQUENTIAL DAMAGES, OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS + * OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE + * OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE + * OR PERFORMANCE OF THIS SOURCE CODE. * - * U.S. Government End Users. This source code is a "commercial item" as - * that term is defined at 48 C.F.R. 2.101 (OCT 1995), consisting of - * "commercial computer software" and "commercial computer software - * documentation" as such terms are used in 48 C.F.R. 12.212 (SEPT 1995) - * and is provided to the U.S. Government only as a commercial end item. - * Consistent with 48 C.F.R.12.212 and 48 C.F.R. 227.7202-1 through - * 227.7202-4 (JUNE 1995), all U.S. Government End Users acquire the - * source code with only those rights set forth herein. + * U.S. Government End Users. This source code is a "commercial item" as + * that term is defined at 48 C.F.R. 2.101 (OCT 1995), consisting of + * "commercial computer software" and "commercial computer software + * documentation" as such terms are used in 48 C.F.R. 12.212 (SEPT 1995) + * and is provided to the U.S. Government only as a commercial end item. + * Consistent with 48 C.F.R.12.212 and 48 C.F.R. 227.7202-1 through + * 227.7202-4 (JUNE 1995), all U.S. Government End Users acquire the + * source code with only those rights set forth herein. * - * Any use of this source code in individual and commercial software must + * Any use of this source code in individual and commercial software must * include, in the user documentation and internal comments to the code, * the above Disclaimer and U.S. Government End Users Notice. */ -#include <stdlib.h> +#include <assert.h> +#include <stdarg.h> #include <stdio.h> +#include <stdlib.h> #include <string.h> -#include <assert.h> #include <time.h> -#include <stdarg.h> +#include <fstream> #include <iostream> -#include <string> #include <regex> #include <sstream> -#include <fstream> +#include <string> #ifdef OPENGL_SUPPORT #define GL_GLEXT_PROTOTYPES #ifdef __APPLE__ -#include <GLUT/glut.h> // Apple's version of GLUT is here +#include <GLUT/glut.h> // Apple's version of GLUT is here #else #include <GL/gl.h> #endif #endif #define __CUDA_RUNTIME_API_H__ - +// clang-format off #include "host_defines.h" #include "builtin_types.h" #include "driver_types.h" +#include "cuda_api.h" +#include "cudaProfiler.h" +// clang-format on #if (CUDART_VERSION < 8000) #include "__cudaFatFormat.h" #endif +#include "gpgpu_context.h" +#include "cuda_api_object.h" #include "../src/gpgpu-sim/gpu-sim.h" #include "../src/cuda-sim/ptx_loader.h" #include "../src/cuda-sim/cuda-sim.h" @@ -145,34 +151,20 @@ #include <mach-o/dyld.h> #endif -extern void synchronize(); -extern void exit_simulation(); - -static int load_static_globals( symbol_table *symtab, unsigned min_gaddr, unsigned max_gaddr, gpgpu_t *gpu ); -static int load_constants( symbol_table *symtab, addr_t min_gaddr, gpgpu_t *gpu ); - -static kernel_info_t *gpgpu_cuda_ptx_sim_init_grid( const char *kernel_key, - gpgpu_ptx_sim_arg_list_t args, - struct dim3 gridDim, - struct dim3 blockDim, - struct CUctx_st* context ); - /*DEVICE_BUILTIN*/ -struct cudaArray -{ - void *devPtr; - int devPtr32; - struct cudaChannelFormatDesc desc; - int width; - int height; - int size; //in bytes - unsigned dimensions; +struct cudaArray { + void *devPtr; + int devPtr32; + struct cudaChannelFormatDesc desc; + int width; + int height; + int size; // in bytes + unsigned dimensions; }; #if !defined(__dv) #if defined(__cplusplus) -#define __dv(v) \ - = v +#define __dv(v) = v #else /* __cplusplus */ #define __dv(v) #endif /* __cplusplus */ @@ -180,263 +172,2122 @@ struct cudaArray cudaError_t g_last_cudaError = cudaSuccess; -extern stream_manager *g_stream_manager; - -void register_ptx_function( const char *name, function_info *impl ) -{ - // no longer need this +void register_ptx_function(const char *name, function_info *impl) { + // no longer need this } #if defined __APPLE__ -# define __my_func__ __PRETTY_FUNCTION__ +#define __my_func__ __PRETTY_FUNCTION__ +#else +#if defined __cplusplus ? __GNUC_PREREQ(2, 6) : __GNUC_PREREQ(2, 4) +#define __my_func__ __PRETTY_FUNCTION__ #else -# if defined __cplusplus ? __GNUC_PREREQ (2, 6) : __GNUC_PREREQ (2, 4) -# define __my_func__ __PRETTY_FUNCTION__ -# else -# if defined __STDC_VERSION__ && __STDC_VERSION__ >= 199901L -# define __my_func__ __func__ -# else -# define __my_func__ ((__const char *) 0) -# endif -# endif +#if defined __STDC_VERSION__ && __STDC_VERSION__ >= 199901L +#define __my_func__ __func__ +#else +#define __my_func__ ((__const char *)0) +#endif +#endif #endif -struct _cuda_device_id { - _cuda_device_id(gpgpu_sim* gpu) {m_id = 0; m_next = NULL; m_gpgpu=gpu;} - struct _cuda_device_id *next() { return m_next; } - unsigned num_shader() const { return m_gpgpu->get_config().num_shader(); } - int num_devices() const { - if( m_next == NULL ) return 1; - else return 1 + m_next->num_devices(); - } - struct _cuda_device_id *get_device( unsigned n ) - { - assert( n < (unsigned)num_devices() ); - struct _cuda_device_id *p=this; - for(unsigned i=0; i<n; i++) - p = p->m_next; - return p; - } - const struct cudaDeviceProp *get_prop() const - { - return m_gpgpu->get_prop(); - } - unsigned get_id() const { return m_id; } +struct _cuda_device_id *gpgpu_context::GPGPUSim_Init() { + _cuda_device_id *the_device = the_gpgpusim->the_cude_device; + if (!the_device) { + gpgpu_sim *the_gpu = gpgpu_ptx_sim_init_perf(); - gpgpu_sim *get_gpgpu() { return m_gpgpu; } -private: - unsigned m_id; - class gpgpu_sim *m_gpgpu; - struct _cuda_device_id *m_next; -}; + cudaDeviceProp *prop = (cudaDeviceProp *)calloc(sizeof(cudaDeviceProp), 1); + snprintf(prop->name, 256, "GPGPU-Sim_v%s", g_gpgpusim_version_string); + prop->major = the_gpu->compute_capability_major(); + prop->minor = the_gpu->compute_capability_minor(); + prop->totalGlobalMem = 0x80000000 /* 2 GB */; + prop->memPitch = 0; + if (prop->major >= 2) { + prop->maxThreadsPerBlock = 1024; + prop->maxThreadsDim[0] = 1024; + prop->maxThreadsDim[1] = 1024; + } else { + prop->maxThreadsPerBlock = 512; + prop->maxThreadsDim[0] = 512; + prop->maxThreadsDim[1] = 512; + } -struct CUctx_st { - CUctx_st( _cuda_device_id *gpu ) - { - m_gpu = gpu; - m_binary_info.cmem = 0; - m_binary_info.gmem = 0; - } + prop->maxThreadsDim[2] = 64; + prop->maxGridSize[0] = 0x40000000; + prop->maxGridSize[1] = 0x40000000; + prop->maxGridSize[2] = 0x40000000; + prop->totalConstMem = 0x40000000; + prop->textureAlignment = 0; + // * TODO: Update the .config and xml files of all GPU config files + // with new value of sharedMemPerBlock and regsPerBlock + prop->sharedMemPerBlock = the_gpu->shared_mem_per_block(); +#if (CUDART_VERSION > 5050) + prop->regsPerMultiprocessor = the_gpu->num_registers_per_core(); + prop->sharedMemPerMultiprocessor = the_gpu->shared_mem_size(); +#endif + prop->sharedMemPerBlock = the_gpu->shared_mem_per_block(); + prop->regsPerBlock = the_gpu->num_registers_per_block(); + prop->warpSize = the_gpu->wrp_size(); + prop->clockRate = the_gpu->shader_clock(); +#if (CUDART_VERSION >= 2010) + prop->multiProcessorCount = the_gpu->get_config().num_shader(); +#endif +#if (CUDART_VERSION >= 4000) + prop->maxThreadsPerMultiProcessor = the_gpu->threads_per_core(); +#endif + the_gpu->set_prop(prop); + the_gpgpusim->the_cude_device = new _cuda_device_id(the_gpu); + the_device = the_gpgpusim->the_cude_device; + } + start_sim_thread(1); + return the_device; +} - _cuda_device_id *get_device() { return m_gpu; } +CUctx_st *GPGPUSim_Context(gpgpu_context *ctx) { + // static CUctx_st *the_context = NULL; + CUctx_st *the_context = ctx->the_gpgpusim->the_context; + if (the_context == NULL) { + _cuda_device_id *the_gpu = ctx->GPGPUSim_Init(); + ctx->the_gpgpusim->the_context = new CUctx_st(the_gpu); + the_context = ctx->the_gpgpusim->the_context; + } + return the_context; +} - void add_binary( symbol_table *symtab, unsigned fat_cubin_handle ) - { - m_code[fat_cubin_handle] = symtab; - m_last_fat_cubin_handle = fat_cubin_handle; - } +gpgpu_context *GPGPU_Context() { + static gpgpu_context *gpgpu_ctx = NULL; + if (gpgpu_ctx == NULL) { + gpgpu_ctx = new gpgpu_context(); + } + return gpgpu_ctx; +} - void add_ptxinfo( const char *deviceFun, const struct gpgpu_ptx_sim_info &info ) - { - symbol *s = m_code[m_last_fat_cubin_handle]->lookup(deviceFun); - assert( s != NULL ); - function_info *f = s->get_pc(); - assert( f != NULL ); - f->set_kernel_info(info); - } +void ptxinfo_data::ptxinfo_addinfo() { + CUctx_st *context = GPGPUSim_Context(gpgpu_ctx); + if (!get_ptxinfo_kname()) { + /* This info is not per kernel (since CUDA 5.0 some info (e.g. gmem, and + * cmem) is added at the beginning for the whole binary ) */ + print_ptxinfo(); + context->add_ptxinfo(get_ptxinfo()); + clear_ptxinfo(); + return; + } + if (!strcmp("__cuda_dummy_entry__", get_ptxinfo_kname())) { + // this string produced by ptxas for empty ptx files (e.g., bandwidth test) + clear_ptxinfo(); + return; + } + print_ptxinfo(); + context->add_ptxinfo(get_ptxinfo_kname(), get_ptxinfo()); + clear_ptxinfo(); +} - void add_ptxinfo( const struct gpgpu_ptx_sim_info &info ) - { - m_binary_info = info; - } +void cuda_not_implemented(const char *func, unsigned line) { + fflush(stdout); + fflush(stderr); + printf( + "\n\nGPGPU-Sim PTX: Execution error: CUDA API function \"%s()\" has not " + "been implemented yet.\n" + " [$GPGPUSIM_ROOT/libcuda/%s around line %u]\n\n\n", + func, __FILE__, line); + fflush(stdout); + abort(); +} - void register_function( unsigned fat_cubin_handle, const char *hostFun, const char *deviceFun ) - { - if( m_code.find(fat_cubin_handle) != m_code.end() ) { - symbol *s = m_code[fat_cubin_handle]->lookup(deviceFun); - if(s != NULL) { - function_info *f = s->get_pc(); - assert( f != NULL ); - m_kernel_lookup[hostFun] = f; - } - else { - printf("Warning: cannot find deviceFun %s\n", deviceFun); - m_kernel_lookup[hostFun] = NULL; - } - // assert( s != NULL ); - // function_info *f = s->get_pc(); - // assert( f != NULL ); - // m_kernel_lookup[hostFun] = f; - } else { - m_kernel_lookup[hostFun] = NULL; - } - } +void announce_call(const char *func) { + printf("\n\nGPGPU-Sim PTX: CUDA API function \"%s\" has been called.\n", + func); + fflush(stdout); +} - function_info *get_kernel(const char *hostFun) - { - std::map<const void*,function_info*>::iterator i=m_kernel_lookup.find(hostFun); - assert( i != m_kernel_lookup.end() ); - return i->second; - } +#define gpgpusim_ptx_error(msg, ...) \ + gpgpusim_ptx_error_impl(__func__, __FILE__, __LINE__, msg, ##__VA_ARGS__) +#define gpgpusim_ptx_assert(cond, msg, ...) \ + gpgpusim_ptx_assert_impl((cond), __func__, __FILE__, __LINE__, msg, \ + ##__VA_ARGS__) -private: - _cuda_device_id *m_gpu; // selected gpu - std::map<unsigned,symbol_table*> m_code; // fat binary handle => global symbol table - unsigned m_last_fat_cubin_handle; - std::map<const void*,function_info*> m_kernel_lookup; // unique id (CUDA app function address) => kernel entry point - struct gpgpu_ptx_sim_info m_binary_info; +void gpgpusim_ptx_error_impl(const char *func, const char *file, unsigned line, + const char *msg, ...) { + va_list ap; + char buf[1024]; + va_start(ap, msg); + vsnprintf(buf, 1024, msg, ap); + va_end(ap); -}; + printf("GPGPU-Sim CUDA API: %s\n", buf); + printf(" [%s:%u : %s]\n", file, line, func); + abort(); +} -class kernel_config { -public: - kernel_config( dim3 GridDim, dim3 BlockDim, size_t sharedMem, struct CUstream_st *stream ) - { - m_GridDim=GridDim; - m_BlockDim=BlockDim; - m_sharedMem=sharedMem; - m_stream = stream; - } - void set_arg( const void *arg, size_t size, size_t offset ) - { - m_args.push_front( gpgpu_ptx_sim_arg(arg,size,offset) ); - } - dim3 grid_dim() const { return m_GridDim; } - dim3 block_dim() const { return m_BlockDim; } - gpgpu_ptx_sim_arg_list_t get_args() { return m_args; } - struct CUstream_st *get_stream() { return m_stream; } +void gpgpusim_ptx_assert_impl(int test_value, const char *func, + const char *file, unsigned line, const char *msg, + ...) { + va_list ap; + char buf[1024]; + va_start(ap, msg); + vsnprintf(buf, 1024, msg, ap); + va_end(ap); -private: - dim3 m_GridDim; - dim3 m_BlockDim; - size_t m_sharedMem; - struct CUstream_st *m_stream; - gpgpu_ptx_sim_arg_list_t m_args; -}; + if (test_value == 0) gpgpusim_ptx_error_impl(func, file, line, msg); +} -class _cuda_device_id *GPGPUSim_Init() -{ - static _cuda_device_id *the_device = NULL; - if( !the_device ) { - gpgpu_sim *the_gpu = gpgpu_ptx_sim_init_perf(); +typedef std::map<unsigned, CUevent_st *> event_tracker_t; + +int CUevent_st::m_next_event_uid; +event_tracker_t g_timer_events; + +extern int cuobjdump_lex_init(yyscan_t *scanner); +extern void cuobjdump_set_in(FILE *_in_str, yyscan_t yyscanner); +extern int cuobjdump_parse(yyscan_t scanner, struct cuobjdump_parser *parser, + std::list<cuobjdumpSection *> &cuobjdumpSectionList); +extern int cuobjdump_lex_destroy(yyscan_t scanner); + +enum cuobjdumpSectionType { PTXSECTION = 0, ELFSECTION }; + +// sectiontype: 0 for ptx, 1 for elf +void addCuobjdumpSection(int sectiontype, + std::list<cuobjdumpSection *> &cuobjdumpSectionList) { + if (sectiontype) + cuobjdumpSectionList.push_front(new cuobjdumpELFSection()); + else + cuobjdumpSectionList.push_front(new cuobjdumpPTXSection()); + printf("## Adding new section %s\n", sectiontype ? "ELF" : "PTX"); +} + +void setCuobjdumparch(const char *arch, + std::list<cuobjdumpSection *> &cuobjdumpSectionList) { + unsigned archnum; + sscanf(arch, "sm_%u", &archnum); + assert(archnum && "cannot have sm_0"); + printf("Adding arch: %s\n", arch); + cuobjdumpSectionList.front()->setArch(archnum); +} + +void setCuobjdumpidentifier( + const char *identifier, + std::list<cuobjdumpSection *> &cuobjdumpSectionList) { + printf("Adding identifier: %s\n", identifier); + cuobjdumpSectionList.front()->setIdentifier(identifier); +} + +void setCuobjdumpptxfilename( + const char *filename, std::list<cuobjdumpSection *> &cuobjdumpSectionList) { + printf("Adding ptx filename: %s\n", filename); + cuobjdumpSection *x = cuobjdumpSectionList.front(); + if (dynamic_cast<cuobjdumpPTXSection *>(x) == NULL) { + assert(0 && + "You shouldn't be trying to add a ptxfilename to an elf section"); + } + (dynamic_cast<cuobjdumpPTXSection *>(x))->setPTXfilename(filename); +} + +void setCuobjdumpelffilename( + const char *filename, std::list<cuobjdumpSection *> &cuobjdumpSectionList) { + if (dynamic_cast<cuobjdumpELFSection *>(cuobjdumpSectionList.front()) == + NULL) { + assert(0 && + "You shouldn't be trying to add a elffilename to an ptx section"); + } + (dynamic_cast<cuobjdumpELFSection *>(cuobjdumpSectionList.front())) + ->setELFfilename(filename); +} + +void setCuobjdumpsassfilename( + const char *filename, std::list<cuobjdumpSection *> &cuobjdumpSectionList) { + if (dynamic_cast<cuobjdumpELFSection *>(cuobjdumpSectionList.front()) == + NULL) { + assert(0 && + "You shouldn't be trying to add a sassfilename to an ptx section"); + } + (dynamic_cast<cuobjdumpELFSection *>(cuobjdumpSectionList.front())) + ->setSASSfilename(filename); +} + +//! Return the executable file of the process containing the PTX/SASS code +//! +//! This Function returns the executable file ran by the process. This +//! executable is supposed to contain the PTX/SASS code. It provides workaround +//! for processes running on valgrind by dereferencing /proc/<pid>/exe within +//! the GPGPU-Sim process before calling cuobjdump to extract PTX/SASS. This is +//! needed because valgrind uses x86 emulation to detect memory leak. Other +//! processes (e.g. cuobjdump) reading /proc/<pid>/exe will see the emulator +//! executable instead of the application binary. +//! +std::string get_app_binary() { + char self_exe_path[1025]; +#ifdef __APPLE__ + uint32_t size = sizeof(self_exe_path); + if (_NSGetExecutablePath(self_exe_path, &size) != 0) { + printf("GPGPU-Sim ** ERROR: _NSGetExecutablePath input buffer too small\n"); + exit(1); + } +#else + std::stringstream exec_link; + exec_link << "/proc/self/exe"; + + ssize_t path_length = readlink(exec_link.str().c_str(), self_exe_path, 1024); + assert(path_length != -1); + self_exe_path[path_length] = '\0'; +#endif + + printf("self exe links to: %s\n", self_exe_path); + return self_exe_path; +} + +// above func gives abs path whereas this give just the name of application. +char *get_app_binary_name(std::string abs_path) { + char *self_exe_path; +#ifdef __APPLE__ + // TODO: get apple device and check the result. + printf("WARNING: not tested for Apple-mac devices \n"); + abort(); +#else + char *buf = strdup(abs_path.c_str()); + char *token = strtok(buf, "/"); + while (token != NULL) { + self_exe_path = token; + token = strtok(NULL, "/"); + } +#endif + self_exe_path = strtok(self_exe_path, "."); + printf("self exe links to: %s\n", self_exe_path); + return self_exe_path; +} + +static int get_app_cuda_version() { + int app_cuda_version = 0; + char fname[1024]; + snprintf(fname, 1024, "_app_cuda_version_XXXXXX"); + int fd = mkstemp(fname); + close(fd); + std::string app_cuda_version_command = + "ldd " + get_app_binary() + + " | grep libcudart.so | sed 's/.*libcudart.so.\\(.*\\) =>.*/\\1/' > " + + fname; + system(app_cuda_version_command.c_str()); + FILE *cmd = fopen(fname, "r"); + char buf[256]; + while (fgets(buf, sizeof(buf), cmd) != 0) { + std::cout << buf; + app_cuda_version = atoi(buf); + } + fclose(cmd); + if (app_cuda_version == 0) { + printf("Error - Cannot detect the app's CUDA version.\n"); + exit(1); + } + return app_cuda_version; +} + +//! Keep track of the association between filename and cubin handle +void cuda_runtime_api::cuobjdumpRegisterFatBinary(unsigned int handle, + const char *filename, + CUctx_st *context) { + fatbinmap[handle] = filename; +} + +/******************************************************************************* + * Add internal cuda runtime API call to accept gpgpu_context * + *******************************************************************************/ +cudaError_t cudaSetDeviceInternal(int device, gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + // set the active device to run cuda + if (device <= ctx->GPGPUSim_Init()->num_devices()) { + ctx->api->g_active_device = device; + return g_last_cudaError = cudaSuccess; + } else { + return g_last_cudaError = cudaErrorInvalidDevice; + } +} + +cudaError_t cudaGetDeviceInternal(int *device, + gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + *device = ctx->api->g_active_device; + return g_last_cudaError = cudaSuccess; +} + +__host__ cudaError_t CUDARTAPI cudaDeviceGetLimitInternal( + size_t *pValue, cudaLimit limit, gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + _cuda_device_id *dev = ctx->GPGPUSim_Init(); + const struct cudaDeviceProp *prop = dev->get_prop(); + const gpgpu_sim_config &config = dev->get_gpgpu()->get_config(); + switch (limit) { + case 0: // cudaLimitStackSize + *pValue = config.stack_limit(); + break; + case 2: // cudaLimitMallocHeapSize + *pValue = config.heap_limit(); + break; +#if (CUDART_VERSION > 5050) + case 3: // cudaLimitDevRuntimeSyncDepth + if (prop->major > 2) { + *pValue = config.sync_depth_limit(); + break; + } else { + printf("ERROR:Limit %d is not supported on this architecture \n", + limit); + abort(); + } + case 4: // cudaLimitDevRuntimePendingLaunchCount + if (prop->major > 2) { + *pValue = config.pending_launch_count_limit(); + break; + } else { + printf("ERROR:Limit %d is not supported on this architecture \n", + limit); + abort(); + } +#endif + default: + printf("ERROR:Limit %d unimplemented \n", limit); + abort(); + } + return g_last_cudaError = cudaSuccess; +} + +void **cudaRegisterFatBinaryInternal(void *fatCubin, + gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } +#if (CUDART_VERSION < 2010) + printf( + "GPGPU-Sim PTX: ERROR ** this version of GPGPU-Sim requires CUDA 2.1 or " + "higher\n"); + exit(1); +#endif + CUctx_st *context = GPGPUSim_Context(ctx); + static unsigned next_fat_bin_handle = 1; + if (context->get_device()->get_gpgpu()->get_config().use_cuobjdump()) { + // The following workaround has only been verified on 64-bit systems. + if (sizeof(void *) == 4) + printf( + "GPGPU-Sim PTX: FatBin file name extraction has not been tested on " + "32-bit system.\n"); + + // This code will get the CUDA version the app was compiled with. + // We need this to determine how to handle the parsing of the binary. + // Making this a runtime variable based on the app, enables GPGPU-Sim + // compiled with a newer version of CUDA to run apps compiled with older + // versions of CUDA. This is especially useful for PTXPLUS execution. + // Skip cuda version check for pytorch application + std::string app_binary_path = get_app_binary(); + int pos = app_binary_path.find("python"); + if (pos == std::string::npos) { + // Not pytorch app : checking cuda version + int app_cuda_version = get_app_cuda_version(); + assert( + app_cuda_version == CUDART_VERSION / 1000 && + "The app must be compiled with same major version as the simulator."); + } + + // int app_cuda_version = get_app_cuda_version(); + // assert( app_cuda_version == CUDART_VERSION / 1000 && "The app must be + // compiled with same major version as the simulator." ); + const char *filename; +#if CUDART_VERSION < 6000 + // FatBin handle from the .fatbin.c file (one of the intermediate files + // generated by NVCC) + typedef struct { + int m; + int v; + const unsigned long long *d; + char *f; + } __fatDeviceText __attribute__((aligned(8))); + __fatDeviceText *fatDeviceText = (__fatDeviceText *)fatCubin; + + // Extract the source code file name that generate the given FatBin. + // - Obtains the pointer to the actual fatbin structure from the FatBin + // handle (fatCubin). + // - An integer inside the fatbin structure contains the relative offset to + // the source code file name. + // - This offset differs among different CUDA and GCC versions. + char *pfatbin = (char *)fatDeviceText->d; + int offset = *((int *)(pfatbin + 48)); + filename = (pfatbin + 16 + offset); +#else + filename = "default"; +#endif + + // The extracted file name is associated with a fat_cubin_handle passed + // into cudaLaunch(). Inside cudaLaunch(), the associated file name is + // used to find the PTX/SASS section from cuobjdump, which contains the + // PTX/SASS code for the launched kernel function. + // This allows us to work around the fact that cuobjdump only outputs the + // file name associated with each section. + unsigned long long fat_cubin_handle = next_fat_bin_handle; + next_fat_bin_handle++; + printf( + "GPGPU-Sim PTX: __cudaRegisterFatBinary, fat_cubin_handle = %llu, " + "filename=%s\n", + fat_cubin_handle, filename); + /*! + * This function extracts all data from all files in first call + * then for next calls, only returns the appropriate number + */ + assert(fat_cubin_handle >= 1); + if (fat_cubin_handle == 1) ctx->api->cuobjdumpInit(); + ctx->api->cuobjdumpRegisterFatBinary(fat_cubin_handle, filename, context); + + return (void **)fat_cubin_handle; + } +#if (CUDART_VERSION < 8000) + else { + static unsigned source_num = 1; + unsigned long long fat_cubin_handle = next_fat_bin_handle++; + __cudaFatCudaBinary *info = (__cudaFatCudaBinary *)fatCubin; + assert(info->version >= 3); + unsigned num_ptx_versions = 0; + unsigned max_capability = 0; + unsigned selected_capability = 0; + bool found = false; + unsigned forced_max_capability = context->get_device() + ->get_gpgpu() + ->get_config() + .get_forced_max_capability(); + if (!info->ptx) { + printf( + "ERROR: Cannot find ptx code in cubin file\n" + "\tIf you are using CUDA 4.0 or higher, please enable " + "-gpgpu_ptx_use_cuobjdump or downgrade to CUDA 3.1\n"); + exit(1); + } + while (info->ptx[num_ptx_versions].gpuProfileName != NULL) { + unsigned capability = 0; + sscanf(info->ptx[num_ptx_versions].gpuProfileName, "compute_%u", + &capability); + printf( + "GPGPU-Sim PTX: __cudaRegisterFatBinary found PTX versions for " + "'%s', ", + info->ident); + printf("capability = %s\n", info->ptx[num_ptx_versions].gpuProfileName); + if (forced_max_capability) { + if (capability > max_capability && + capability <= forced_max_capability) { + found = true; + max_capability = capability; + selected_capability = num_ptx_versions; + } + } else { + if (capability > max_capability) { + found = true; + max_capability = capability; + selected_capability = num_ptx_versions; + } + } + num_ptx_versions++; + } + if (found) { + printf("GPGPU-Sim PTX: Loading PTX for %s, capability = %s\n", + info->ident, info->ptx[selected_capability].gpuProfileName); + symbol_table *symtab; + const char *ptx = info->ptx[selected_capability].ptx; + if (context->get_device() + ->get_gpgpu() + ->get_config() + .convert_to_ptxplus()) { + printf( + "GPGPU-Sim PTX: ERROR ** PTXPlus is only supported through " + "cuobjdump\n" + "\tEither enable cuobjdump or disable PTXPlus in your " + "configuration file\n"); + exit(1); + } else { + symtab = ctx->gpgpu_ptx_sim_load_ptx_from_string(ptx, source_num); + context->add_binary(symtab, fat_cubin_handle); + ctx->gpgpu_ptxinfo_load_from_string(ptx, source_num, max_capability, + context->no_of_ptx); + } + source_num++; + ctx->api->load_static_globals(symtab, STATIC_ALLOC_LIMIT, 0xFFFFFFFF, + context->get_device()->get_gpgpu()); + ctx->api->load_constants(symtab, STATIC_ALLOC_LIMIT, + context->get_device()->get_gpgpu()); + } else { + printf( + "GPGPU-Sim PTX: warning -- did not find an appropriate PTX in " + "cubin\n"); + } + return (void **)fat_cubin_handle; + } +#else + else { + printf("ERROR ** __cudaRegisterFatBinary() needs to be updated\n"); + abort(); + } +#endif +} + +void cudaRegisterFunctionInternal(void **fatCubinHandle, const char *hostFun, + char *deviceFun, const char *deviceName, + int thread_limit, uint3 *tid, uint3 *bid, + dim3 *bDim, dim3 *gDim, + gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + CUctx_st *context = GPGPUSim_Context(ctx); + unsigned fat_cubin_handle = (unsigned)(unsigned long long)fatCubinHandle; + printf( + "GPGPU-Sim PTX: __cudaRegisterFunction %s : hostFun 0x%p, " + "fat_cubin_handle = %u\n", + deviceFun, hostFun, fat_cubin_handle); + if (context->get_device()->get_gpgpu()->get_config().use_cuobjdump()) + ctx->cuobjdumpParseBinary(fat_cubin_handle); + context->register_function(fat_cubin_handle, hostFun, deviceFun); +} + +void cudaRegisterVarInternal( + void **fatCubinHandle, + char *hostVar, // pointer to...something + char *deviceAddress, // name of variable + const char *deviceName, // name of variable (same as above) + int ext, int size, int constant, int global, + gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf( + "GPGPU-Sim PTX: __cudaRegisterVar: hostVar = %p; deviceAddress = %s; " + "deviceName = %s\n", + hostVar, deviceAddress, deviceName); + printf( + "GPGPU-Sim PTX: __cudaRegisterVar: Registering const memory space of %d " + "bytes\n", + size); + if (GPGPUSim_Context(ctx) + ->get_device() + ->get_gpgpu() + ->get_config() + .use_cuobjdump()) + ctx->cuobjdumpParseBinary((unsigned)(unsigned long long)fatCubinHandle); + fflush(stdout); + if (constant && !global && !ext) { + ctx->func_sim->gpgpu_ptx_sim_register_const_variable(hostVar, deviceName, + size); + } else if (!constant && !global && !ext) { + ctx->func_sim->gpgpu_ptx_sim_register_global_variable(hostVar, deviceName, + size); + } else + cuda_not_implemented(__my_func__, __LINE__); +} + +cudaError_t cudaConfigureCallInternal(dim3 gridDim, dim3 blockDim, + size_t sharedMem, cudaStream_t stream, + gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + struct CUstream_st *s = (struct CUstream_st *)stream; + ctx->api->g_cuda_launch_stack.push_back( + kernel_config(gridDim, blockDim, sharedMem, s)); + return g_last_cudaError = cudaSuccess; +} + +__host__ cudaError_t CUDARTAPI +cudaGetDeviceCountInternal(int *count, gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + _cuda_device_id *dev = ctx->GPGPUSim_Init(); + *count = dev->num_devices(); + return g_last_cudaError = cudaSuccess; +} + +__host__ cudaError_t CUDARTAPI cudaGetDevicePropertiesInternal( + struct cudaDeviceProp *prop, int device, gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + _cuda_device_id *dev = ctx->GPGPUSim_Init(); + if (device <= dev->num_devices()) { + *prop = *dev->get_prop(); + return g_last_cudaError = cudaSuccess; + } else { + return g_last_cudaError = cudaErrorInvalidDevice; + } +} + +__host__ cudaError_t CUDARTAPI +cudaChooseDeviceInternal(int *device, const struct cudaDeviceProp *prop, + gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + _cuda_device_id *dev = ctx->GPGPUSim_Init(); + *device = dev->get_id(); + return g_last_cudaError = cudaSuccess; +} + +cudaError_t cudaSetupArgumentInternal(const void *arg, size_t size, + size_t offset, + gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + gpgpusim_ptx_assert(!ctx->api->g_cuda_launch_stack.empty(), + "empty launch stack"); + kernel_config &config = ctx->api->g_cuda_launch_stack.back(); + config.set_arg(arg, size, offset); + printf( + "GPGPU-Sim PTX: Setting up arguments for %zu bytes starting at " + "0x%llx..\n", + size, (unsigned long long)arg); + + return g_last_cudaError = cudaSuccess; +} + +cudaError_t cudaLaunchInternal(const char *hostFun, + gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + CUctx_st *context = GPGPUSim_Context(ctx); + char *mode = getenv("PTX_SIM_MODE_FUNC"); + if (mode) sscanf(mode, "%u", &(ctx->func_sim->g_ptx_sim_mode)); + gpgpusim_ptx_assert(!ctx->api->g_cuda_launch_stack.empty(), + "empty launch stack"); + kernel_config config = ctx->api->g_cuda_launch_stack.back(); + { + dim3 gridDim = config.grid_dim(); + dim3 blockDim = config.block_dim(); + if (gridDim.x * gridDim.y * gridDim.z == 0 || + blockDim.x * blockDim.y * blockDim.z == 0) { + // can't launch + printf("can't launch a empty kernel\n"); + ctx->api->g_cuda_launch_stack.pop_back(); + return g_last_cudaError = cudaErrorInvalidConfiguration; + } + } + struct CUstream_st *stream = config.get_stream(); + + printf("\nGPGPU-Sim PTX: cudaLaunch for 0x%p (mode=%s) on stream %u\n", + hostFun, + (ctx->func_sim->g_ptx_sim_mode) ? "functional simulation" + : "performance simulation", + stream ? stream->get_uid() : 0); + kernel_info_t *grid = ctx->api->gpgpu_cuda_ptx_sim_init_grid( + hostFun, config.get_args(), config.grid_dim(), config.block_dim(), + context); + // do dynamic PDOM analysis for performance simulation scenario + std::string kname = grid->name(); + function_info *kernel_func_info = grid->entry(); + if (kernel_func_info->is_pdom_set()) { + printf("GPGPU-Sim PTX: PDOM analysis already done for %s \n", + kname.c_str()); + } else { + printf("GPGPU-Sim PTX: finding reconvergence points for \'%s\'...\n", + kname.c_str()); + kernel_func_info->do_pdom(); + kernel_func_info->set_pdom(); + } + dim3 gridDim = config.grid_dim(); + dim3 blockDim = config.block_dim(); + + gpgpu_t *gpu = context->get_device()->get_gpgpu(); + checkpoint *g_checkpoint; + g_checkpoint = new checkpoint(); + class memory_space *global_mem; + global_mem = gpu->get_global_memory(); + + if (gpu->resume_option == 1 && (grid->get_uid() == gpu->resume_kernel)) { + char f1name[2048]; + snprintf(f1name, 2048, "checkpoint_files/global_mem_%d.txt", + grid->get_uid()); + + g_checkpoint->load_global_mem(global_mem, f1name); + for (int i = 0; i < gpu->resume_CTA; i++) grid->increment_cta_id(); + } + if (gpu->resume_option == 1 && (grid->get_uid() < gpu->resume_kernel)) { + char f1name[2048]; + snprintf(f1name, 2048, "checkpoint_files/global_mem_%d.txt", + grid->get_uid()); + + g_checkpoint->load_global_mem(global_mem, f1name); + printf("Skipping kernel %d as resuming from kernel %d\n", grid->get_uid(), + gpu->resume_kernel); + ctx->api->g_cuda_launch_stack.pop_back(); + return g_last_cudaError = cudaSuccess; + } + if (gpu->checkpoint_option == 1 && + (grid->get_uid() > gpu->checkpoint_kernel)) { + printf("Skipping kernel %d as checkpoint from kernel %d\n", grid->get_uid(), + gpu->checkpoint_kernel); + ctx->api->g_cuda_launch_stack.pop_back(); + return g_last_cudaError = cudaSuccess; + } + printf( + "GPGPU-Sim PTX: pushing kernel \'%s\' to stream %u, gridDim= (%u,%u,%u) " + "blockDim = (%u,%u,%u) \n", + kname.c_str(), stream ? stream->get_uid() : 0, gridDim.x, gridDim.y, + gridDim.z, blockDim.x, blockDim.y, blockDim.z); + stream_operation op(grid, ctx->func_sim->g_ptx_sim_mode, stream); + ctx->the_gpgpusim->g_stream_manager->push(op); + ctx->api->g_cuda_launch_stack.pop_back(); + return g_last_cudaError = cudaSuccess; +} + +cudaError_t cudaMallocInternal(void **devPtr, size_t size, + gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + CUctx_st *context = GPGPUSim_Context(ctx); + *devPtr = context->get_device()->get_gpgpu()->gpu_malloc(size); + if (g_debug_execution >= 3) { + printf("GPGPU-Sim PTX: cudaMallocing %zu bytes starting at 0x%llx..\n", + size, (unsigned long long)*devPtr); + ctx->api->g_mallocPtr_Size[(unsigned long long)*devPtr] = size; + } + if (*devPtr) { + return g_last_cudaError = cudaSuccess; + } else { + return g_last_cudaError = cudaErrorMemoryAllocation; + } +} + +cudaError_t cudaMallocHostInternal(void **ptr, size_t size, + gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + *ptr = malloc(size); + if (*ptr) { + // track pinned memory size allocated in the host so that same amount of + // memory is also allocated in GPU. + ctx->api->pinned_memory_size[*ptr] = size; + return g_last_cudaError = cudaSuccess; + } else { + return g_last_cudaError = cudaErrorMemoryAllocation; + } +} + +__host__ cudaError_t CUDARTAPI +cudaMallocPitchInternal(void **devPtr, size_t *pitch, size_t width, + size_t height, gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + unsigned malloc_width_inbytes = width; + printf("GPGPU-Sim PTX: cudaMallocPitch (width = %d)\n", malloc_width_inbytes); + CUctx_st *context = GPGPUSim_Context(ctx); + *devPtr = context->get_device()->get_gpgpu()->gpu_malloc( + malloc_width_inbytes * height); + pitch[0] = malloc_width_inbytes; + if (*devPtr) { + return g_last_cudaError = cudaSuccess; + } else { + return g_last_cudaError = cudaErrorMemoryAllocation; + } +} + +cudaError_t cudaHostGetDevicePointerInternal(void **pDevice, void *pHost, + unsigned int flags, + gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + // only cpu memory allocation happens in cudaHostAlloc. Linking with device + // pointer to pinned memory happens here. + // TODO: once kernel is executed, the contents in global pointer of GPU must + // be copied back to CPU host pointer! + flags = 0; + CUctx_st *context = GPGPUSim_Context(ctx); + gpgpu_t *gpu = context->get_device()->get_gpgpu(); + std::map<void *, size_t>::const_iterator i = + ctx->api->pinned_memory_size.find(pHost); + assert(i != ctx->api->pinned_memory_size.end()); + size_t size = i->second; + *pDevice = gpu->gpu_malloc(size); + if (g_debug_execution >= 3) { + printf("GPGPU-Sim PTX: cudaMallocing %zu bytes starting at 0x%llx..\n", + size, (unsigned long long)*pDevice); + ctx->api->g_mallocPtr_Size[(unsigned long long)*pDevice] = size; + } + if (*pDevice) { + ctx->api->pinned_memory[pHost] = pDevice; + // Copy contents in cpu to gpu + gpu->memcpy_to_gpu((size_t)*pDevice, pHost, size); + return g_last_cudaError = cudaSuccess; + } else { + return g_last_cudaError = cudaErrorMemoryAllocation; + } +} + +__host__ cudaError_t CUDARTAPI cudaMallocArrayInternal( + struct cudaArray **array, const struct cudaChannelFormatDesc *desc, + size_t width, size_t height __dv(1), gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + unsigned size = + width * height * ((desc->x + desc->y + desc->z + desc->w) / 8); + CUctx_st *context = GPGPUSim_Context(ctx); + (*array) = (struct cudaArray *)malloc(sizeof(struct cudaArray)); + (*array)->desc = *desc; + (*array)->width = width; + (*array)->height = height; + (*array)->size = size; + (*array)->dimensions = 2; + ((*array)->devPtr32) = + (int)(long long)context->get_device()->get_gpgpu()->gpu_mallocarray(size); + printf("GPGPU-Sim PTX: cudaMallocArray: devPtr32 = %d\n", + ((*array)->devPtr32)); + ((*array)->devPtr) = (void *)(long long)((*array)->devPtr32); + if (((*array)->devPtr)) { + return g_last_cudaError = cudaSuccess; + } else { + return g_last_cudaError = cudaErrorMemoryAllocation; + } +} + +__host__ cudaError_t CUDARTAPI +cudaMemcpyInternal(void *dst, const void *src, size_t count, + enum cudaMemcpyKind kind, gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + // CUctx_st *context = GPGPUSim_Context(); + // gpgpu_t *gpu = context->get_device()->get_gpgpu(); + if (g_debug_execution >= 3) + printf("GPGPU-Sim PTX: cudaMemcpy(): devPtr = %p\n", dst); + if (kind == cudaMemcpyHostToDevice) + ctx->the_gpgpusim->g_stream_manager->push( + stream_operation(src, (size_t)dst, count, 0)); + else if (kind == cudaMemcpyDeviceToHost) + ctx->the_gpgpusim->g_stream_manager->push( + stream_operation((size_t)src, dst, count, 0)); + else if (kind == cudaMemcpyDeviceToDevice) + ctx->the_gpgpusim->g_stream_manager->push( + stream_operation((size_t)src, (size_t)dst, count, 0)); + else if (kind == cudaMemcpyDefault) { + if ((size_t)src >= GLOBAL_HEAP_START) { + if ((size_t)dst >= GLOBAL_HEAP_START) + ctx->the_gpgpusim->g_stream_manager->push(stream_operation( + (size_t)src, (size_t)dst, count, 0)); // device to device + else + ctx->the_gpgpusim->g_stream_manager->push( + stream_operation((size_t)src, dst, count, 0)); // device to host + } else { + if ((size_t)dst >= GLOBAL_HEAP_START) + ctx->the_gpgpusim->g_stream_manager->push( + stream_operation(src, (size_t)dst, count, 0)); + else { + printf( + "GPGPU-Sim PTX: cudaMemcpy - ERROR : unsupported transfer: host to " + "host\n"); + abort(); + } + } + } else { + printf("GPGPU-Sim PTX: cudaMemcpy - ERROR : unsupported cudaMemcpyKind\n"); + abort(); + } + return g_last_cudaError = cudaSuccess; +} + +__host__ cudaError_t CUDARTAPI cudaMemcpyToArrayInternal( + struct cudaArray *dst, size_t wOffset, size_t hOffset, const void *src, + size_t count, enum cudaMemcpyKind kind, gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + CUctx_st *context = GPGPUSim_Context(ctx); + gpgpu_t *gpu = context->get_device()->get_gpgpu(); + size_t size = count; + printf("GPGPU-Sim PTX: cudaMemcpyToArray\n"); + if (kind == cudaMemcpyHostToDevice) + gpu->memcpy_to_gpu((size_t)(dst->devPtr), src, size); + else if (kind == cudaMemcpyDeviceToHost) + gpu->memcpy_from_gpu(dst->devPtr, (size_t)src, size); + else if (kind == cudaMemcpyDeviceToDevice) + gpu->memcpy_gpu_to_gpu((size_t)(dst->devPtr), (size_t)src, size); + else { + printf( + "GPGPU-Sim PTX: cudaMemcpyToArray - ERROR : unsupported " + "cudaMemcpyKind\n"); + abort(); + } + dst->devPtr32 = (unsigned)(size_t)(dst->devPtr); + return g_last_cudaError = cudaSuccess; +} + +__host__ cudaError_t CUDARTAPI cudaMemcpy2DInternal( + void *dst, size_t dpitch, const void *src, size_t spitch, size_t width, + size_t height, enum cudaMemcpyKind kind, gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + CUctx_st *context = GPGPUSim_Context(ctx); + gpgpu_t *gpu = context->get_device()->get_gpgpu(); + size_t size = spitch * height; + gpgpusim_ptx_assert((dpitch == spitch), + "different src and dst pitch not supported yet"); + if (kind == cudaMemcpyHostToDevice) + gpu->memcpy_to_gpu((size_t)dst, src, size); + else if (kind == cudaMemcpyDeviceToHost) + gpu->memcpy_from_gpu(dst, (size_t)src, size); + else if (kind == cudaMemcpyDeviceToDevice) + gpu->memcpy_gpu_to_gpu((size_t)dst, (size_t)src, size); + else { + printf( + "GPGPU-Sim PTX: cudaMemcpy2D - ERROR : unsupported cudaMemcpyKind\n"); + abort(); + } + return g_last_cudaError = cudaSuccess; +} + +__host__ cudaError_t CUDARTAPI cudaMemcpy2DToArrayInternal( + struct cudaArray *dst, size_t wOffset, size_t hOffset, const void *src, + size_t spitch, size_t width, size_t height, enum cudaMemcpyKind kind, + gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + CUctx_st *context = GPGPUSim_Context(ctx); + gpgpu_t *gpu = context->get_device()->get_gpgpu(); + size_t size = spitch * height; + size_t channel_size = dst->desc.w + dst->desc.x + dst->desc.y + dst->desc.z; + gpgpusim_ptx_assert( + ((channel_size % 8) == 0), + "none byte multiple destination channel size not supported (sz=%u)", + channel_size); + unsigned elem_size = channel_size / 8; + gpgpusim_ptx_assert((dst->dimensions == 2), + "copy to none 2D array not supported"); + gpgpusim_ptx_assert((wOffset == 0), "non-zero wOffset not yet supported"); + gpgpusim_ptx_assert((hOffset == 0), "non-zero hOffset not yet supported"); + gpgpusim_ptx_assert((dst->height == (int)height), + "partial copy not supported"); + gpgpusim_ptx_assert((elem_size * dst->width == width), + "partial copy not supported"); + gpgpusim_ptx_assert((spitch == width), "spitch != width not supported"); + if (kind == cudaMemcpyHostToDevice) + gpu->memcpy_to_gpu((size_t)(dst->devPtr), src, size); + else if (kind == cudaMemcpyDeviceToHost) + gpu->memcpy_from_gpu(dst->devPtr, (size_t)src, size); + else if (kind == cudaMemcpyDeviceToDevice) + gpu->memcpy_gpu_to_gpu((size_t)dst->devPtr, (size_t)src, size); + else { + printf( + "GPGPU-Sim PTX: cudaMemcpy2D - ERROR : unsupported cudaMemcpyKind\n"); + abort(); + } + dst->devPtr32 = (unsigned)(size_t)(dst->devPtr); + return g_last_cudaError = cudaSuccess; +} + +__host__ cudaError_t CUDARTAPI cudaMemcpyToSymbolInternal( + const char *symbol, const void *src, size_t count, size_t offset __dv(0), + enum cudaMemcpyKind kind __dv(cudaMemcpyHostToDevice), + gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + // CUctx_st *context = GPGPUSim_Context(); + assert(kind == cudaMemcpyHostToDevice); + printf("GPGPU-Sim PTX: cudaMemcpyToSymbol: symbol = %p\n", symbol); + // stream_operation( const char *symbol, const void *src, size_t count, size_t + // offset ) + ctx->the_gpgpusim->g_stream_manager->push( + stream_operation(src, symbol, count, offset, 0)); + // gpgpu_ptx_sim_memcpy_symbol(symbol,src,count,offset,1,context->get_device()->get_gpgpu()); + return g_last_cudaError = cudaSuccess; +} + +__host__ cudaError_t CUDARTAPI cudaMemcpyFromSymbolInternal( + void *dst, const char *symbol, size_t count, size_t offset __dv(0), + enum cudaMemcpyKind kind __dv(cudaMemcpyDeviceToHost), + gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + // CUctx_st *context = GPGPUSim_Context(); + assert(kind == cudaMemcpyDeviceToHost); + printf("GPGPU-Sim PTX: cudaMemcpyFromSymbol: symbol = %p\n", symbol); + ctx->the_gpgpusim->g_stream_manager->push( + stream_operation(symbol, dst, count, offset, 0)); + // gpgpu_ptx_sim_memcpy_symbol(symbol,dst,count,offset,0,context->get_device()->get_gpgpu()); + return g_last_cudaError = cudaSuccess; +} + +__host__ cudaError_t CUDARTAPI cudaMemcpyAsyncInternal( + void *dst, const void *src, size_t count, enum cudaMemcpyKind kind, + cudaStream_t stream, gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + struct CUstream_st *s = (struct CUstream_st *)stream; + switch (kind) { + case cudaMemcpyHostToDevice: + ctx->the_gpgpusim->g_stream_manager->push( + stream_operation(src, (size_t)dst, count, s)); + break; + case cudaMemcpyDeviceToHost: + ctx->the_gpgpusim->g_stream_manager->push( + stream_operation((size_t)src, dst, count, s)); + break; + case cudaMemcpyDeviceToDevice: + ctx->the_gpgpusim->g_stream_manager->push( + stream_operation((size_t)src, (size_t)dst, count, s)); + break; + default: + abort(); + } + return g_last_cudaError = cudaSuccess; +} + +#if (CUDART_VERSION >= 8000) +cudaError_t CUDARTAPI +cudaOccupancyMaxActiveBlocksPerMultiprocessorWithFlagsInternal( + int *numBlocks, const char *hostFunc, int blockSize, size_t dynamicSMemSize, + unsigned int flags, gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + printf( + "GPGPU-Sim PTX: cudaOccupancyMaxActiveBlocksPerMultiprocessorWithFlags " + "%p\n", + hostFunc); + CUctx_st *context = GPGPUSim_Context(ctx); + function_info *entry = context->get_kernel(hostFunc); + printf( + "Calculate Maxium Active Block with function ptr=%p, blockSize=%d, " + "SMemSize=%d\n", + hostFunc, blockSize, dynamicSMemSize); + if (flags == cudaOccupancyDefault) { + // create kernel_info based on entry + dim3 gridDim(context->get_device()->get_gpgpu()->max_cta_per_core() * + context->get_device()->get_gpgpu()->get_config().num_shader()); + dim3 blockDim(blockSize); + kernel_info_t result(gridDim, blockDim, entry); + // if(entry == NULL){ + // *numBlocks = 1; + // return g_last_cudaError = cudaErrorUnknown; + //} + *numBlocks = context->get_device()->get_gpgpu()->get_max_cta(result); + printf("Maximum size is %d with gridDim %d and blockDim %d\n", *numBlocks, + gridDim.x, blockDim.x); + return g_last_cudaError = cudaSuccess; + } else { + cuda_not_implemented(__my_func__, __LINE__); + return g_last_cudaError = cudaErrorUnknown; + } +} + +#endif + +__host__ cudaError_t CUDARTAPI cudaMemsetInternal( + void *mem, int c, size_t count, gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + CUctx_st *context = GPGPUSim_Context(ctx); + gpgpu_t *gpu = context->get_device()->get_gpgpu(); + gpu->gpu_memset((size_t)mem, c, count); + return g_last_cudaError = cudaSuccess; +} + +// memset operation is done but i think its not async? +__host__ cudaError_t CUDARTAPI +cudaMemsetAsyncInternal(void *mem, int c, size_t count, cudaStream_t stream = 0, + gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("GPGPU-Sim PTX: WARNING: Asynchronous memset not supported (%s)\n", + __my_func__); + CUctx_st *context = GPGPUSim_Context(ctx); + gpgpu_t *gpu = context->get_device()->get_gpgpu(); + gpu->gpu_memset((size_t)mem, c, count); + return g_last_cudaError = cudaSuccess; +} + +cudaError_t cudaGLMapBufferObjectInternal(void **devPtr, GLuint bufferObj, + gpgpu_context *gpgpu_ctx = NULL) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } +#ifdef OPENGL_SUPPORT + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + GLint buffer_size = 0; + CUctx_st *context = GPGPUSim_Context(ctx); + + glbmap_entry_t *p = ctx->api->g_glbmap; + while (p && p->m_bufferObj != bufferObj) p = p->m_next; + if (p == NULL) { + glBindBuffer(GL_ARRAY_BUFFER, bufferObj); + glGetBufferParameteriv(GL_ARRAY_BUFFER, GL_BUFFER_SIZE, &buffer_size); + assert(buffer_size != 0); + *devPtr = context->get_device()->get_gpgpu()->gpu_malloc(buffer_size); + + // create entry and insert to front of list + glbmap_entry_t *n = (glbmap_entry_t *)calloc(1, sizeof(glbmap_entry_t)); + n->m_next = ctx->api->g_glbmap; + ctx->api->g_glbmap = n; + + // initialize entry + n->m_bufferObj = bufferObj; + n->m_devPtr = *devPtr; + n->m_size = buffer_size; + + p = n; + } else { + buffer_size = p->m_size; + *devPtr = p->m_devPtr; + } + + if (*devPtr) { + char *data = (char *)calloc(p->m_size, 1); + glGetBufferSubData(GL_ARRAY_BUFFER, 0, buffer_size, data); + memcpy_to_gpu((size_t)*devPtr, data, buffer_size); + free(data); + printf( + "GPGPU-Sim PTX: cudaGLMapBufferObject %zu bytes starting at 0x%llx..\n", + (size_t)buffer_size, (unsigned long long)*devPtr); + return g_last_cudaError = cudaSuccess; + } else { + return g_last_cudaError = cudaErrorMemoryAllocation; + } + + return g_last_cudaError = cudaSuccess; +#else + fflush(stdout); + fflush(stderr); + printf( + "GPGPU-Sim PTX: GPGPU-Sim support for OpenGL integration disabled -- " + "exiting\n"); + fflush(stdout); + exit(50); +#endif +} + +#if CUDART_VERSION >= 6050 +CUresult cuLinkAddFileInternal(CUlinkState state, CUjitInputType type, + const char *path, unsigned int numOptions, + CUjit_option *options, void **optionValues, + gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + static bool addedFile = false; + if (addedFile) { + printf( + "GPGPU-Sim PTX: ERROR: cuLinkAddFile does not support multiple " + "files\n"); + abort(); + } + + // blocking + assert(type == CU_JIT_INPUT_PTX); + CUctx_st *context = GPGPUSim_Context(ctx); + char *file = getenv("PTX_JIT_PATH"); + if (file == NULL) { + printf("GPGPU-Sim PTX: ERROR: PTX_JIT_PATH has not been set\n"); + abort(); + } + strcat(file, "/"); + strcat(file, path); + symbol_table *symtab = ctx->gpgpu_ptx_sim_load_ptx_from_filename(file); + std::string fname(path); + ctx->api->name_symtab[fname] = symtab; + context->add_binary(symtab, 1); + ctx->api->load_static_globals(symtab, STATIC_ALLOC_LIMIT, 0xFFFFFFFF, + context->get_device()->get_gpgpu()); + ctx->api->load_constants(symtab, STATIC_ALLOC_LIMIT, + context->get_device()->get_gpgpu()); + addedFile = true; + return CUDA_SUCCESS; +} +#endif - cudaDeviceProp *prop = (cudaDeviceProp *) calloc(sizeof(cudaDeviceProp),1); - snprintf(prop->name,256,"GPGPU-Sim_v%s", g_gpgpusim_version_string ); - prop->major = 5; - prop->minor = 2; - prop->totalGlobalMem = 0x80000000 /* 2 GB */; - prop->memPitch = 0; - prop->maxThreadsPerBlock = 512; - prop->maxThreadsDim[0] = 512; - prop->maxThreadsDim[1] = 512; - prop->maxThreadsDim[2] = 512; - prop->maxGridSize[0] = 0x40000000; - prop->maxGridSize[1] = 0x40000000; - prop->maxGridSize[2] = 0x40000000; - prop->totalConstMem = 0x40000000; - prop->textureAlignment = 0; - prop->sharedMemPerBlock = the_gpu->shared_mem_size(); - prop->regsPerBlock = the_gpu->num_registers_per_core(); - prop->warpSize = the_gpu->wrp_size(); - prop->clockRate = the_gpu->shader_clock(); #if (CUDART_VERSION >= 2010) - prop->multiProcessorCount = the_gpu->get_config().num_shader(); + +cudaError_t cudaHostAllocInternal(void **pHost, size_t bytes, + unsigned int flags, + gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + *pHost = malloc(bytes); + // need to track the size allocated so that cudaHostGetDevicePointer() can + // function properly. + // TODO: vary this function behavior based on flags value (following nvidia + // documentation) + ctx->api->pinned_memory_size[*pHost] = bytes; + if (*pHost) + return g_last_cudaError = cudaSuccess; + else + return g_last_cudaError = cudaErrorMemoryAllocation; +} + #endif - the_gpu->set_prop(prop); - the_device = new _cuda_device_id(the_gpu); - } - start_sim_thread(1); - return the_device; + +size_t getMaxThreadsPerBlock(struct cudaFuncAttributes *attr, + gpgpu_context *ctx) { + _cuda_device_id *dev = ctx->GPGPUSim_Init(); + struct cudaDeviceProp prop; + + prop = *dev->get_prop(); + + size_t max = prop.maxThreadsPerBlock; + + if (attr->numRegs && (prop.regsPerBlock / attr->numRegs) < max) + max = prop.regsPerBlock / attr->numRegs; + + if (attr->sharedSizeBytes && + (prop.sharedMemPerBlock / attr->sharedSizeBytes) < max) + max = prop.sharedMemPerBlock / attr->sharedSizeBytes; + + return max; } -static CUctx_st* GPGPUSim_Context() -{ - static CUctx_st *the_context = NULL; - if( the_context == NULL ) { - _cuda_device_id *the_gpu = GPGPUSim_Init(); - the_context = new CUctx_st(the_gpu); - } - return the_context; +cudaError_t CUDARTAPI cudaFuncGetAttributesInternal( + struct cudaFuncAttributes *attr, const char *hostFun, + gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + CUctx_st *context = GPGPUSim_Context(ctx); + function_info *entry = context->get_kernel(hostFun); + if (entry) { + const struct gpgpu_ptx_sim_info *kinfo = entry->get_kernel_info(); + attr->sharedSizeBytes = kinfo->smem; + attr->constSizeBytes = kinfo->cmem; + attr->localSizeBytes = kinfo->lmem; + attr->numRegs = kinfo->regs; + if (kinfo->maxthreads > 0) + attr->maxThreadsPerBlock = kinfo->maxthreads; + else + attr->maxThreadsPerBlock = getMaxThreadsPerBlock(attr, ctx); +#if CUDART_VERSION >= 3000 + attr->ptxVersion = kinfo->ptx_version; + attr->binaryVersion = kinfo->sm_target; +#endif + } + return g_last_cudaError = cudaSuccess; } - void ptxinfo_addinfo() -{ - if(!get_ptxinfo_kname()){ - /* This info is not per kernel (since CUDA 5.0 some info (e.g. gmem, and cmem) is added at the beginning for the whole binary ) */ - CUctx_st *context = GPGPUSim_Context(); - print_ptxinfo(); - context->add_ptxinfo(get_ptxinfo()); - clear_ptxinfo(); - return; - } - if( !strcmp("__cuda_dummy_entry__",get_ptxinfo_kname()) ) { - // this string produced by ptxas for empty ptx files (e.g., bandwidth test) - clear_ptxinfo(); - return; - } - CUctx_st *context = GPGPUSim_Context(); - print_ptxinfo(); - context->add_ptxinfo( get_ptxinfo_kname(), get_ptxinfo() ); - clear_ptxinfo(); +#if (CUDART_VERSION > 5000) +__host__ cudaError_t CUDARTAPI +cudaDeviceGetAttributeInternal(int *value, enum cudaDeviceAttr attr, int device, + gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + + const struct cudaDeviceProp *prop; + _cuda_device_id *dev = ctx->GPGPUSim_Init(); + + if (device <= dev->num_devices()) { + prop = dev->get_prop(); + switch (attr) { + case 1: + *value = prop->maxThreadsPerBlock; + break; + case 2: + *value = prop->maxThreadsDim[0]; + break; + case 3: + *value = prop->maxThreadsDim[1]; + break; + case 4: + *value = prop->maxThreadsDim[2]; + break; + case 5: + *value = prop->maxGridSize[0]; + break; + case 6: + *value = prop->maxGridSize[1]; + break; + case 7: + *value = prop->maxGridSize[2]; + break; + case 8: + *value = prop->sharedMemPerBlock; + break; + case 9: + *value = prop->totalConstMem; + break; + case 10: + *value = prop->warpSize; + break; + case 11: + *value = 16; // dummy value + break; + case 12: + *value = prop->regsPerBlock; + break; + case 13: + *value = 1480000; // for 1080ti + break; + case 14: + *value = prop->textureAlignment; + break; + case 15: + *value = 0; + break; + case 16: + *value = prop->multiProcessorCount; + break; + case 17: + case 18: + case 19: + *value = 0; + break; + case 21: + case 22: + case 23: + case 24: + case 25: + case 26: + case 27: + case 28: + case 42: + case 45: + case 46: + case 47: + case 48: + case 49: + case 52: + case 53: + case 55: + case 56: + case 57: + case 58: + case 59: + case 60: + case 61: + case 62: + case 63: + case 64: + case 66: + case 67: + case 69: + case 70: + case 71: + case 73: + case 74: + case 77: + *value = 1000; // dummy value + break; + case 29: + case 43: + case 54: + case 65: + case 68: + case 72: + *value = 10; // dummy value + break; + case 30: + case 51: + *value = 128; // dummy value + break; + case 31: + *value = 1; + break; + case 32: + *value = 0; + break; + case 33: + case 50: + *value = 0; // dummy value + break; + case 34: + *value = 0; + break; + case 35: + *value = 0; + break; + case 36: + *value = 1250000; // CK value for 1080ti + break; + case 37: + *value = 352; // value for 1080ti + break; + case 38: + *value = 3000000; // value for 1080ti + break; + case 39: + *value = dev->get_gpgpu()->threads_per_core(); + break; + case 40: + *value = 0; + break; + case 41: + *value = 0; + break; + case 75: // cudaDevAttrComputeCapabilityMajor + *value = prop->major; + break; + case 76: // cudaDevAttrComputeCapabilityMinor + *value = prop->minor; + break; + case 78: + *value = 0; // TODO: as of now, we dont support stream priorities. + break; + case 79: + *value = 0; + break; + case 80: + *value = 0; + break; +#if (CUDART_VERSION > 5050) + case 81: + *value = prop->sharedMemPerMultiprocessor; + break; + case 82: + *value = prop->regsPerMultiprocessor; + break; +#endif + case 83: + case 84: + case 85: + case 86: + *value = 0; + break; + case 87: + *value = 4; // dummy value + break; + case 88: + case 89: + *value = 0; + break; + default: + printf("ERROR: Attribute number %d unimplemented \n", attr); + abort(); + } + return g_last_cudaError = cudaSuccess; + } else { + return g_last_cudaError = cudaErrorInvalidDevice; + } } +#endif -void cuda_not_implemented( const char* func, unsigned line ) -{ - fflush(stdout); - fflush(stderr); - printf("\n\nGPGPU-Sim PTX: Execution error: CUDA API function \"%s()\" has not been implemented yet.\n" - " [$GPGPUSIM_ROOT/libcuda/%s around line %u]\n\n\n", - func,__FILE__, line ); - fflush(stdout); - abort(); +__host__ cudaError_t CUDARTAPI cudaBindTextureInternal( + size_t *offset, const struct textureReference *texref, const void *devPtr, + const struct cudaChannelFormatDesc *desc, size_t size __dv(UINT_MAX), + gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + CUctx_st *context = GPGPUSim_Context(ctx); + gpgpu_t *gpu = context->get_device()->get_gpgpu(); + printf( + "GPGPU-Sim PTX: in cudaBindTexture: sizeof(struct textureReference) = " + "%zu\n", + sizeof(struct textureReference)); + struct cudaArray *array; + array = (struct cudaArray *)malloc(sizeof(struct cudaArray)); + array->desc = *desc; + array->size = size; + array->width = size; + array->height = 1; + array->dimensions = 1; + array->devPtr = (void *)devPtr; + array->devPtr32 = (int)(long long)devPtr; + offset = 0; + printf("GPGPU-Sim PTX: size = %zu\n", size); + printf("GPGPU-Sim PTX: texref = %p, array = %p\n", texref, array); + printf("GPGPU-Sim PTX: devPtr32 = %x\n", array->devPtr32); + printf("GPGPU-Sim PTX: Name corresponding to textureReference: %s\n", + gpu->gpgpu_ptx_sim_findNamefromTexture(texref)); + printf("GPGPU-Sim PTX: ChannelFormatDesc: x=%d, y=%d, z=%d, w=%d\n", + desc->x, desc->y, desc->z, desc->w); + printf("GPGPU-Sim PTX: Texture Normalized? = %d\n", texref->normalized); + gpu->gpgpu_ptx_sim_bindTextureToArray(texref, array); + devPtr = (void *)(long long)array->devPtr32; + printf("GPGPU-Sim PTX: devPtr = %p\n", devPtr); + return g_last_cudaError = cudaSuccess; +} + +__host__ cudaError_t CUDARTAPI cudaBindTextureToArrayInternal( + const struct textureReference *texref, const struct cudaArray *array, + const struct cudaChannelFormatDesc *desc, gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + CUctx_st *context = GPGPUSim_Context(ctx); + gpgpu_t *gpu = context->get_device()->get_gpgpu(); + printf("GPGPU-Sim PTX: in cudaBindTextureToArray: %p %p\n", texref, array); + printf("GPGPU-Sim PTX: devPtr32 = %x\n", array->devPtr32); + printf("GPGPU-Sim PTX: Name corresponding to textureReference: %s\n", + gpu->gpgpu_ptx_sim_findNamefromTexture(texref)); + printf("GPGPU-Sim PTX: Texture Normalized? = %d\n", texref->normalized); + gpu->gpgpu_ptx_sim_bindTextureToArray(texref, array); + return g_last_cudaError = cudaSuccess; } +__host__ cudaError_t CUDARTAPI cudaUnbindTextureInternal( + const struct textureReference *texref, gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + CUctx_st *context = GPGPUSim_Context(ctx); + gpgpu_t *gpu = context->get_device()->get_gpgpu(); + printf( + "GPGPU-Sim PTX: in cudaUnbindTexture: sizeof(struct textureReference) = " + "%zu\n", + sizeof(struct textureReference)); + printf("GPGPU-Sim PTX: Name corresponding to textureReference: %s\n", + gpu->gpgpu_ptx_sim_findNamefromTexture(texref)); + + gpu->gpgpu_ptx_sim_unbindTexture(texref); + return g_last_cudaError = cudaSuccess; +} -#define gpgpusim_ptx_error(msg, ...) gpgpusim_ptx_error_impl(__func__, __FILE__,__LINE__, msg, ##__VA_ARGS__) -#define gpgpusim_ptx_assert(cond,msg, ...) gpgpusim_ptx_assert_impl((cond),__func__, __FILE__,__LINE__, msg, ##__VA_ARGS__) +__host__ cudaError_t CUDARTAPI cudaLaunchKernelInternal( + const char *hostFun, dim3 gridDim, dim3 blockDim, const void **args, + size_t sharedMem, cudaStream_t stream, gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } -void gpgpusim_ptx_error_impl( const char *func, const char *file, unsigned line, const char *msg, ... ) -{ - va_list ap; - char buf[1024]; - va_start(ap,msg); - vsnprintf(buf,1024,msg,ap); - va_end(ap); + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + CUctx_st *context = GPGPUSim_Context(ctx); + function_info *entry = context->get_kernel(hostFun); +#if CUDART_VERSION < 10000 + cudaConfigureCallInternal(gridDim, blockDim, sharedMem, stream, ctx); +#endif + for (unsigned i = 0; i < entry->num_args(); i++) { + std::pair<size_t, unsigned> p = entry->get_param_config(i); + cudaSetupArgumentInternal(args[i], p.first, p.second); + } - printf("GPGPU-Sim CUDA API: %s\n", buf); - printf(" [%s:%u : %s]\n", file, line, func ); - abort(); + cudaLaunchInternal(hostFun); + return g_last_cudaError = cudaSuccess; } -void gpgpusim_ptx_assert_impl( int test_value, const char *func, const char *file, unsigned line, const char *msg, ... ) +__host__ cudaError_t CUDARTAPI cudaStreamCreateInternal( + cudaStream_t *stream, gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("GPGPU-Sim PTX: cudaStreamCreate\n"); +#if (CUDART_VERSION >= 3000) + *stream = new struct CUstream_st(); + ctx->the_gpgpusim->g_stream_manager->add_stream(*stream); +#else + *stream = 0; + printf( + "GPGPU-Sim PTX: WARNING: Asynchronous kernel execution not supported " + "(%s)\n", + __my_func__); +#endif + return g_last_cudaError = cudaSuccess; +} + +__host__ cudaError_t CUDARTAPI cudaStreamDestroyInternal( + cudaStream_t stream, gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } +#if (CUDART_VERSION >= 3000) + // per-stream synchronization required for application using external + // libraries without explicit synchronization in the code to avoid the + // stream_manager from spinning forever to destroy non-empty streams without + // making any forward progress. + stream->synchronize(); + ctx->the_gpgpusim->g_stream_manager->destroy_stream(stream); +#endif + return g_last_cudaError = cudaSuccess; +} + +__host__ cudaError_t CUDARTAPI cudaStreamSynchronizeInternal( + cudaStream_t stream, gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } +#if (CUDART_VERSION >= 3000) + if (stream == NULL) ctx->synchronize(); + return g_last_cudaError = cudaSuccess; + stream->synchronize(); +#else + printf( + "GPGPU-Sim PTX: WARNING: Asynchronous kernel execution not supported " + "(%s)\n", + __my_func__); +#endif + return g_last_cudaError = cudaSuccess; +} + +void __cudaRegisterTextureInternal( + void **fatCubinHandle, const struct textureReference *hostVar, + const void **deviceAddress, const char *deviceName, int dim, int norm, + int ext, + gpgpu_context *gpgpu_ctx = + NULL) // passes in a newly created textureReference { - va_list ap; - char buf[1024]; - va_start(ap,msg); - vsnprintf(buf,1024,msg,ap); - va_end(ap); + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + std::string devStr(deviceName); +#if (CUDART_VERSION > 4020) + if (devStr.size() > 2 && devStr.data()[0] == ':' && devStr.data()[1] == ':') + devStr = devStr.replace(0, 2, ""); +#endif + CUctx_st *context = GPGPUSim_Context(ctx); + gpgpu_t *gpu = context->get_device()->get_gpgpu(); + printf("GPGPU-Sim PTX: in __cudaRegisterTexture:\n"); + gpu->gpgpu_ptx_sim_bindNameToTexture(devStr.data(), hostVar, dim, norm, ext); + printf("GPGPU-Sim PTX: int dim = %d\n", dim); + printf("GPGPU-Sim PTX: int norm = %d\n", norm); + printf("GPGPU-Sim PTX: int ext = %d\n", ext); + printf( + "GPGPU-Sim PTX: Execution warning: Not finished implementing \"%s\"\n", + __my_func__); +} - if ( test_value == 0 ) - gpgpusim_ptx_error_impl(func, file, line, msg); +cudaError_t cudaGLUnmapBufferObjectInternal(GLuint bufferObj, + gpgpu_context *gpgpu_ctx = NULL) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } +#ifdef OPENGL_SUPPORT + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + CUctx_st *ctx = GPGPUSim_Context(ctx); + glbmap_entry_t *p = ctx->api->g_glbmap; + while (p && p->m_bufferObj != bufferObj) p = p->m_next; + if (p == NULL) return g_last_cudaError = cudaErrorUnknown; + + char *data = (char *)calloc(p->m_size, 1); + memcpy_from_gpu(data, (size_t)p->m_devPtr, p->m_size); + glBufferSubData(GL_ARRAY_BUFFER, 0, p->m_size, data); + free(data); + + return g_last_cudaError = cudaSuccess; +#else + fflush(stdout); + fflush(stderr); + printf("GPGPU-Sim PTX: support for OpenGL integration disabled -- exiting\n"); + fflush(stdout); + exit(50); +#endif } +#if CUDART_VERSION >= 3000 -typedef std::map<unsigned,CUevent_st*> event_tracker_t; +__host__ cudaError_t CUDARTAPI +cudaFuncSetCacheConfigInternal(const char *func, enum cudaFuncCache cacheConfig, + gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + CUctx_st *context = GPGPUSim_Context(ctx); + context->get_device()->get_gpgpu()->set_cache_config( + context->get_kernel(func)->get_name(), (FuncCache)cacheConfig); + return g_last_cudaError = cudaSuccess; +} -int CUevent_st::m_next_event_uid; -event_tracker_t g_timer_events; -int g_active_device = 0; //active gpu that runs the code -std::list<kernel_config> g_cuda_launch_stack; +#endif + +#if CUDART_VERSION >= 4000 +CUresult CUDAAPI cuLaunchKernelInternal( + CUfunction f, unsigned int gridDimX, unsigned int gridDimY, + unsigned int gridDimZ, unsigned int blockDimX, unsigned int blockDimY, + unsigned int blockDimZ, unsigned int sharedMemBytes, CUstream hStream, + void **kernelParams, void **extra, gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + if (extra != NULL) { + printf( + "GPGPU-Sim CUDA DRIVER API: ERROR: Currently do not support void** " + "extra.\n"); + abort(); + } + const char *hostFun = (const char *)f; + CUctx_st *context = GPGPUSim_Context(ctx); + function_info *entry = context->get_kernel(hostFun); + cudaConfigureCallInternal(dim3(gridDimX, gridDimY, gridDimZ), + dim3(blockDimX, blockDimY, blockDimZ), + sharedMemBytes, (cudaStream_t)hStream, ctx); + for (unsigned i = 0; i < entry->num_args(); i++) { + std::pair<size_t, unsigned> p = entry->get_param_config(i); + cudaSetupArgumentInternal(kernelParams[i], p.first, p.second, ctx); + } + cudaLaunchInternal(hostFun, ctx); + return CUDA_SUCCESS; +} +#endif /* CUDART_VERSION >= 4000 */ + +CUevent_st *get_event(cudaEvent_t event) { + unsigned event_uid; +#if CUDART_VERSION >= 3000 + event_uid = event->get_uid(); +#else + event_uid = event; +#endif + event_tracker_t::iterator e = g_timer_events.find(event_uid); + if (e == g_timer_events.end()) return NULL; + return e->second; +} + +__host__ cudaError_t CUDARTAPI cudaEventRecordInternal( + cudaEvent_t event, cudaStream_t stream, gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + CUevent_st *e = get_event(event); + if (!e) return g_last_cudaError = cudaErrorUnknown; + struct CUstream_st *s = (struct CUstream_st *)stream; + stream_operation op(e, s); + e->issue(); + ctx->the_gpgpusim->g_stream_manager->push(op); + return g_last_cudaError = cudaSuccess; +} + +__host__ cudaError_t CUDARTAPI cudaStreamWaitEventInternal( + cudaStream_t stream, cudaEvent_t event, unsigned int flags, + gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + // reference: + // https://www.cs.cmu.edu/afs/cs/academic/class/15668-s11/www/cuda-doc/html/group__CUDART__STREAM_gfe68d207dc965685d92d3f03d77b0876.html + CUevent_st *e = get_event(event); + if (!e) { + printf( + "GPGPU-Sim API: Error at cudaStreamWaitEvent. Event is not created " + ".\n"); + return g_last_cudaError = cudaErrorInvalidResourceHandle; + } else if (e->num_issued() == 0) { + printf( + "GPGPU-Sim API: Warning: cudaEventRecord has not been called on event " + "before calling cudaStreamWaitEvent.\nNothin g to be done.\n"); + return g_last_cudaError = cudaSuccess; + } + if (!stream) { + ctx->the_gpgpusim->g_stream_manager->pushCudaStreamWaitEventToAllStreams( + e, flags); + } else { + struct CUstream_st *s = (struct CUstream_st *)stream; + stream_operation op(s, e, flags); + ctx->the_gpgpusim->g_stream_manager->push(op); + } + return g_last_cudaError = cudaSuccess; +} + +__host__ cudaError_t CUDARTAPI +cudaThreadExitInternal(gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + ctx->exit_simulation(); + return g_last_cudaError = cudaSuccess; +} + +__host__ cudaError_t CUDARTAPI +cudaThreadSynchronizeInternal(gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + // Called on host side + ctx->synchronize(); + return g_last_cudaError = cudaSuccess; +} + +cudaError_t CUDARTAPI +cudaDeviceSynchronizeInternal(gpgpu_context *gpgpu_ctx = NULL) { + gpgpu_context *ctx; + if (gpgpu_ctx) { + ctx = gpgpu_ctx; + } else { + ctx = GPGPU_Context(); + } + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + // Blocks until the device has completed all preceding requested tasks + ctx->synchronize(); + return g_last_cudaError = cudaSuccess; +} /******************************************************************************* * * @@ -451,304 +2302,360 @@ extern "C" { * * * * *******************************************************************************/ -cudaError_t cudaPeekAtLastError(void) -{ - return g_last_cudaError; -} +cudaError_t cudaPeekAtLastError(void) { return g_last_cudaError; } -__host__ cudaError_t CUDARTAPI cudaMalloc(void **devPtr, size_t size) -{ - CUctx_st* context = GPGPUSim_Context(); - *devPtr = context->get_device()->get_gpgpu()->gpu_malloc(size); - if(g_debug_execution >= 3) - printf("GPGPU-Sim PTX: cudaMallocing %zu bytes starting at 0x%llx..\n",size, (unsigned long long) *devPtr); - if ( *devPtr ) { - return g_last_cudaError = cudaSuccess; - } else { - return g_last_cudaError = cudaErrorMemoryAllocation; - } +__host__ cudaError_t CUDARTAPI cudaMalloc(void **devPtr, size_t size) { + return cudaMallocInternal(devPtr, size); } -__host__ cudaError_t CUDARTAPI cudaMallocHost(void **ptr, size_t size) -{ - GPGPUSim_Context(); - *ptr = malloc(size); - if ( *ptr ) { - return g_last_cudaError = cudaSuccess; - } else { - return g_last_cudaError = cudaErrorMemoryAllocation; - } +__host__ cudaError_t CUDARTAPI cudaMallocHost(void **ptr, size_t size) { + return cudaMallocHostInternal(ptr, size); } -__host__ cudaError_t CUDARTAPI cudaMallocPitch(void **devPtr, size_t *pitch, size_t width, size_t height) -{ - unsigned malloc_width_inbytes = width; - printf("GPGPU-Sim PTX: cudaMallocPitch (width = %d)\n", malloc_width_inbytes); - CUctx_st* ctx = GPGPUSim_Context(); - *devPtr = ctx->get_device()->get_gpgpu()->gpu_malloc(malloc_width_inbytes*height); - pitch[0] = malloc_width_inbytes; - if ( *devPtr ) { - return g_last_cudaError = cudaSuccess; - } else { - return g_last_cudaError = cudaErrorMemoryAllocation; - } +__host__ cudaError_t CUDARTAPI cudaMallocPitch(void **devPtr, size_t *pitch, + size_t width, size_t height) { + return cudaMallocPitchInternal(devPtr, pitch, width, height); } -__host__ cudaError_t CUDARTAPI cudaMallocArray(struct cudaArray **array, const struct cudaChannelFormatDesc *desc, size_t width, size_t height __dv(1)) -{ - unsigned size = width * height * ((desc->x + desc->y + desc->z + desc->w)/8); - CUctx_st* context = GPGPUSim_Context(); - (*array) = (struct cudaArray*) malloc(sizeof(struct cudaArray)); - (*array)->desc = *desc; - (*array)->width = width; - (*array)->height = height; - (*array)->size = size; - (*array)->dimensions = 2; - ((*array)->devPtr32)= (int) (long long)context->get_device()->get_gpgpu()->gpu_mallocarray(size); - printf("GPGPU-Sim PTX: cudaMallocArray: devPtr32 = %d\n", ((*array)->devPtr32)); - ((*array)->devPtr) = (void*) (long long) ((*array)->devPtr32); - if ( ((*array)->devPtr) ) { - return g_last_cudaError = cudaSuccess; - } else { - return g_last_cudaError = cudaErrorMemoryAllocation; - } +__host__ cudaError_t CUDARTAPI cudaMallocArray( + struct cudaArray **array, const struct cudaChannelFormatDesc *desc, + size_t width, size_t height __dv(1)) { + return cudaMallocArrayInternal(array, desc, width, height); } -__host__ cudaError_t CUDARTAPI cudaFree(void *devPtr) -{ - // TODO... manage g_global_mem space? - return g_last_cudaError = cudaSuccess; +__host__ cudaError_t CUDARTAPI cudaFree(void *devPtr) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + // TODO... manage g_global_mem space? + return g_last_cudaError = cudaSuccess; } -__host__ cudaError_t CUDARTAPI cudaFreeHost(void *ptr) -{ - free (ptr); // this will crash the system if called twice - return g_last_cudaError = cudaSuccess; +__host__ cudaError_t CUDARTAPI cudaFreeHost(void *ptr) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + free(ptr); // this will crash the system if called twice + return g_last_cudaError = cudaSuccess; } -__host__ cudaError_t CUDARTAPI cudaFreeArray(struct cudaArray *array) -{ - // TODO... manage g_global_mem space? - return g_last_cudaError = cudaSuccess; +__host__ cudaError_t CUDARTAPI cudaFreeArray(struct cudaArray *array) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + // TODO... manage g_global_mem space? + return g_last_cudaError = cudaSuccess; }; - /******************************************************************************* * * * * * * *******************************************************************************/ -__host__ cudaError_t CUDARTAPI cudaMemcpy(void *dst, const void *src, size_t count, enum cudaMemcpyKind kind) -{ - //CUctx_st *context = GPGPUSim_Context(); - //gpgpu_t *gpu = context->get_device()->get_gpgpu(); - if(g_debug_execution >= 3) - printf("GPGPU-Sim PTX: cudaMemcpy(): devPtr = %p\n", dst); - if( kind == cudaMemcpyHostToDevice ) - g_stream_manager->push( stream_operation(src,(size_t)dst,count,0) ); - else if( kind == cudaMemcpyDeviceToHost ) - g_stream_manager->push( stream_operation((size_t)src,dst,count,0) ); - else if( kind == cudaMemcpyDeviceToDevice ) - g_stream_manager->push( stream_operation((size_t)src,(size_t)dst,count,0) ); - else if ( kind == cudaMemcpyDefault ) { - if ((size_t)src >= GLOBAL_HEAP_START) { - if ((size_t)dst >= GLOBAL_HEAP_START) - g_stream_manager->push( stream_operation((size_t)src,(size_t)dst,count,0) ); // device to device - else - g_stream_manager->push( stream_operation((size_t)src,dst,count,0) ); // device to host - } - else { - if ((size_t)dst >= GLOBAL_HEAP_START) - g_stream_manager->push( stream_operation(src,(size_t)dst,count,0) ); - else { - printf("GPGPU-Sim PTX: cudaMemcpy - ERROR : unsupported transfer: host to host\n"); - abort(); - } - } - } - else { - printf("GPGPU-Sim PTX: cudaMemcpy - ERROR : unsupported cudaMemcpyKind\n"); - abort(); - } - return g_last_cudaError = cudaSuccess; +__host__ cudaError_t CUDARTAPI cudaMemcpy(void *dst, const void *src, + size_t count, + enum cudaMemcpyKind kind) { + return cudaMemcpyInternal(dst, src, count, kind); } -__host__ cudaError_t CUDARTAPI cudaMemcpyToArray(struct cudaArray *dst, size_t wOffset, size_t hOffset, const void *src, size_t count, enum cudaMemcpyKind kind) -{ - CUctx_st *context = GPGPUSim_Context(); - gpgpu_t *gpu = context->get_device()->get_gpgpu(); - size_t size = count; - printf("GPGPU-Sim PTX: cudaMemcpyToArray\n"); - if( kind == cudaMemcpyHostToDevice ) - gpu->memcpy_to_gpu( (size_t)(dst->devPtr), src, size); - else if( kind == cudaMemcpyDeviceToHost ) - gpu->memcpy_from_gpu( dst->devPtr, (size_t)src, size); - else if( kind == cudaMemcpyDeviceToDevice ) - gpu->memcpy_gpu_to_gpu( (size_t)(dst->devPtr), (size_t)src, size); - else { - printf("GPGPU-Sim PTX: cudaMemcpyToArray - ERROR : unsupported cudaMemcpyKind\n"); - abort(); - } - dst->devPtr32 = (unsigned) (size_t)(dst->devPtr); - return g_last_cudaError = cudaSuccess; +__host__ cudaError_t CUDARTAPI cudaMemcpyToArray(struct cudaArray *dst, + size_t wOffset, size_t hOffset, + const void *src, size_t count, + enum cudaMemcpyKind kind) { + return cudaMemcpyToArrayInternal(dst, wOffset, hOffset, src, count, kind); } +__host__ cudaError_t CUDARTAPI cudaMemcpyFromArray(void *dst, + const struct cudaArray *src, + size_t wOffset, + size_t hOffset, size_t count, + enum cudaMemcpyKind kind) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + cuda_not_implemented(__my_func__, __LINE__); + return g_last_cudaError = cudaErrorUnknown; +} -__host__ cudaError_t CUDARTAPI cudaMemcpyFromArray(void *dst, const struct cudaArray *src, size_t wOffset, size_t hOffset, size_t count, enum cudaMemcpyKind kind) -{ - cuda_not_implemented(__my_func__,__LINE__); - return g_last_cudaError = cudaErrorUnknown; +__host__ cudaError_t CUDARTAPI cudaMemcpyArrayToArray( + struct cudaArray *dst, size_t wOffsetDst, size_t hOffsetDst, + const struct cudaArray *src, size_t wOffsetSrc, size_t hOffsetSrc, + size_t count, enum cudaMemcpyKind kind __dv(cudaMemcpyDeviceToDevice)) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + cuda_not_implemented(__my_func__, __LINE__); + return g_last_cudaError = cudaErrorUnknown; } +__host__ cudaError_t CUDARTAPI cudaMemcpy2D(void *dst, size_t dpitch, + const void *src, size_t spitch, + size_t width, size_t height, + enum cudaMemcpyKind kind) { + return cudaMemcpy2DInternal(dst, dpitch, src, spitch, width, height, kind); +} -__host__ cudaError_t CUDARTAPI cudaMemcpyArrayToArray(struct cudaArray *dst, size_t wOffsetDst, size_t hOffsetDst, const struct cudaArray *src, size_t wOffsetSrc, size_t hOffsetSrc, size_t count, enum cudaMemcpyKind kind __dv(cudaMemcpyDeviceToDevice)) -{ - cuda_not_implemented(__my_func__,__LINE__); - return g_last_cudaError = cudaErrorUnknown; +__host__ cudaError_t CUDARTAPI cudaMemcpy2DToArray( + struct cudaArray *dst, size_t wOffset, size_t hOffset, const void *src, + size_t spitch, size_t width, size_t height, enum cudaMemcpyKind kind) { + return cudaMemcpy2DToArrayInternal(dst, wOffset, hOffset, src, spitch, width, + height, kind); } +__host__ cudaError_t CUDARTAPI cudaMemcpy2DFromArray( + void *dst, size_t dpitch, const struct cudaArray *src, size_t wOffset, + size_t hOffset, size_t width, size_t height, enum cudaMemcpyKind kind) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + cuda_not_implemented(__my_func__, __LINE__); + return g_last_cudaError = cudaErrorUnknown; +} -__host__ cudaError_t CUDARTAPI cudaMemcpy2D(void *dst, size_t dpitch, const void *src, size_t spitch, size_t width, size_t height, enum cudaMemcpyKind kind) -{ - CUctx_st *context = GPGPUSim_Context(); - gpgpu_t *gpu = context->get_device()->get_gpgpu(); - size_t size = spitch*height; - gpgpusim_ptx_assert( (dpitch==spitch), "different src and dst pitch not supported yet" ); - if( kind == cudaMemcpyHostToDevice ) - gpu->memcpy_to_gpu( (size_t)dst, src, size ); - else if( kind == cudaMemcpyDeviceToHost ) - gpu->memcpy_from_gpu( dst, (size_t)src, size ); - else if( kind == cudaMemcpyDeviceToDevice ) - gpu->memcpy_gpu_to_gpu( (size_t)dst, (size_t)src, size); - else { - printf("GPGPU-Sim PTX: cudaMemcpy2D - ERROR : unsupported cudaMemcpyKind\n"); - abort(); - } - return g_last_cudaError = cudaSuccess; +__host__ cudaError_t CUDARTAPI cudaMemcpy2DArrayToArray( + struct cudaArray *dst, size_t wOffsetDst, size_t hOffsetDst, + const struct cudaArray *src, size_t wOffsetSrc, size_t hOffsetSrc, + size_t width, size_t height, + enum cudaMemcpyKind kind __dv(cudaMemcpyDeviceToDevice)) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + cuda_not_implemented(__my_func__, __LINE__); + return g_last_cudaError = cudaErrorUnknown; } +__host__ cudaError_t CUDARTAPI cudaMemcpyToSymbol( + const char *symbol, const void *src, size_t count, size_t offset __dv(0), + enum cudaMemcpyKind kind __dv(cudaMemcpyHostToDevice)) { + return cudaMemcpyToSymbolInternal(symbol, src, count, offset, kind); +} -__host__ cudaError_t CUDARTAPI cudaMemcpy2DToArray(struct cudaArray *dst, size_t wOffset, size_t hOffset, const void *src, size_t spitch, size_t width, size_t height, enum cudaMemcpyKind kind) -{ - CUctx_st *context = GPGPUSim_Context(); - gpgpu_t *gpu = context->get_device()->get_gpgpu(); - size_t size = spitch*height; - size_t channel_size = dst->desc.w+dst->desc.x+dst->desc.y+dst->desc.z; - gpgpusim_ptx_assert( ((channel_size%8) == 0), "none byte multiple destination channel size not supported (sz=%u)", channel_size ); - unsigned elem_size = channel_size/8; - gpgpusim_ptx_assert( (dst->dimensions==2), "copy to none 2D array not supported" ); - gpgpusim_ptx_assert( (wOffset==0), "non-zero wOffset not yet supported" ); - gpgpusim_ptx_assert( (hOffset==0), "non-zero hOffset not yet supported" ); - gpgpusim_ptx_assert( (dst->height == (int)height), "partial copy not supported" ); - gpgpusim_ptx_assert( (elem_size*dst->width == width), "partial copy not supported" ); - gpgpusim_ptx_assert( (spitch == width), "spitch != width not supported" ); - if( kind == cudaMemcpyHostToDevice ) - gpu->memcpy_to_gpu( (size_t)(dst->devPtr), src, size); - else if( kind == cudaMemcpyDeviceToHost ) - gpu->memcpy_from_gpu( dst->devPtr, (size_t)src, size); - else if( kind == cudaMemcpyDeviceToDevice ) - gpu->memcpy_gpu_to_gpu( (size_t)dst->devPtr, (size_t)src, size); - else { - printf("GPGPU-Sim PTX: cudaMemcpy2D - ERROR : unsupported cudaMemcpyKind\n"); - abort(); - } - dst->devPtr32 = (unsigned) (size_t)(dst->devPtr); - return g_last_cudaError = cudaSuccess; +__host__ cudaError_t CUDARTAPI cudaMemcpyFromSymbol( + void *dst, const char *symbol, size_t count, size_t offset __dv(0), + enum cudaMemcpyKind kind __dv(cudaMemcpyDeviceToHost)) { + return cudaMemcpyFromSymbolInternal(dst, symbol, count, offset, kind); } +__host__ cudaError_t CUDARTAPI cudaMemGetInfo(size_t *free, size_t *total) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + // placeholder; should interact with cudaMalloc and cudaFree? + *free = 10000000000; + *total = 10000000000; -__host__ cudaError_t CUDARTAPI cudaMemcpy2DFromArray(void *dst, size_t dpitch, const struct cudaArray *src, size_t wOffset, size_t hOffset, size_t width, size_t height, enum cudaMemcpyKind kind) -{ - cuda_not_implemented(__my_func__,__LINE__); - return g_last_cudaError = cudaErrorUnknown; + return g_last_cudaError = cudaSuccess; } +/******************************************************************************* + * * + * * + * * + *******************************************************************************/ + +__host__ cudaError_t CUDARTAPI cudaMemcpyAsync(void *dst, const void *src, + size_t count, + enum cudaMemcpyKind kind, + cudaStream_t stream) { + return cudaMemcpyAsyncInternal(dst, src, count, kind, stream); +} -__host__ cudaError_t CUDARTAPI cudaMemcpy2DArrayToArray(struct cudaArray *dst, size_t wOffsetDst, size_t hOffsetDst, const struct cudaArray *src, size_t wOffsetSrc, size_t hOffsetSrc, size_t width, size_t height, enum cudaMemcpyKind kind __dv(cudaMemcpyDeviceToDevice)) -{ - cuda_not_implemented(__my_func__,__LINE__); - return g_last_cudaError = cudaErrorUnknown; +__host__ cudaError_t CUDARTAPI cudaMemcpyToArrayAsync( + struct cudaArray *dst, size_t wOffset, size_t hOffset, const void *src, + size_t count, enum cudaMemcpyKind kind, cudaStream_t stream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + cuda_not_implemented(__my_func__, __LINE__); + return g_last_cudaError = cudaErrorUnknown; } +__host__ cudaError_t CUDARTAPI cudaMemcpyFromArrayAsync( + void *dst, const struct cudaArray *src, size_t wOffset, size_t hOffset, + size_t count, enum cudaMemcpyKind kind, cudaStream_t stream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + cuda_not_implemented(__my_func__, __LINE__); + return g_last_cudaError = cudaErrorUnknown; +} -__host__ cudaError_t CUDARTAPI cudaMemcpyToSymbol(const char *symbol, const void *src, size_t count, size_t offset __dv(0), enum cudaMemcpyKind kind __dv(cudaMemcpyHostToDevice)) -{ - //CUctx_st *context = GPGPUSim_Context(); - assert(kind == cudaMemcpyHostToDevice); - printf("GPGPU-Sim PTX: cudaMemcpyToSymbol: symbol = %p\n", symbol); - //stream_operation( const char *symbol, const void *src, size_t count, size_t offset ) - g_stream_manager->push( stream_operation(src,symbol,count,offset,0) ); - //gpgpu_ptx_sim_memcpy_symbol(symbol,src,count,offset,1,context->get_device()->get_gpgpu()); - return g_last_cudaError = cudaSuccess; +__host__ cudaError_t CUDARTAPI cudaMemcpy2DAsync(void *dst, size_t dpitch, + const void *src, size_t spitch, + size_t width, size_t height, + enum cudaMemcpyKind kind, + cudaStream_t stream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + cuda_not_implemented(__my_func__, __LINE__); + return g_last_cudaError = cudaErrorUnknown; } +__host__ cudaError_t CUDARTAPI cudaMemcpy2DToArrayAsync( + struct cudaArray *dst, size_t wOffset, size_t hOffset, const void *src, + size_t spitch, size_t width, size_t height, enum cudaMemcpyKind kind, + cudaStream_t stream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + cuda_not_implemented(__my_func__, __LINE__); + return g_last_cudaError = cudaErrorUnknown; +} -__host__ cudaError_t CUDARTAPI cudaMemcpyFromSymbol(void *dst, const char *symbol, size_t count, size_t offset __dv(0), enum cudaMemcpyKind kind __dv(cudaMemcpyDeviceToHost)) -{ - //CUctx_st *context = GPGPUSim_Context(); - assert(kind == cudaMemcpyDeviceToHost); - printf("GPGPU-Sim PTX: cudaMemcpyFromSymbol: symbol = %p\n", symbol); - g_stream_manager->push( stream_operation(symbol,dst,count,offset,0) ); - //gpgpu_ptx_sim_memcpy_symbol(symbol,dst,count,offset,0,context->get_device()->get_gpgpu()); - return g_last_cudaError = cudaSuccess; +__host__ cudaError_t CUDARTAPI cudaMemcpy2DFromArrayAsync( + void *dst, size_t dpitch, const struct cudaArray *src, size_t wOffset, + size_t hOffset, size_t width, size_t height, enum cudaMemcpyKind kind, + cudaStream_t stream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + cuda_not_implemented(__my_func__, __LINE__); + return g_last_cudaError = cudaErrorUnknown; } +#if (CUDART_VERSION >= 8000) +cudaError_t CUDARTAPI cudaOccupancyMaxActiveBlocksPerMultiprocessorWithFlags( + int *numBlocks, const char *hostFunc, int blockSize, size_t dynamicSMemSize, + unsigned int flags) { + return cudaOccupancyMaxActiveBlocksPerMultiprocessorWithFlagsInternal( + numBlocks, hostFunc, blockSize, dynamicSMemSize, flags); +} +#endif /******************************************************************************* * * * * * * *******************************************************************************/ +__host__ cudaError_t CUDARTAPI cudaMemset(void *mem, int c, size_t count) { + return cudaMemsetInternal(mem, c, count); +} -__host__ cudaError_t CUDARTAPI cudaMemcpyAsync(void *dst, const void *src, size_t count, enum cudaMemcpyKind kind, cudaStream_t stream) -{ - struct CUstream_st *s = (struct CUstream_st *)stream; - switch( kind ) { - case cudaMemcpyHostToDevice: g_stream_manager->push( stream_operation(src,(size_t)dst,count,s) ); break; - case cudaMemcpyDeviceToHost: g_stream_manager->push( stream_operation((size_t)src,dst,count,s) ); break; - case cudaMemcpyDeviceToDevice: g_stream_manager->push( stream_operation((size_t)src,(size_t)dst,count,s) ); break; - default: - abort(); - } - return g_last_cudaError = cudaSuccess; +// memset operation is done but i think its not async? +__host__ cudaError_t CUDARTAPI cudaMemsetAsync(void *mem, int c, size_t count, + cudaStream_t stream = 0) { + return cudaMemsetAsyncInternal(mem, c, count, stream = 0); } +__host__ cudaError_t CUDARTAPI cudaMemset2D(void *mem, size_t pitch, int c, + size_t width, size_t height) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + cuda_not_implemented(__my_func__, __LINE__); + return g_last_cudaError = cudaErrorUnknown; +} -__host__ cudaError_t CUDARTAPI cudaMemcpyToArrayAsync(struct cudaArray *dst, size_t wOffset, size_t hOffset, const void *src, size_t count, enum cudaMemcpyKind kind, cudaStream_t stream) -{ - cuda_not_implemented(__my_func__,__LINE__); - return g_last_cudaError = cudaErrorUnknown; +/******************************************************************************* + * * + * * + * * + *******************************************************************************/ + +__host__ cudaError_t CUDARTAPI cudaGetSymbolAddress(void **devPtr, + const char *symbol) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + cuda_not_implemented(__my_func__, __LINE__); + return g_last_cudaError = cudaErrorUnknown; } +__host__ cudaError_t CUDARTAPI cudaGetSymbolSize(size_t *size, + const char *symbol) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + cuda_not_implemented(__my_func__, __LINE__); + return g_last_cudaError = cudaErrorUnknown; +} -__host__ cudaError_t CUDARTAPI cudaMemcpyFromArrayAsync(void *dst, const struct cudaArray *src, size_t wOffset, size_t hOffset, size_t count, enum cudaMemcpyKind kind, cudaStream_t stream) -{ - cuda_not_implemented(__my_func__,__LINE__); - return g_last_cudaError = cudaErrorUnknown; +/******************************************************************************* + * * + * * + * * + *******************************************************************************/ +__host__ cudaError_t CUDARTAPI cudaGetDeviceCount(int *count) { + return cudaGetDeviceCountInternal(count); } +__host__ cudaError_t CUDARTAPI +cudaGetDeviceProperties(struct cudaDeviceProp *prop, int device) { + return cudaGetDevicePropertiesInternal(prop, device); +} -__host__ cudaError_t CUDARTAPI cudaMemcpy2DAsync(void *dst, size_t dpitch, const void *src, size_t spitch, size_t width, size_t height, enum cudaMemcpyKind kind, cudaStream_t stream) -{ - cuda_not_implemented(__my_func__,__LINE__); - return g_last_cudaError = cudaErrorUnknown; +#if (CUDART_VERSION > 5000) +__host__ cudaError_t CUDARTAPI cudaDeviceGetAttribute(int *value, + enum cudaDeviceAttr attr, + int device) { + return cudaDeviceGetAttributeInternal(value, attr, device); } +#endif +__host__ cudaError_t CUDARTAPI +cudaChooseDevice(int *device, const struct cudaDeviceProp *prop) { + return cudaChooseDeviceInternal(device, prop); +} -__host__ cudaError_t CUDARTAPI cudaMemcpy2DToArrayAsync(struct cudaArray *dst, size_t wOffset, size_t hOffset, const void *src, size_t spitch, size_t width, size_t height, enum cudaMemcpyKind kind, cudaStream_t stream) -{ - cuda_not_implemented(__my_func__,__LINE__); - return g_last_cudaError = cudaErrorUnknown; +__host__ cudaError_t CUDARTAPI cudaSetDevice(int device) { + return cudaSetDeviceInternal(device); } +__host__ cudaError_t CUDARTAPI cudaGetDevice(int *device) { + return cudaGetDeviceInternal(device); +} -__host__ cudaError_t CUDARTAPI cudaMemcpy2DFromArrayAsync(void *dst, size_t dpitch, const struct cudaArray *src, size_t wOffset, size_t hOffset, size_t width, size_t height, enum cudaMemcpyKind kind, cudaStream_t stream) -{ - cuda_not_implemented(__my_func__,__LINE__); - return g_last_cudaError = cudaErrorUnknown; +__host__ cudaError_t CUDARTAPI cudaDeviceGetLimit(size_t *pValue, + cudaLimit limit) { + return cudaDeviceGetLimitInternal(pValue, limit); } +__host__ cudaError_t CUDARTAPI cudaStreamGetPriority(cudaStream_t hStream, + int *priority) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + cuda_not_implemented(__my_func__, __LINE__); + return g_last_cudaError = cudaSuccess; +} +__host__ cudaError_t CUDARTAPI cudaDeviceGetPCIBusId(char *pciBusId, int len, + int device) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + cuda_not_implemented(__my_func__, __LINE__); + return g_last_cudaError = cudaErrorUnknown; +} + +__host__ cudaError_t CUDARTAPI cudaIpcGetMemHandle(cudaIpcMemHandle_t *handle, + void *devPtr) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + cuda_not_implemented(__my_func__, __LINE__); + return g_last_cudaError = cudaErrorUnknown; +} + +__host__ cudaError_t cudaIpcOpenMemHandle(void **devPtr, + cudaIpcMemHandle_t handle, + unsigned int flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + cuda_not_implemented(__my_func__, __LINE__); + return g_last_cudaError = cudaErrorUnknown; +} + +__host__ cudaError_t CUDARTAPI +cudaDestroyTextureObject(cudaTextureObject_t texObject) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + cuda_not_implemented(__my_func__, __LINE__); + return g_last_cudaError = cudaErrorUnknown; +} /******************************************************************************* * * @@ -756,90 +2663,168 @@ __host__ cudaError_t CUDARTAPI cudaMemcpy2DFromArrayAsync(void *dst, size_t dpit * * *******************************************************************************/ -__host__ cudaError_t CUDARTAPI cudaMemset(void *mem, int c, size_t count) -{ - CUctx_st *context = GPGPUSim_Context(); - gpgpu_t *gpu = context->get_device()->get_gpgpu(); - gpu->gpu_memset((size_t)mem, c, count); - return g_last_cudaError = cudaSuccess; +__host__ cudaError_t CUDARTAPI cudaBindTexture( + size_t *offset, const struct textureReference *texref, const void *devPtr, + const struct cudaChannelFormatDesc *desc, size_t size __dv(UINT_MAX)) { + return cudaBindTextureInternal(offset, texref, devPtr, desc, + size __dv(UINT_MAX)); } -__host__ cudaError_t CUDARTAPI cudaMemset2D(void *mem, size_t pitch, int c, size_t width, size_t height) -{ - cuda_not_implemented(__my_func__,__LINE__); - return g_last_cudaError = cudaErrorUnknown; +__host__ cudaError_t CUDARTAPI cudaBindTextureToArray( + const struct textureReference *texref, const struct cudaArray *array, + const struct cudaChannelFormatDesc *desc) { + return cudaBindTextureToArrayInternal(texref, array, desc); } +__host__ cudaError_t CUDARTAPI +cudaUnbindTexture(const struct textureReference *texref) { + return cudaUnbindTextureInternal(texref); +} +__host__ cudaError_t CUDARTAPI cudaGetTextureAlignmentOffset( + size_t *offset, const struct textureReference *texref) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + cuda_not_implemented(__my_func__, __LINE__); + return g_last_cudaError = cudaErrorUnknown; +} -/******************************************************************************* - * * - * * - * * - *******************************************************************************/ +__host__ cudaError_t CUDARTAPI cudaGetTextureReference( + const struct textureReference **texref, const char *symbol) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + cuda_not_implemented(__my_func__, __LINE__); + return g_last_cudaError = cudaErrorUnknown; +} -__host__ cudaError_t CUDARTAPI cudaGetSymbolAddress(void **devPtr, const char *symbol) -{ - cuda_not_implemented(__my_func__,__LINE__); - return g_last_cudaError = cudaErrorUnknown; +__host__ cudaError_t CUDARTAPI cudaGetChannelDesc( + struct cudaChannelFormatDesc *desc, const struct cudaArray *array) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + *desc = array->desc; + return g_last_cudaError = cudaSuccess; } +__host__ struct cudaChannelFormatDesc CUDARTAPI cudaCreateChannelDesc( + int x, int y, int z, int w, enum cudaChannelFormatKind f) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + struct cudaChannelFormatDesc dummy; + dummy.x = x; + dummy.y = y; + dummy.z = z; + dummy.w = w; + dummy.f = f; + return dummy; +} -__host__ cudaError_t CUDARTAPI cudaGetSymbolSize(size_t *size, const char *symbol) -{ - cuda_not_implemented(__my_func__,__LINE__); - return g_last_cudaError = cudaErrorUnknown; +__host__ cudaError_t CUDARTAPI cudaGetLastError(void) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + return g_last_cudaError; } +__host__ const char *cudaGetErrorName(cudaError_t error) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + cuda_not_implemented(__my_func__, __LINE__); + return NULL; +} +__host__ const char *CUDARTAPI cudaGetErrorString(cudaError_t error) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + if (g_last_cudaError == cudaSuccess) return "no error"; + char buf[1024]; + snprintf(buf, 1024, "<<GPGPU-Sim PTX: there was an error (code = %d)>>", + g_last_cudaError); + return strdup(buf); +} + +__host__ cudaError_t CUDARTAPI cudaSetupArgument(const void *arg, size_t size, + size_t offset) { + return cudaSetupArgumentInternal(arg, size, offset); +} + +__host__ cudaError_t CUDARTAPI cudaLaunch(const char *hostFun) { + return cudaLaunchInternal(hostFun); +} + +__host__ cudaError_t CUDARTAPI cudaLaunchKernel(const char *hostFun, + dim3 gridDim, dim3 blockDim, + const void **args, + size_t sharedMem, + cudaStream_t stream) { + return cudaLaunchKernelInternal(hostFun, gridDim, blockDim, args, sharedMem, + stream); +} /******************************************************************************* * * * * * * *******************************************************************************/ -__host__ cudaError_t CUDARTAPI cudaGetDeviceCount(int *count) -{ - _cuda_device_id *dev = GPGPUSim_Init(); - *count = dev->num_devices(); - return g_last_cudaError = cudaSuccess; + +__host__ cudaError_t CUDARTAPI cudaStreamCreate(cudaStream_t *stream) { + return cudaStreamCreateInternal(stream); } -__host__ cudaError_t CUDARTAPI cudaGetDeviceProperties(struct cudaDeviceProp *prop, int device) -{ - _cuda_device_id *dev = GPGPUSim_Init(); - if (device <= dev->num_devices() ) { - *prop= *dev->get_prop(); - return g_last_cudaError = cudaSuccess; - } else { - return g_last_cudaError = cudaErrorInvalidDevice; - } +// TODO: introduce priorities +__host__ cudaError_t CUDARTAPI cudaStreamCreateWithPriority( + cudaStream_t *stream, unsigned int flags, int priority) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + return cudaStreamCreate(stream); } -__host__ cudaError_t CUDARTAPI cudaChooseDevice(int *device, const struct cudaDeviceProp *prop) -{ - _cuda_device_id *dev = GPGPUSim_Init(); - *device = dev->get_id(); - return g_last_cudaError = cudaSuccess; +__host__ cudaError_t CUDARTAPI +cudaDeviceGetStreamPriorityRange(int *leastPriority, int *greatestPriority) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + return cudaSuccess; } -__host__ cudaError_t CUDARTAPI cudaSetDevice(int device) -{ - //set the active device to run cuda - if ( device <= GPGPUSim_Init()->num_devices() ) { - g_active_device = device; - return g_last_cudaError = cudaSuccess; - } else { - return g_last_cudaError = cudaErrorInvalidDevice; - } +__host__ __device__ cudaError_t CUDARTAPI +cudaStreamCreateWithFlags(cudaStream_t *stream, unsigned int flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + return cudaStreamCreate(stream); } -__host__ cudaError_t CUDARTAPI cudaGetDevice(int *device) -{ - *device = g_active_device; - return g_last_cudaError = cudaSuccess; +__host__ cudaError_t CUDARTAPI cudaStreamDestroy(cudaStream_t stream) { + return cudaStreamDestroyInternal(stream); +} + +__host__ cudaError_t CUDARTAPI cudaStreamSynchronize(cudaStream_t stream) { + return cudaStreamSynchronizeInternal(stream); } +__host__ cudaError_t CUDARTAPI cudaStreamQuery(cudaStream_t stream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } +#if (CUDART_VERSION >= 3000) + if (stream == NULL) return g_last_cudaError = cudaErrorInvalidResourceHandle; + return g_last_cudaError = stream->empty() ? cudaSuccess : cudaErrorNotReady; +#else + printf( + "GPGPU-Sim PTX: WARNING: Asynchronous kernel execution not supported " + "(%s)\n", + __my_func__); + return g_last_cudaError = cudaSuccess; // it is always success because all + // cuda calls are synchronous +#endif +} /******************************************************************************* * * @@ -847,1478 +2832,4181 @@ __host__ cudaError_t CUDARTAPI cudaGetDevice(int *device) * * *******************************************************************************/ -__host__ cudaError_t CUDARTAPI cudaBindTexture(size_t *offset, - const struct textureReference *texref, - const void *devPtr, - const struct cudaChannelFormatDesc *desc, - size_t size __dv(UINT_MAX)) -{ - CUctx_st *context = GPGPUSim_Context(); - gpgpu_t *gpu = context->get_device()->get_gpgpu(); - printf("GPGPU-Sim PTX: in cudaBindTexture: sizeof(struct textureReference) = %zu\n", sizeof(struct textureReference)); - struct cudaArray *array; - array = (struct cudaArray*) malloc(sizeof(struct cudaArray)); - array->desc = *desc; - array->size = size; - array->width = size; - array->height = 1; - array->dimensions = 1; - array->devPtr = (void*)devPtr; - array->devPtr32 = (int)(long long)devPtr; - offset = 0; - printf("GPGPU-Sim PTX: size = %zu\n", size); - printf("GPGPU-Sim PTX: texref = %p, array = %p\n", texref, array); - printf("GPGPU-Sim PTX: devPtr32 = %x\n", array->devPtr32); - printf("GPGPU-Sim PTX: Name corresponding to textureReference: %s\n", gpu->gpgpu_ptx_sim_findNamefromTexture(texref)); - printf("GPGPU-Sim PTX: ChannelFormatDesc: x=%d, y=%d, z=%d, w=%d\n", desc->x, desc->y, desc->z, desc->w); - printf("GPGPU-Sim PTX: Texture Normalized? = %d\n", texref->normalized); - gpu->gpgpu_ptx_sim_bindTextureToArray(texref, array); - devPtr = (void*)(long long)array->devPtr32; - printf("GPGPU-Sim PTX: devPtr = %p\n", devPtr); - return g_last_cudaError = cudaSuccess; +__host__ cudaError_t CUDARTAPI cudaEventCreate(cudaEvent_t *event) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + CUevent_st *e = new CUevent_st(false); + g_timer_events[e->get_uid()] = e; +#if CUDART_VERSION >= 3000 + *event = e; +#else + *event = e->get_uid(); +#endif + return g_last_cudaError = cudaSuccess; } +__host__ cudaError_t CUDARTAPI cudaEventRecord(cudaEvent_t event, + cudaStream_t stream) { + return cudaEventRecordInternal(event, stream); +} -__host__ cudaError_t CUDARTAPI cudaBindTextureToArray(const struct textureReference *texref, const struct cudaArray *array, const struct cudaChannelFormatDesc *desc) -{ - CUctx_st *context = GPGPUSim_Context(); - gpgpu_t *gpu = context->get_device()->get_gpgpu(); - printf("GPGPU-Sim PTX: in cudaBindTextureToArray: %p %p\n", texref, array); - printf("GPGPU-Sim PTX: devPtr32 = %x\n", array->devPtr32); - printf("GPGPU-Sim PTX: Name corresponding to textureReference: %s\n", gpu->gpgpu_ptx_sim_findNamefromTexture(texref)); - printf("GPGPU-Sim PTX: Texture Normalized? = %d\n", texref->normalized); - gpu->gpgpu_ptx_sim_bindTextureToArray(texref, array); - return g_last_cudaError = cudaSuccess; +__host__ cudaError_t CUDARTAPI cudaStreamWaitEvent(cudaStream_t stream, + cudaEvent_t event, + unsigned int flags) { + return cudaStreamWaitEventInternal(stream, event, flags); } -__host__ cudaError_t CUDARTAPI cudaUnbindTexture(const struct textureReference *texref) -{ - return g_last_cudaError = cudaSuccess; +__host__ cudaError_t CUDARTAPI cudaEventQuery(cudaEvent_t event) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + CUevent_st *e = get_event(event); + if (e == NULL) { + return g_last_cudaError = cudaErrorInvalidValue; + } else if (e->done()) { + return g_last_cudaError = cudaSuccess; + } else { + return g_last_cudaError = cudaErrorNotReady; + } } -__host__ cudaError_t CUDARTAPI cudaGetTextureAlignmentOffset(size_t *offset, const struct textureReference *texref) -{ - cuda_not_implemented(__my_func__,__LINE__); - return g_last_cudaError = cudaErrorUnknown; +__host__ cudaError_t CUDARTAPI cudaEventSynchronize(cudaEvent_t event) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("GPGPU-Sim API: cudaEventSynchronize ** waiting for event\n"); + fflush(stdout); + CUevent_st *e = (CUevent_st *)event; + while (!e->done()) + ; + printf("GPGPU-Sim API: cudaEventSynchronize ** event detected\n"); + fflush(stdout); + return g_last_cudaError = cudaSuccess; } -__host__ cudaError_t CUDARTAPI cudaGetTextureReference(const struct textureReference **texref, const char *symbol) -{ - cuda_not_implemented(__my_func__,__LINE__); - return g_last_cudaError = cudaErrorUnknown; +__host__ cudaError_t CUDARTAPI cudaEventDestroy(cudaEvent_t event) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + CUevent_st *e = get_event(event); + unsigned event_uid = e->get_uid(); + event_tracker_t::iterator pe = g_timer_events.find(event_uid); + if (pe == g_timer_events.end()) + return g_last_cudaError = cudaErrorInvalidValue; + g_timer_events.erase(pe); + return g_last_cudaError = cudaSuccess; } -__host__ cudaError_t CUDARTAPI cudaGetChannelDesc(struct cudaChannelFormatDesc *desc, const struct cudaArray *array) -{ - *desc = array->desc; - return g_last_cudaError = cudaSuccess; +__host__ cudaError_t CUDARTAPI cudaEventElapsedTime(float *ms, + cudaEvent_t start, + cudaEvent_t end) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + time_t elapsed_time; + CUevent_st *s = get_event(start); + CUevent_st *e = get_event(end); + if (s == NULL || e == NULL) return g_last_cudaError = cudaErrorUnknown; + elapsed_time = e->clock() - s->clock(); + *ms = 1000 * elapsed_time; + return g_last_cudaError = cudaSuccess; } +/******************************************************************************* + * * + * * + * * + *******************************************************************************/ -__host__ struct cudaChannelFormatDesc CUDARTAPI cudaCreateChannelDesc(int x, int y, int z, int w, enum cudaChannelFormatKind f) -{ - struct cudaChannelFormatDesc dummy; - dummy.x = x; - dummy.y = y; - dummy.z = z; - dummy.w = w; - dummy.f = f; - return dummy; +__host__ cudaError_t CUDARTAPI cudaThreadExit(void) { + return cudaThreadExitInternal(); } -__host__ cudaError_t CUDARTAPI cudaGetLastError(void) -{ - return g_last_cudaError; +__host__ cudaError_t CUDARTAPI cudaThreadSynchronize(void) { + return cudaThreadSynchronizeInternal(); } -__host__ const char* CUDARTAPI cudaGetErrorString(cudaError_t error) -{ - if( g_last_cudaError == cudaSuccess ) - return "no error"; - char buf[1024]; - snprintf(buf,1024,"<<GPGPU-Sim PTX: there was an error (code = %d)>>", g_last_cudaError); - return strdup(buf); +int CUDARTAPI __cudaSynchronizeThreads(void **, void *) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + return cudaThreadExit(); } -__host__ cudaError_t CUDARTAPI cudaConfigureCall(dim3 gridDim, dim3 blockDim, size_t sharedMem, cudaStream_t stream) -{ - struct CUstream_st *s = (struct CUstream_st *)stream; - g_cuda_launch_stack.push_back( kernel_config(gridDim,blockDim,sharedMem,s) ); - return g_last_cudaError = cudaSuccess; -} +/******************************************************************************* + * * + * * + * * + *******************************************************************************/ -__host__ cudaError_t CUDARTAPI cudaSetupArgument(const void *arg, size_t size, size_t offset) -{ - gpgpusim_ptx_assert( !g_cuda_launch_stack.empty(), "empty launch stack" ); - kernel_config &config = g_cuda_launch_stack.back(); - config.set_arg(arg,size,offset); +#if (CUDART_VERSION >= 3010) +int dummy0() { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + return 0; +} - return g_last_cudaError = cudaSuccess; +int dummy1() { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + return 2 << 20; } +typedef int (*ExportedFunction)(); -__host__ cudaError_t CUDARTAPI cudaLaunch( const char *hostFun ) -{ - CUctx_st* context = GPGPUSim_Context(); - char *mode = getenv("PTX_SIM_MODE_FUNC"); - if( mode ) - sscanf(mode,"%u", &g_ptx_sim_mode); - gpgpusim_ptx_assert( !g_cuda_launch_stack.empty(), "empty launch stack" ); - kernel_config config = g_cuda_launch_stack.back(); - struct CUstream_st *stream = config.get_stream(); - printf("\nGPGPU-Sim PTX: cudaLaunch for 0x%p (mode=%s) on stream %u\n", hostFun, - g_ptx_sim_mode?"functional simulation":"performance simulation", stream?stream->get_uid():0 ); - kernel_info_t *grid = gpgpu_cuda_ptx_sim_init_grid(hostFun,config.get_args(),config.grid_dim(),config.block_dim(),context); - std::string kname = grid->name(); - dim3 gridDim = config.grid_dim(); - dim3 blockDim = config.block_dim(); - printf("GPGPU-Sim PTX: pushing kernel \'%s\' to stream %u, gridDim= (%u,%u,%u) blockDim = (%u,%u,%u) \n", - kname.c_str(), stream?stream->get_uid():0, gridDim.x,gridDim.y,gridDim.z,blockDim.x,blockDim.y,blockDim.z ); - stream_operation op(grid,g_ptx_sim_mode,stream); - g_stream_manager->push(op); - g_cuda_launch_stack.pop_back(); - return g_last_cudaError = cudaSuccess; +static ExportedFunction exportTable[3] = {&dummy0, &dummy0, &dummy0}; + +__host__ cudaError_t CUDARTAPI cudaGetExportTable( + const void **ppExportTable, const cudaUUID_t *pExportTableId) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("cudaGetExportTable: UUID = "); + for (int s = 0; s < 16; s++) { + printf("%#2x ", (unsigned char)(pExportTableId->bytes[s])); + } + *ppExportTable = &exportTable; + + printf("\n"); + return g_last_cudaError = cudaSuccess; } +#endif + /******************************************************************************* * * * * * * *******************************************************************************/ -__host__ cudaError_t CUDARTAPI cudaStreamCreate(cudaStream_t *stream) -{ - printf("GPGPU-Sim PTX: cudaStreamCreate\n"); -#if (CUDART_VERSION >= 3000) - *stream = new struct CUstream_st(); - g_stream_manager->add_stream(*stream); -#else - *stream = 0; - printf("GPGPU-Sim PTX: WARNING: Asynchronous kernel execution not supported (%s)\n", __my_func__); +//#include "../../cuobjdump_to_ptxplus/cuobjdump_parser.h" + +// extracts all ptx files from binary and dumps into +// prog_name.unique_no.sm_<>.ptx files +void cuda_runtime_api::extract_ptx_files_using_cuobjdump(CUctx_st *context) { + char command[1000]; + char *pytorch_bin = getenv("PYTORCH_BIN"); + std::string app_binary = get_app_binary(); + + char ptx_list_file_name[1024]; + snprintf(ptx_list_file_name, 1024, "_cuobjdump_list_ptx_XXXXXX"); + int fd2 = mkstemp(ptx_list_file_name); + close(fd2); + + if (pytorch_bin != NULL && strlen(pytorch_bin) != 0) { + app_binary = std::string(pytorch_bin); + } + + // only want file names + snprintf(command, 1000, + "$CUDA_INSTALL_PATH/bin/cuobjdump -lptx %s | cut -d \":\" -f 2 | " + "awk '{$1=$1}1' > %s", + app_binary.c_str(), ptx_list_file_name); + if (system(command) != 0) { + printf("WARNING: Failed to execute cuobjdump to get list of ptx files \n"); + exit(0); + } + if (!gpgpu_ctx->device_runtime->g_cdp_enabled) { + // based on the list above, dump ptx files individually. Format of dumped + // ptx file is prog_name.unique_no.sm_<>.ptx + + std::ifstream infile(ptx_list_file_name); + std::string line; + while (std::getline(infile, line)) { + // int pos = line.find(std::string(get_app_binary_name(app_binary))); + const char *ptx_file = line.c_str(); + printf("Extracting specific PTX file named %s \n", ptx_file); + snprintf(command, 1000, "$CUDA_INSTALL_PATH/bin/cuobjdump -xptx %s %s", + ptx_file, app_binary.c_str()); + if (system(command) != 0) { + printf("ERROR: command: %s failed \n", command); + exit(0); + } + context->no_of_ptx++; + } + } + + if (!context->no_of_ptx) { + printf( + "WARNING: Number of ptx in the executable file are 0. One of the " + "reasons might be\n"); + printf("\t1. CDP is enabled\n"); + printf("\t2. When using PyTorch, PYTORCH_BIN is not set correctly\n"); + } + + std::ifstream infile(ptx_list_file_name); + std::string line; + while (std::getline(infile, line)) { + // int pos = line.find(std::string(get_app_binary_name(app_binary))); + int pos1 = line.find("sm_"); + int pos2 = line.find_last_of("."); + if (pos1 == std::string::npos && pos2 == std::string::npos) { + printf("ERROR: PTX list is not in correct format"); + exit(0); + } + std::string vstr = line.substr(pos1 + 3, pos2 - pos1 - 3); + int version = atoi(vstr.c_str()); + if (version_filename.find(version) == version_filename.end()) { + version_filename[version] = std::set<std::string>(); + } + version_filename[version].insert(line); + } +} + +//! Call cuobjdump to extract everything (-elf -sass -ptx) +/*! + * This Function extract the whole PTX (for all the files) using cuobjdump + * to _cuobjdump_complete_output_XXXXXX then runs a parser to chop it up + *with each binary in its own file It is also responsible for extracting the + *libraries linked to the binary if the option is enabled + * */ +void cuda_runtime_api::extract_code_using_cuobjdump() { + CUctx_st *context = GPGPUSim_Context(gpgpu_ctx); + + // prevent the dumping by cuobjdump everytime we execute the code! + const char *override_cuobjdump = getenv("CUOBJDUMP_SIM_FILE"); + char command[1000]; + std::string app_binary = get_app_binary(); + // Running cuobjdump using dynamic link to current process + snprintf(command, 1000, "md5sum %s ", app_binary.c_str()); + printf("Running md5sum using \"%s\"\n", command); + if (system(command)) { + std::cout << "Failed to execute: " << command << std::endl; + exit(1); + } + // Running cuobjdump using dynamic link to current process + // Needs the option '-all' to extract PTX from CDP-enabled binary + + // dump ptx for all individial ptx files into sepearte files which is later + // used by ptxas. + int result = 0; +#if (CUDART_VERSION >= 6000) + extract_ptx_files_using_cuobjdump(context); + return; #endif - return g_last_cudaError = cudaSuccess; + // TODO: redundant to dump twice. how can it be prevented? + // dump only for specific arch + char fname[1024]; + if ((override_cuobjdump == NULL) || (strlen(override_cuobjdump) == 0)) { + snprintf(fname, 1024, "_cuobjdump_complete_output_XXXXXX"); + int fd = mkstemp(fname); + close(fd); + if (!gpgpu_ctx->device_runtime->g_cdp_enabled) + snprintf(command, 1000, + "$CUDA_INSTALL_PATH/bin/cuobjdump -ptx -elf -sass %s > %s", + app_binary.c_str(), fname); + else + snprintf(command, 1000, + "$CUDA_INSTALL_PATH/bin/cuobjdump -ptx -elf -sass -all %s > %s", + app_binary.c_str(), fname); + bool parse_output = true; + result = system(command); + if (result) { + if (context->get_device() + ->get_gpgpu() + ->get_config() + .experimental_lib_support() && + (result == 65280)) { + // Some CUDA application may exclusively use kernels provided by CUDA + // libraries (e.g. CUBLAS). Skipping cuobjdump extraction from the + // executable for this case. + // 65280 is the return code from cuobjdump denoting the specific error + // (tested on CUDA 4.0/4.1/4.2) + printf("WARNING: Failed to execute: %s\n", command); + printf(" Executable binary does not contain any GPU kernel.\n"); + parse_output = false; + } else { + printf("ERROR: Failed to execute: %s\n", command); + exit(1); + } + } + + if (parse_output) { + printf("Parsing file %s\n", fname); + FILE *cuobjdump_in; + cuobjdump_in = fopen(fname, "r"); + + struct cuobjdump_parser parser; + parser.elfserial = 1; + parser.ptxserial = 1; + cuobjdump_lex_init(&(parser.scanner)); + cuobjdump_set_in(cuobjdump_in, (parser.scanner)); + cuobjdump_parse(parser.scanner, &parser, cuobjdumpSectionList); + cuobjdump_lex_destroy(parser.scanner); + fclose(cuobjdump_in); + printf("Done parsing!!!\n"); + } else { + printf("Parsing skipped for %s\n", fname); + } + + if (context->get_device() + ->get_gpgpu() + ->get_config() + .experimental_lib_support()) { + // Experimental library support + // Currently only for cufft + + std::stringstream cmd; + cmd << "ldd " << app_binary + << " | grep $CUDA_INSTALL_PATH | awk \'{print $3}\' > _tempfile_.txt"; + int result = system(cmd.str().c_str()); + if (result) { + std::cout << "Failed to execute: " << cmd.str() << std::endl; + exit(1); + } + std::ifstream libsf; + libsf.open("_tempfile_.txt"); + if (!libsf.is_open()) { + std::cout << "Failed to open: _tempfile_.txt" << std::endl; + exit(1); + } + + // Save the original section list + std::list<cuobjdumpSection *> tmpsl = cuobjdumpSectionList; + cuobjdumpSectionList.clear(); + + std::string line; + std::getline(libsf, line); + std::cout << "DOING: " << line << std::endl; + int cnt = 1; + while (libsf.good()) { + std::stringstream libcodfn; + libcodfn << "_cuobjdump_complete_lib_" << cnt << "_"; + cmd.str(""); // resetting + cmd << "$CUDA_INSTALL_PATH/bin/cuobjdump -ptx -elf -sass "; + cmd << line; + cmd << " > "; + cmd << libcodfn.str(); + std::cout << "Running cuobjdump on " << line << std::endl; + std::cout << "Using command: " << cmd.str() << std::endl; + result = system(cmd.str().c_str()); + if (result) { + printf("ERROR: Failed to execute: %s\n", command); + exit(1); + } + std::cout << "Done" << std::endl; + + std::cout << "Trying to parse " << libcodfn.str() << std::endl; + FILE *cuobjdump_in; + cuobjdump_in = fopen(libcodfn.str().c_str(), "r"); + struct cuobjdump_parser parser; + parser.elfserial = 1; + parser.ptxserial = 1; + cuobjdump_lex_init(&(parser.scanner)); + cuobjdump_set_in(cuobjdump_in, (parser.scanner)); + cuobjdump_parse(parser.scanner, &parser, cuobjdumpSectionList); + cuobjdump_lex_destroy(parser.scanner); + fclose(cuobjdump_in); + std::getline(libsf, line); + } + libSectionList = cuobjdumpSectionList; + + // Restore the original section list + cuobjdumpSectionList = tmpsl; + } + } else { + printf( + "GPGPU-Sim PTX: overriding cuobjdump with '%s' (CUOBJDUMP_SIM_FILE is " + "set)\n", + override_cuobjdump); + snprintf(fname, 1024, "%s", override_cuobjdump); + } } -__host__ __device__ cudaError_t CUDARTAPI cudaStreamCreateWithFlags(cudaStream_t *stream, unsigned int flags) { - return cudaStreamCreate(stream); +//! Read file into char* +// TODO: convert this to C++ streams, will be way cleaner +char *readfile(const std::string filename) { + assert(filename != ""); + FILE *fp = fopen(filename.c_str(), "r"); + if (!fp) { + std::cout << "ERROR: Could not open file %s for reading\n" + << filename << std::endl; + assert(0); + } + // finding size of the file + int filesize = 0; + fseek(fp, 0, SEEK_END); + + filesize = ftell(fp); + fseek(fp, 0, SEEK_SET); + // allocate and copy the entire ptx + char *ret = (char *)malloc((filesize + 1) * sizeof(char)); + fread(ret, 1, filesize, fp); + ret[filesize] = '\0'; + fclose(fp); + return ret; } -__host__ cudaError_t CUDARTAPI cudaStreamDestroy(cudaStream_t stream) -{ -#if (CUDART_VERSION >= 3000) - g_stream_manager->destroy_stream(stream); -#endif - return g_last_cudaError = cudaSuccess; +//! Function that helps debugging +void printSectionList(std::list<cuobjdumpSection *> sl) { + std::list<cuobjdumpSection *>::iterator iter; + for (iter = sl.begin(); iter != sl.end(); iter++) { + (*iter)->print(); + } } -__host__ cudaError_t CUDARTAPI cudaStreamSynchronize(cudaStream_t stream) -{ -#if (CUDART_VERSION >= 3000) - if( stream == NULL ) - synchronize(); - return g_last_cudaError = cudaSuccess; - stream->synchronize(); -#else - printf("GPGPU-Sim PTX: WARNING: Asynchronous kernel execution not supported (%s)\n", __my_func__); -#endif - return g_last_cudaError = cudaSuccess; +//! Remove unecessary sm versions from the section list +std::list<cuobjdumpSection *> cuda_runtime_api::pruneSectionList( + CUctx_st *context) { + unsigned forced_max_capability = context->get_device() + ->get_gpgpu() + ->get_config() + .get_forced_max_capability(); + + // For ptxplus, force the max capability to 19 if it's higher or + // unspecified(0) + if (context->get_device()->get_gpgpu()->get_config().convert_to_ptxplus()) { + if ((forced_max_capability == 0) || (forced_max_capability >= 20)) { + printf( + "GPGPU-Sim: WARNING: Capability >= 20 are not supported in " + "PTXPlus\n\tSetting forced_max_capability to 19\n"); + forced_max_capability = 19; + } + } + + std::list<cuobjdumpSection *> prunedList; + + // Find the highest capability (that is lower than the forced maximum) for + // each cubin file and set it in cuobjdumpSectionMap. Do this only for ptx + // sections + std::map<std::string, unsigned> cuobjdumpSectionMap; + int min_ptx_capability_found = 0; + for (std::list<cuobjdumpSection *>::iterator iter = + cuobjdumpSectionList.begin(); + iter != cuobjdumpSectionList.end(); iter++) { + unsigned capability = (*iter)->getArch(); + if (dynamic_cast<cuobjdumpPTXSection *>(*iter) != NULL) { + if (capability < min_ptx_capability_found || + min_ptx_capability_found == 0) + min_ptx_capability_found = capability; + if (capability <= forced_max_capability || forced_max_capability == 0) { + if ((cuobjdumpSectionMap.find((*iter)->getIdentifier()) == + cuobjdumpSectionMap.end()) || + (cuobjdumpSectionMap[(*iter)->getIdentifier()] < capability)) + cuobjdumpSectionMap[(*iter)->getIdentifier()] = capability; + } + } + } + + // Throw away the sections with the lower capabilites and push those with the + // highest in the pruned list + for (std::list<cuobjdumpSection *>::iterator iter = + cuobjdumpSectionList.begin(); + iter != cuobjdumpSectionList.end(); iter++) { + unsigned capability = (*iter)->getArch(); + if (capability == cuobjdumpSectionMap[(*iter)->getIdentifier()]) { + prunedList.push_back(*iter); + } else { + delete *iter; + } + } + if (prunedList.empty()) { + printf( + "Error: No PTX sections found with sm capability that is lower than " + "current forced maximum capability \n minimum ptx capability found = " + "%u, maximum forced ptx capability = %u \n User might want to change " + "either the forced maximum capability from gpgpusim configuration or " + "update the compilation to generate the required PTX version\n", + min_ptx_capability_found, forced_max_capability); + abort(); + } + return prunedList; } -__host__ cudaError_t CUDARTAPI cudaStreamQuery(cudaStream_t stream) -{ -#if (CUDART_VERSION >= 3000) - if( stream == NULL ) - return g_last_cudaError = cudaErrorInvalidResourceHandle; - return g_last_cudaError = stream->empty()?cudaSuccess:cudaErrorNotReady; -#else - printf("GPGPU-Sim PTX: WARNING: Asynchronous kernel execution not supported (%s)\n", __my_func__); - return g_last_cudaError = cudaSuccess; // it is always success because all cuda calls are synchronous +//! Merge all PTX sections that have a specific identifier into one file +std::list<cuobjdumpSection *> cuda_runtime_api::mergeMatchingSections( + std::string identifier) { + const char *ptxcode = ""; + std::list<cuobjdumpSection *>::iterator old_iter; + cuobjdumpPTXSection *old_ptxsection = NULL; + cuobjdumpPTXSection *ptxsection; + std::list<cuobjdumpSection *> mergedList; + + for (std::list<cuobjdumpSection *>::iterator iter = + cuobjdumpSectionList.begin(); + iter != cuobjdumpSectionList.end(); iter++) { + if ((ptxsection = dynamic_cast<cuobjdumpPTXSection *>(*iter)) != NULL && + strcmp(ptxsection->getIdentifier().c_str(), identifier.c_str()) == 0) { + // Read and remove the last PTX section + if (old_ptxsection != NULL) { + ptxcode = readfile(old_ptxsection->getPTXfilename()); + // remove ptx file? + delete *old_iter; + } + + // Append all the PTX from the last PTX section into the current PTX + // section Add 50 to ptxcode to ignore the information regarding + // version/target/address_size + if (strlen(ptxcode) >= 50) { + FILE *ptxfile = fopen((ptxsection->getPTXfilename()).c_str(), "a"); + fprintf(ptxfile, "%s", ptxcode + 50); + fclose(ptxfile); + } + + old_iter = iter; + old_ptxsection = ptxsection; + } + // Store all non-PTX sections and PTX sections with non-matching identifiers + else { + mergedList.push_back(*iter); + } + } + + // Store the final PTX section + mergedList.push_back(*old_iter); + + return mergedList; +} + +//! Merge any PTX sections with matching identifiers +std::list<cuobjdumpSection *> cuda_runtime_api::mergeSections() { + std::vector<std::string> identifier; + cuobjdumpPTXSection *ptxsection; + + // Add all identifiers present in PTX sections to a vector + for (std::list<cuobjdumpSection *>::iterator iter = + cuobjdumpSectionList.begin(); + iter != cuobjdumpSectionList.end(); iter++) { + if ((ptxsection = dynamic_cast<cuobjdumpPTXSection *>(*iter)) != NULL) { + std::string current_id = ptxsection->getIdentifier(); + + // If we haven't yet seen a given identifier, add it to the vector + if (std::find(identifier.begin(), identifier.end(), current_id) == + identifier.end()) { + identifier.push_back(current_id); + } + } + } + + // Call mergeMatchingSections on all identifiers in the vector + for (std::vector<std::string>::iterator iter = identifier.begin(); + iter != identifier.end(); iter++) { + cuobjdumpSectionList = mergeMatchingSections(*iter); + } + + return cuobjdumpSectionList; +} + +//! Within the section list, find the ELF section corresponding to a given +//! identifier +cuobjdumpELFSection *findELFSectionInList( + std::list<cuobjdumpSection *> sectionlist, const std::string identifier) { + std::list<cuobjdumpSection *>::iterator iter; + for (iter = sectionlist.begin(); iter != sectionlist.end(); iter++) { + cuobjdumpELFSection *elfsection; + if ((elfsection = dynamic_cast<cuobjdumpELFSection *>(*iter)) != NULL) { + if (elfsection->getIdentifier() == identifier) return elfsection; + } + } + return NULL; +} + +//! Find an ELF section in all the known lists +cuobjdumpELFSection *cuda_runtime_api::findELFSection( + const std::string identifier) { + cuobjdumpELFSection *sec = + findELFSectionInList(cuobjdumpSectionList, identifier); + if (sec != NULL) return sec; + sec = findELFSectionInList(libSectionList, identifier); + if (sec != NULL) return sec; + std::cout << "Could not find " << identifier << std::endl; + assert(0 && "Could not find the required ELF section"); + return NULL; +} + +//! Within the section list, find the PTX section corresponding to a given +//! identifier +cuobjdumpPTXSection *cuda_runtime_api::findPTXSectionInList( + std::list<cuobjdumpSection *> §ionlist, const std::string identifier) { + std::list<cuobjdumpSection *>::iterator iter; + for (iter = sectionlist.begin(); iter != sectionlist.end(); iter++) { + cuobjdumpPTXSection *ptxsection; + if ((ptxsection = dynamic_cast<cuobjdumpPTXSection *>(*iter)) != NULL) { + if (ptxsection->getIdentifier() == identifier) + return ptxsection; + else { + if (gpgpu_ctx->device_runtime->g_cdp_enabled) { + printf( + "Warning: __cudaRegisterFatBinary needs %s, but find PTX section " + "with %s\n", + identifier.c_str(), ptxsection->getIdentifier().c_str()); + return ptxsection; + } + } + } + } + return NULL; +} + +//! Find an PTX section in all the known lists +cuobjdumpPTXSection *cuda_runtime_api::findPTXSection( + const std::string identifier) { + cuobjdumpPTXSection *sec = + findPTXSectionInList(cuobjdumpSectionList, identifier); + if (sec != NULL) return sec; + sec = findPTXSectionInList(libSectionList, identifier); + if (sec != NULL) return sec; + std::cout << "Could not find " << identifier << std::endl; + assert(0 && "Could not find the required PTX section"); + return NULL; +} + +//! Extract the code using cuobjdump and remove unnecessary sections +void cuda_runtime_api::cuobjdumpInit() { + CUctx_st *context = GPGPUSim_Context(gpgpu_ctx); + extract_code_using_cuobjdump(); // extract all the output of cuobjdump to + // _cuobjdump_*.* + const char *pre_load = getenv("CUOBJDUMP_SIM_FILE"); + if (pre_load == NULL || strlen(pre_load) == 0) { + cuobjdumpSectionList = pruneSectionList(context); + cuobjdumpSectionList = mergeSections(); + } +} + +//! Either submit PTX for simulation or convert SASS to PTXPlus and submit it +void gpgpu_context::cuobjdumpParseBinary(unsigned int handle) { + CUctx_st *context = GPGPUSim_Context(this); + if (api->fatbin_registered[handle]) return; + api->fatbin_registered[handle] = true; + std::string fname = api->fatbinmap[handle]; + + if (api->name_symtab.find(fname) != api->name_symtab.end()) { + symbol_table *symtab = api->name_symtab[fname]; + context->add_binary(symtab, handle); + return; + } + symbol_table *symtab; + +#if (CUDART_VERSION >= 6000) + // loops through all ptx files from smallest sm version to largest + std::map<unsigned, std::set<std::string> >::iterator itr_m; + for (itr_m = api->version_filename.begin(); + itr_m != api->version_filename.end(); itr_m++) { + std::set<std::string>::iterator itr_s; + for (itr_s = itr_m->second.begin(); itr_s != itr_m->second.end(); itr_s++) { + std::string ptx_filename = *itr_s; + printf("GPGPU-Sim PTX: Parsing %s\n", ptx_filename.c_str()); + symtab = gpgpu_ptx_sim_load_ptx_from_filename(ptx_filename.c_str()); + } + } + api->name_symtab[fname] = symtab; + context->add_binary(symtab, handle); + api->load_static_globals(symtab, STATIC_ALLOC_LIMIT, 0xFFFFFFFF, + context->get_device()->get_gpgpu()); + api->load_constants(symtab, STATIC_ALLOC_LIMIT, + context->get_device()->get_gpgpu()); + for (itr_m = api->version_filename.begin(); + itr_m != api->version_filename.end(); itr_m++) { + std::set<std::string>::iterator itr_s; + for (itr_s = itr_m->second.begin(); itr_s != itr_m->second.end(); itr_s++) { + std::string ptx_filename = *itr_s; + printf("GPGPU-Sim PTX: Loading PTXInfo from %s\n", ptx_filename.c_str()); + gpgpu_ptx_info_load_from_filename(ptx_filename.c_str(), itr_m->first); + } + } + return; #endif + + unsigned max_capability = 0; + for (std::list<cuobjdumpSection *>::iterator iter = + api->cuobjdumpSectionList.begin(); + iter != api->cuobjdumpSectionList.end(); iter++) { + unsigned capability = (*iter)->getArch(); + if (capability > max_capability) max_capability = capability; + } + if (max_capability > 20) + printf("WARNING: No guarantee that PTX will be parsed for SM version %u\n", + max_capability); + if (max_capability == 0) + max_capability = context->get_device() + ->get_gpgpu() + ->get_config() + .get_forced_max_capability(); + + cuobjdumpPTXSection *ptx = NULL; + const char *pre_load = getenv("CUOBJDUMP_SIM_FILE"); + if (pre_load == NULL || strlen(pre_load) == 0) + ptx = api->findPTXSection(fname); + char *ptxcode; + const char *override_ptx_name = getenv("PTX_SIM_KERNELFILE"); + if (override_ptx_name == NULL or getenv("PTX_SIM_USE_PTX_FILE") == NULL or + strlen(getenv("PTX_SIM_USE_PTX_FILE")) == 0) { + ptxcode = readfile(ptx->getPTXfilename()); + } else { + printf( + "GPGPU-Sim PTX: overriding embedded ptx with '%s' " + "(PTX_SIM_USE_PTX_FILE is set)\n", + override_ptx_name); + ptxcode = readfile(override_ptx_name); + } + if (context->get_device()->get_gpgpu()->get_config().convert_to_ptxplus()) { + cuobjdumpELFSection *elfsection = api->findELFSection(ptx->getIdentifier()); + assert(elfsection != NULL); + char *ptxplus_str = ptxinfo->gpgpu_ptx_sim_convert_ptx_and_sass_to_ptxplus( + ptx->getPTXfilename(), elfsection->getELFfilename(), + elfsection->getSASSfilename()); + symtab = gpgpu_ptx_sim_load_ptx_from_string(ptxplus_str, handle); + printf("Adding %s with cubin handle %u\n", ptx->getPTXfilename().c_str(), + handle); + context->add_binary(symtab, handle); + gpgpu_ptxinfo_load_from_string(ptxcode, handle, max_capability, + context->no_of_ptx); + delete[] ptxplus_str; + } else { + symtab = gpgpu_ptx_sim_load_ptx_from_string(ptxcode, handle); + // if CUOBJDUMP_SIM_FILE is not set, ptx is NULL. So comment below. + // printf("Adding %s with cubin handle %u\n", ptx->getPTXfilename().c_str(), + // handle); + context->add_binary(symtab, handle); + gpgpu_ptxinfo_load_from_string(ptxcode, handle, max_capability, + context->no_of_ptx); + } + api->load_static_globals(symtab, STATIC_ALLOC_LIMIT, 0xFFFFFFFF, + context->get_device()->get_gpgpu()); + api->load_constants(symtab, STATIC_ALLOC_LIMIT, + context->get_device()->get_gpgpu()); + api->name_symtab[fname] = symtab; + + // TODO: Remove temporarily files as per configurations +} } -/******************************************************************************* - * * - * * - * * - *******************************************************************************/ +extern "C" { + +void **CUDARTAPI __cudaRegisterFatBinary(void *fatCubin) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + return cudaRegisterFatBinaryInternal(fatCubin); +} + +void CUDARTAPI __cudaRegisterFatBinaryEnd(void **fatCubinHandle) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } +} + +unsigned CUDARTAPI __cudaPushCallConfiguration(dim3 gridDim, dim3 blockDim, + size_t sharedMem = 0, + struct CUstream_st *stream = 0) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + cudaConfigureCallInternal(gridDim, blockDim, sharedMem, stream); +} + +cudaError_t CUDARTAPI __cudaPopCallConfiguration(dim3 *gridDim, dim3 *blockDim, + size_t *sharedMem, + void *stream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + return g_last_cudaError = cudaSuccess; +} + +void CUDARTAPI __cudaRegisterFunction(void **fatCubinHandle, + const char *hostFun, char *deviceFun, + const char *deviceName, int thread_limit, + uint3 *tid, uint3 *bid, dim3 *bDim, + dim3 *gDim) { + cudaRegisterFunctionInternal(fatCubinHandle, hostFun, deviceFun, deviceName, + thread_limit, tid, bid, bDim, gDim); +} + +extern void __cudaRegisterVar( + void **fatCubinHandle, + char *hostVar, // pointer to...something + char *deviceAddress, // name of variable + const char *deviceName, // name of variable (same as above) + int ext, int size, int constant, int global) { + cudaRegisterVarInternal(fatCubinHandle, hostVar, deviceAddress, deviceName, + ext, size, constant, global); +} + +__host__ cudaError_t CUDARTAPI cudaConfigureCall(dim3 gridDim, dim3 blockDim, + size_t sharedMem, + cudaStream_t stream) { + return cudaConfigureCallInternal(gridDim, blockDim, sharedMem, stream); +} + +void __cudaUnregisterFatBinary(void **fatCubinHandle) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } +} + +cudaError_t cudaDeviceReset(void) { + // Should reset the simulated GPU + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + return g_last_cudaError = cudaSuccess; +} + +cudaError_t CUDARTAPI cudaDeviceSynchronize(void) { + return cudaDeviceSynchronizeInternal(); +} -__host__ cudaError_t CUDARTAPI cudaEventCreate(cudaEvent_t *event) +void __cudaRegisterShared(void **fatCubinHandle, void **devicePtr) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + // we don't do anything here + printf("GPGPU-Sim PTX: __cudaRegisterShared\n"); +} + +void CUDARTAPI __cudaRegisterSharedVar(void **fatCubinHandle, void **devicePtr, + size_t size, size_t alignment, + int storage) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + // we don't do anything here + printf("GPGPU-Sim PTX: __cudaRegisterSharedVar\n"); +} + +void __cudaRegisterTexture( + void **fatCubinHandle, const struct textureReference *hostVar, + const void **deviceAddress, const char *deviceName, int dim, int norm, + int ext) // passes in a newly created textureReference { - CUevent_st *e = new CUevent_st(false); - g_timer_events[e->get_uid()] = e; + __cudaRegisterTextureInternal(fatCubinHandle, hostVar, deviceAddress, + deviceName, dim, norm, ext); +} + +char __cudaInitModule(void **fatCubinHandle) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + cuda_not_implemented(__my_func__, __LINE__); + return g_last_cudaError = cudaErrorUnknown; +} + +cudaError_t cudaGLRegisterBufferObject(GLuint bufferObj) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("GPGPU-Sim PTX: Execution warning: ignoring call to \"%s\"\n", + __my_func__); + return g_last_cudaError = cudaSuccess; +} + +cudaError_t cudaGLMapBufferObject(void **devPtr, GLuint bufferObj) { + return cudaGLMapBufferObjectInternal(devPtr, bufferObj); +} + +cudaError_t cudaGLUnmapBufferObject(GLuint bufferObj) { + return cudaGLUnmapBufferObjectInternal(bufferObj); +} + +cudaError_t cudaGLUnregisterBufferObject(GLuint bufferObj) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("GPGPU-Sim PTX: Execution warning: ignoring call to \"%s\"\n", + __my_func__); + return g_last_cudaError = cudaSuccess; +} + +#if (CUDART_VERSION >= 2010) + +cudaError_t CUDARTAPI cudaHostAlloc(void **pHost, size_t bytes, + unsigned int flags) { + return cudaHostAllocInternal(pHost, bytes, flags); +} + +cudaError_t CUDARTAPI cudaHostGetDevicePointer(void **pDevice, void *pHost, + unsigned int flags) { + return cudaHostGetDevicePointerInternal(pDevice, pHost, flags); +} + +__host__ cudaError_t CUDARTAPI +cudaPointerGetAttributes(cudaPointerAttributes *attributes, const void *ptr) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + cuda_not_implemented(__my_func__, __LINE__); + return g_last_cudaError = cudaErrorUnknown; +} + +__host__ cudaError_t CUDARTAPI cudaDeviceCanAccessPeer(int *canAccessPeer, + int device, + int peerDevice) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + cuda_not_implemented(__my_func__, __LINE__); + return g_last_cudaError = cudaErrorUnknown; +} + +__host__ cudaError_t CUDARTAPI cudaDeviceEnablePeerAccess(int peerDevice, + unsigned int flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + cuda_not_implemented(__my_func__, __LINE__); + return g_last_cudaError = cudaErrorUnknown; +} + +cudaError_t CUDARTAPI cudaSetValidDevices(int *device_arr, int len) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + cuda_not_implemented(__my_func__, __LINE__); + return g_last_cudaError = cudaErrorUnknown; +} + +cudaError_t CUDARTAPI cudaSetDeviceFlags(int flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + // This flag is implicitly always on (unless you are using the driver API). It + // is safe for GPGPU-Sim to just ignore it. + if (cudaDeviceMapHost == flags) { + return g_last_cudaError = cudaSuccess; + } else { + cuda_not_implemented(__my_func__, __LINE__); + return g_last_cudaError = cudaErrorUnknown; + } +} + +cudaError_t CUDARTAPI cudaFuncGetAttributes(struct cudaFuncAttributes *attr, + const char *hostFun) { + return cudaFuncGetAttributesInternal(attr, hostFun); +} + +cudaError_t CUDARTAPI cudaEventCreateWithFlags(cudaEvent_t *event, int flags) { + CUevent_st *e = new CUevent_st(flags == cudaEventBlockingSync); + g_timer_events[e->get_uid()] = e; #if CUDART_VERSION >= 3000 - *event = e; + *event = e; #else - *event = e->get_uid(); + *event = e->get_uid(); #endif - return g_last_cudaError = cudaSuccess; + return g_last_cudaError = cudaSuccess; +} + +cudaError_t CUDARTAPI cudaDriverGetVersion(int *driverVersion) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + *driverVersion = CUDART_VERSION; + return g_last_cudaError = cudaSuccess; +} + +cudaError_t CUDARTAPI cudaRuntimeGetVersion(int *runtimeVersion) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + *runtimeVersion = CUDART_VERSION; + return g_last_cudaError = cudaSuccess; } -CUevent_st *get_event(cudaEvent_t event) -{ - unsigned event_uid; #if CUDART_VERSION >= 3000 - event_uid = event->get_uid(); -#else - event_uid = event; +__host__ cudaError_t CUDARTAPI +cudaFuncSetCacheConfig(const char *func, enum cudaFuncCache cacheConfig) { + return cudaFuncSetCacheConfigInternal(func, cacheConfig); +} + +// Jin: hack for cdp +__host__ cudaError_t CUDARTAPI cudaDeviceSetLimit(enum cudaLimit limit, + size_t value) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + return g_last_cudaError = cudaSuccess; +} + +//#if CUDART_VERSION >= 9000 +//__host__ cudaError_t cudaFuncSetAttribute ( const void* func, enum +// cudaFuncAttribute attr, int value ) { + +// ignore this Attribute for now, and the default is that carveout = +// cudaSharedmemCarveoutDefault; // (-1) +// return g_last_cudaError = cudaSuccess; +//} + +#endif + #endif - event_tracker_t::iterator e = g_timer_events.find(event_uid); - if( e == g_timer_events.end() ) - return NULL; - return e->second; + +#if CUDART_VERSION >= 9000 +/** + * \brief Set attributes for a given function + * + * This function sets the attributes of a function specified via \p entry. + * The parameter \p entry must be a pointer to a function that executes + * on the device. The parameter specified by \p entry must be declared as a \p + * __global__ function. The enumeration defined by \p attr is set to the value + * defined by \p value If the specified function does not exist, then + * ::cudaErrorInvalidDeviceFunction is returned. If the specified attribute + * cannot be written, or if the value is incorrect, then ::cudaErrorInvalidValue + * is returned. + * + * Valid values for \p attr are: + * ::cuFuncAttrMaxDynamicSharedMem - Maximum size of dynamic shared memory per + * block + * ::cudaFuncAttributePreferredSharedMemoryCarveout - Preferred shared memory-L1 + * cache split ratio + * + * \param entry - Function to get attributes of + * \param attr - Attribute to set + * \param value - Value to set + * + * \return + * ::cudaSuccess, + * ::cudaErrorInitializationError, + * ::cudaErrorInvalidDeviceFunction, + * ::cudaErrorInvalidValue + * \notefnerr + * + * \ref ::cudaLaunchKernel(const T *func, dim3 gridDim, dim3 blockDim, void + * **args, size_t sharedMem, cudaStream_t stream) "cudaLaunchKernel (C++ API)", + * \ref ::cudaFuncSetCacheConfig(T*, enum cudaFuncCache) "cudaFuncSetCacheConfig + * (C++ API)", \ref ::cudaFuncGetAttributes(struct cudaFuncAttributes*, const + * void*) "cudaFuncGetAttributes (C API)", + * ::cudaSetDoubleForDevice, + * ::cudaSetDoubleForHost, + * \ref ::cudaSetupArgument(T, size_t) "cudaSetupArgument (C++ API)" + */ +cudaError_t CUDARTAPI cudaFuncSetAttribute(const void *func, + enum cudaFuncAttribute attr, + int value) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf( + "GPGPU-Sim PTX: Execution warning: ignoring call to \"%s ( func=%p, " + "attr=%d, value=%d )\"\n", + __my_func__, func, attr, value); + return g_last_cudaError = cudaSuccess; } +#endif -__host__ cudaError_t CUDARTAPI cudaEventRecord(cudaEvent_t event, cudaStream_t stream) -{ - CUevent_st *e = get_event(event); - if( !e ) return g_last_cudaError = cudaErrorUnknown; - struct CUstream_st *s = (struct CUstream_st *)stream; - stream_operation op(e,s); - g_stream_manager->push(op); - return g_last_cudaError = cudaSuccess; +cudaError_t CUDARTAPI cudaGLSetGLDevice(int device) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("GPGPU-Sim PTX: Execution warning: ignoring call to \"%s\"\n", + __my_func__); + return g_last_cudaError = cudaErrorUnknown; } -__host__ cudaError_t CUDARTAPI cudaEventQuery(cudaEvent_t event) -{ - CUevent_st *e = get_event(event); - if( e == NULL ) { - return g_last_cudaError = cudaErrorInvalidValue; - } else if( e->done() ) { - return g_last_cudaError = cudaSuccess; - } else { - return g_last_cudaError = cudaErrorNotReady; - } +typedef void *HGPUNV; + +cudaError_t CUDARTAPI cudaWGLGetDevice(int *device, HGPUNV hGpu) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + cuda_not_implemented(__my_func__, __LINE__); + return g_last_cudaError = cudaErrorUnknown; } -__host__ cudaError_t CUDARTAPI cudaEventSynchronize(cudaEvent_t event) -{ - printf("GPGPU-Sim API: cudaEventSynchronize ** waiting for event\n"); - fflush(stdout); - CUevent_st *e = (CUevent_st*) event; - while( !e->done() ) - ; - printf("GPGPU-Sim API: cudaEventSynchronize ** event detected\n"); - fflush(stdout); - return g_last_cudaError = cudaSuccess; +void CUDARTAPI __cudaMutexOperation(int lock) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + cuda_not_implemented(__my_func__, __LINE__); } -__host__ cudaError_t CUDARTAPI cudaEventDestroy(cudaEvent_t event) -{ - CUevent_st *e = get_event(event); - unsigned event_uid = e->get_uid(); - event_tracker_t::iterator pe = g_timer_events.find(event_uid); - if( pe == g_timer_events.end() ) - return g_last_cudaError = cudaErrorInvalidValue; - g_timer_events.erase(pe); - return g_last_cudaError = cudaSuccess; +void CUDARTAPI __cudaTextureFetch(const void *tex, void *index, int integer, + void *val) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + cuda_not_implemented(__my_func__, __LINE__); +} } +namespace cuda_math { -__host__ cudaError_t CUDARTAPI cudaEventElapsedTime(float *ms, cudaEvent_t start, cudaEvent_t end) -{ - time_t elapsed_time; - CUevent_st *s = get_event(start); - CUevent_st *e = get_event(end); - if( s==NULL || e==NULL ) - return g_last_cudaError = cudaErrorUnknown; - elapsed_time = e->clock() - s->clock(); - *ms = 1000*elapsed_time; - return g_last_cudaError = cudaSuccess; +void CUDARTAPI __cudaMutexOperation(int lock) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + cuda_not_implemented(__my_func__, __LINE__); } +void CUDARTAPI __cudaTextureFetch(const void *tex, void *index, int integer, + void *val) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + cuda_not_implemented(__my_func__, __LINE__); +} +int CUDARTAPI __cudaSynchronizeThreads(void **, void *) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + // TODO This function should syncronize if we support Asyn kernel calls + return g_last_cudaError = cudaSuccess; +} -/******************************************************************************* - * * - * * - * * - *******************************************************************************/ +} // namespace cuda_math -__host__ cudaError_t CUDARTAPI cudaThreadExit(void) -{ - exit_simulation(); - return g_last_cudaError = cudaSuccess; +//////// + +/// static functions + +int cuda_runtime_api::load_static_globals(symbol_table *symtab, + unsigned min_gaddr, + unsigned max_gaddr, gpgpu_t *gpu) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("GPGPU-Sim PTX: loading globals with explicit initializers... \n"); + fflush(stdout); + int ng_bytes = 0; + symbol_table::iterator g = symtab->global_iterator_begin(); + + for (; g != symtab->global_iterator_end(); g++) { + symbol *global = *g; + if (global->has_initializer()) { + printf("GPGPU-Sim PTX: initializing '%s' ... ", + global->name().c_str()); + unsigned addr = global->get_address(); + const type_info *type = global->type(); + type_info_key ti = type->get_key(); + size_t size; + int t; + ti.type_decode(size, t); + int nbytes = size / 8; + int offset = 0; + std::list<operand_info> init_list = global->get_initializer(); + for (std::list<operand_info>::iterator i = init_list.begin(); + i != init_list.end(); i++) { + operand_info op = *i; + ptx_reg_t value = op.get_literal_value(); + assert((addr + offset + nbytes) < + min_gaddr); // min_gaddr is start of "heap" for cudaMalloc + gpu->get_global_memory()->write(addr + offset, nbytes, &value, NULL, + NULL); // assuming little endian here + offset += nbytes; + ng_bytes += nbytes; + } + printf(" wrote %u bytes\n", offset); + } + } + printf("GPGPU-Sim PTX: finished loading globals (%u bytes total).\n", + ng_bytes); + fflush(stdout); + return ng_bytes; } -__host__ cudaError_t CUDARTAPI cudaThreadSynchronize(void) -{ - //Called on host side - synchronize(); - return g_last_cudaError = cudaSuccess; -}; +int cuda_runtime_api::load_constants(symbol_table *symtab, addr_t min_gaddr, + gpgpu_t *gpu) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("GPGPU-Sim PTX: loading constants with explicit initializers... "); + fflush(stdout); + int nc_bytes = 0; + symbol_table::iterator g = symtab->const_iterator_begin(); -int CUDARTAPI __cudaSynchronizeThreads(void**, void*) -{ - return cudaThreadExit(); + for (; g != symtab->const_iterator_end(); g++) { + symbol *constant = *g; + if (constant->is_const() && constant->has_initializer()) { + // get the constant element data size + int basic_type; + size_t num_bits; + constant->type()->get_key().type_decode(num_bits, basic_type); + + std::list<operand_info> init_list = constant->get_initializer(); + int nbytes_written = 0; + for (std::list<operand_info>::iterator i = init_list.begin(); + i != init_list.end(); i++) { + operand_info op = *i; + ptx_reg_t value = op.get_literal_value(); + int nbytes = num_bits / 8; + switch (op.get_type()) { + case int_t: + assert(nbytes >= 1); + break; + case float_op_t: + assert(nbytes == 4); + break; + case double_op_t: + assert(nbytes >= 4); + break; // account for double DEMOTING + default: + abort(); + } + unsigned addr = constant->get_address() + nbytes_written; + assert(addr + nbytes < min_gaddr); + + gpu->get_global_memory()->write( + addr, nbytes, &value, NULL, + NULL); // assume little endian (so u8 is the first byte in u32) + nc_bytes += nbytes; + nbytes_written += nbytes; + } + } + } + printf(" done.\n"); + fflush(stdout); + return nc_bytes; } +kernel_info_t *cuda_runtime_api::gpgpu_cuda_ptx_sim_init_grid( + const char *hostFun, gpgpu_ptx_sim_arg_list_t args, struct dim3 gridDim, + struct dim3 blockDim, CUctx_st *context) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + function_info *entry = context->get_kernel(hostFun); + gpgpu_t *gpu = context->get_device()->get_gpgpu(); + /* + Passing a snapshot of the GPU's current texture mapping to the kernel's info + as kernels should use texture bindings present at the time of their launch. + */ + kernel_info_t *result = + new kernel_info_t(gridDim, blockDim, entry, gpu->getNameArrayMapping(), + gpu->getNameInfoMapping()); + if (entry == NULL) { + printf( + "GPGPU-Sim PTX: ERROR launching kernel -- no PTX implementation found " + "for %p\n", + hostFun); + abort(); + } + unsigned argcount = args.size(); + unsigned argn = 1; + for (gpgpu_ptx_sim_arg_list_t::iterator a = args.begin(); a != args.end(); + a++) { + entry->add_param_data(argcount - argn, &(*a)); + argn++; + } + + entry->finalize(result->get_param_memory()); + gpgpu_ctx->func_sim->g_ptx_kernel_count++; + fflush(stdout); + if (g_debug_execution >= 4) { + entry->ptx_jit_config(g_mallocPtr_Size, result->get_param_memory(), + (gpgpu_t *)context->get_device()->get_gpgpu(), + gridDim, blockDim); + } + + return result; +} /******************************************************************************* * * * * * * *******************************************************************************/ +//***extra api for pytorch*** -#if (CUDART_VERSION >= 3010) +CUresult CUDAAPI cuGetErrorString(CUresult error, const char **pStr) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} -typedef struct CUuuid_st { /**< CUDA definition of UUID */ - char bytes[16]; -} CUuuid; +CUresult CUDAAPI cuGetErrorName(CUresult error, const char **pStr) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} -/** - * CUDA UUID types - */ -// typedef __device_builtin__ struct CUuuid_st cudaUUID_t; +CUresult CUDAAPI cuInit(unsigned int Flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} -__host__ cudaError_t CUDARTAPI cudaGetExportTable(const void **ppExportTable, const cudaUUID_t *pExportTableId) -{ - printf("cudaGetExportTable: UUID = "); - for (int s = 0; s < 16; s++) { - printf("%#2x ", (unsigned char) (pExportTableId->bytes[s])); - } - printf("\n"); - return g_last_cudaError = cudaSuccess; +CUresult CUDAAPI cuDriverGetVersion(int *driverVersion) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + cudaError_t e = cudaDriverGetVersion(driverVersion); + assert(e == cudaSuccess); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuDeviceGet(CUdevice *device, int ordinal) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + int deviceI = -1; + cudaError_t e = cudaGetDevice(&deviceI); + assert(e == cudaSuccess); + assert(deviceI != -1); + *device = deviceI; + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuDeviceGetCount(int *count) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + cudaError_t e = cudaGetDeviceCount(count); + assert(e == cudaSuccess); + return CUDA_SUCCESS; } +CUresult CUDAAPI cuDeviceGetName(char *name, int len, CUdevice dev) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + assert(len >= 10); + strcpy(name, "GPGPU-Sim"); + return CUDA_SUCCESS; +} + +#if CUDART_VERSION >= 3020 +CUresult CUDAAPI cuDeviceTotalMem(size_t *bytes, CUdevice dev) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + *bytes = 20000000000; // dummy value + return CUDA_SUCCESS; +} +#endif /* CUDART_VERSION >= 3020 */ +#if (CUDART_VERSION > 5000) +CUresult CUDAAPI cuDeviceGetAttribute(int *pi, CUdevice_attribute attrib, + CUdevice dev) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + cudaError_t e = cudaDeviceGetAttribute(pi, (cudaDeviceAttr)attrib, dev); + assert(e == cudaSuccess); + + return CUDA_SUCCESS; +} #endif +CUresult CUDAAPI cuDeviceGetProperties(CUdevprop *prop, CUdevice dev) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuDeviceComputeCapability(int *major, int *minor, + CUdevice dev) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} -/******************************************************************************* - * * - * * - * * - *******************************************************************************/ +#if CUDART_VERSION >= 7000 -//#include "../../cuobjdump_to_ptxplus/cuobjdump_parser.h" +CUresult CUDAAPI cuDevicePrimaryCtxRetain(CUcontext *pctx, CUdevice dev) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} -enum cuobjdumpSectionType { - PTXSECTION=0, - ELFSECTION -}; +CUresult CUDAAPI cuDevicePrimaryCtxRelease(CUdevice dev) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuDevicePrimaryCtxSetFlags(CUdevice dev, unsigned int flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} -class cuobjdumpSection { -public: - //Constructor - cuobjdumpSection() { - arch = 0; - identifier = ""; - } - virtual ~cuobjdumpSection() {} - unsigned getArch() {return arch;} - void setArch(unsigned a) {arch = a;} - std::string getIdentifier() {return identifier;} - void setIdentifier(std::string i) {identifier = i;} - virtual void print(){std::cout << "cuobjdump Section: unknown type" << std::endl;} -private: - unsigned arch; - std::string identifier; -}; +CUresult CUDAAPI cuDevicePrimaryCtxGetState(CUdevice dev, unsigned int *flags, + int *active) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} -class cuobjdumpELFSection : public cuobjdumpSection -{ -public: - cuobjdumpELFSection() {} - virtual ~cuobjdumpELFSection() { - elffilename = ""; - sassfilename = ""; - } - std::string getELFfilename() {return elffilename;} - void setELFfilename(std::string f) {elffilename = f;} - std::string getSASSfilename() {return sassfilename;} - void setSASSfilename(std::string f) {sassfilename = f;} - virtual void print() { - std::cout << "ELF Section:" << std::endl; - std::cout << "arch: sm_" << getArch() << std::endl; - std::cout << "identifier: " << getIdentifier() << std::endl; - std::cout << "elf filename: " << getELFfilename() << std::endl; - std::cout << "sass filename: " << getSASSfilename() << std::endl; - std::cout << std::endl; - } -private: - std::string elffilename; - std::string sassfilename; -}; +CUresult CUDAAPI cuDevicePrimaryCtxReset(CUdevice dev) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} -class cuobjdumpPTXSection : public cuobjdumpSection -{ -public: - cuobjdumpPTXSection(){ - ptxfilename = ""; - } - std::string getPTXfilename() {return ptxfilename;} - void setPTXfilename(std::string f) {ptxfilename = f;} - virtual void print() { - std::cout << "PTX Section:" << std::endl; - std::cout << "arch: sm_" << getArch() << std::endl; - std::cout << "identifier: " << getIdentifier() << std::endl; - std::cout << "ptx filename: " << getPTXfilename() << std::endl; - std::cout << std::endl; - } -private: - std::string ptxfilename; -}; +#endif /* CUDART_VERSION >= 7000 */ -std::list<cuobjdumpSection*> cuobjdumpSectionList; -std::list<cuobjdumpSection*> libSectionList; +#if CUDART_VERSION >= 3020 +CUresult CUDAAPI cuCtxCreate(CUcontext *pctx, unsigned int flags, + CUdevice dev) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +#endif /* CUDART_VERSION >= 3020 */ -// sectiontype: 0 for ptx, 1 for elf -void addCuobjdumpSection(int sectiontype){ - if (sectiontype) - cuobjdumpSectionList.push_front(new cuobjdumpELFSection()); - else - cuobjdumpSectionList.push_front(new cuobjdumpPTXSection()); - printf("## Adding new section %s\n", sectiontype?"ELF":"PTX"); +#if CUDART_VERSION >= 4000 +CUresult CUDAAPI cuCtxDestroy(CUcontext ctx) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } +#endif /* CUDART_VERSION >= 4000 */ -void setCuobjdumparch(const char* arch){ - unsigned archnum; - sscanf(arch, "sm_%u", &archnum); - assert (archnum && "cannot have sm_0"); - printf("Adding arch: %s\n", arch); - cuobjdumpSectionList.front()->setArch(archnum); +#if CUDART_VERSION >= 4000 +CUresult CUDAAPI cuCtxPushCurrent(CUcontext ctx) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -void setCuobjdumpidentifier(const char* identifier){ - printf("Adding identifier: %s\n", identifier); - cuobjdumpSectionList.front()->setIdentifier(identifier); +CUresult CUDAAPI cuCtxPopCurrent(CUcontext *pctx) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -void setCuobjdumpptxfilename(const char* filename){ - printf("Adding ptx filename: %s\n", filename); - cuobjdumpSection* x = cuobjdumpSectionList.front(); - if (dynamic_cast<cuobjdumpPTXSection*>(x) == NULL){ - assert (0 && "You shouldn't be trying to add a ptxfilename to an elf section"); - } - (dynamic_cast<cuobjdumpPTXSection*>(x))->setPTXfilename(filename); +CUresult CUDAAPI cuCtxSetCurrent(CUcontext ctx) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -void setCuobjdumpelffilename(const char* filename){ - if (dynamic_cast<cuobjdumpELFSection*>(cuobjdumpSectionList.front()) == NULL){ - assert (0 && "You shouldn't be trying to add a elffilename to an ptx section"); - } - (dynamic_cast<cuobjdumpELFSection*>(cuobjdumpSectionList.front()))->setELFfilename(filename); +CUresult CUDAAPI cuCtxGetCurrent(CUcontext *pctx) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } +#endif /* CUDART_VERSION >= 4000 */ -void setCuobjdumpsassfilename(const char* filename){ - if (dynamic_cast<cuobjdumpELFSection*>(cuobjdumpSectionList.front()) == NULL){ - assert (0 && "You shouldn't be trying to add a sassfilename to an ptx section"); - } - (dynamic_cast<cuobjdumpELFSection*>(cuobjdumpSectionList.front()))->setSASSfilename(filename); +CUresult CUDAAPI cuCtxGetDevice(CUdevice *device) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -extern int cuobjdump_parse(); -extern FILE *cuobjdump_in; -//! Return the executable file of the process containing the PTX/SASS code -//! -//! This Function returns the executable file ran by the process. This -//! executable is supposed to contain the PTX/SASS code. It provides workaround -//! for processes running on valgrind by dereferencing /proc/<pid>/exe within the -//! GPGPU-Sim process before calling cuobjdump to extract PTX/SASS. This is -//! needed because valgrind uses x86 emulation to detect memory leak. Other -//! processes (e.g. cuobjdump) reading /proc/<pid>/exe will see the emulator -//! executable instead of the application binary. -//! -std::string get_app_binary(){ - char self_exe_path[1025]; -#ifdef __APPLE__ - uint32_t size = sizeof(self_exe_path); - if( _NSGetExecutablePath(self_exe_path,&size) != 0 ) { - printf("GPGPU-Sim ** ERROR: _NSGetExecutablePath input buffer too small\n"); - exit(1); - } -#else - std::stringstream exec_link; - exec_link << "/proc/self/exe"; +#if CUDART_VERSION >= 7000 +CUresult CUDAAPI cuCtxGetFlags(unsigned int *flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +#endif /* CUDART_VERSION >= 7000 */ - ssize_t path_length = readlink(exec_link.str().c_str(), self_exe_path, 1024); - assert(path_length != -1); - self_exe_path[path_length] = '\0'; +CUresult CUDAAPI cuCtxSynchronize(void) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuCtxSetLimit(CUlimit limit, size_t value) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuCtxGetLimit(size_t *pvalue, CUlimit limit) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuCtxGetCacheConfig(CUfunc_cache *pconfig) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuCtxSetCacheConfig(CUfunc_cache config) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +#if CUDART_VERSION >= 4020 +CUresult CUDAAPI cuCtxGetSharedMemConfig(CUsharedconfig *pConfig) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuCtxSetSharedMemConfig(CUsharedconfig config) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} #endif - printf("self exe links to: %s\n", self_exe_path); - return self_exe_path; +CUresult CUDAAPI cuCtxGetApiVersion(CUcontext ctx, unsigned int *version) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -//! Call cuobjdump to extract everything (-elf -sass -ptx) -/*! - * This Function extract the whole PTX (for all the files) using cuobjdump - * to _cuobjdump_complete_output_XXXXXX then runs a parser to chop it up with each binary in - * its own file - * It is also responsible for extracting the libraries linked to the binary if the option is - * enabled - * */ -void extract_code_using_cuobjdump(){ - CUctx_st *context = GPGPUSim_Context(); - char command[1000]; +CUresult CUDAAPI cuCtxGetStreamPriorityRange(int *leastPriority, + int *greatestPriority) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} - std::string app_binary = get_app_binary(); +CUresult CUDAAPI cuCtxAttach(CUcontext *pctx, unsigned int flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuCtxDetach(CUcontext ctx) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} - char fname[1024]; - snprintf(fname,1024,"_cuobjdump_complete_output_XXXXXX"); - int fd=mkstemp(fname); - close(fd); - // Running cuobjdump using dynamic link to current process - snprintf(command,1000,"md5sum %s ", app_binary.c_str()); - printf("Running md5sum using \"%s\"\n", command); - system(command); - // Running cuobjdump using dynamic link to current process - // Needs the option '-all' to extract PTX from CDP-enabled binary - extern bool g_cdp_enabled; - if(!g_cdp_enabled) - snprintf(command,1000,"$CUDA_INSTALL_PATH/bin/cuobjdump -ptx -elf -sass %s > %s", app_binary.c_str(), fname); - else - snprintf(command,1000,"$CUDA_INSTALL_PATH/bin/cuobjdump -ptx -elf -sass -all %s > %s", app_binary.c_str(), fname); - bool parse_output = true; - int result = system(command); - if(result) { - if (context->get_device()->get_gpgpu()->get_config().experimental_lib_support() && (result == 65280)) { - // Some CUDA application may exclusively use kernels provided by CUDA - // libraries (e.g. CUBLAS). Skipping cuobjdump extraction from the - // executable for this case. - // 65280 is the return code from cuobjdump denoting the specific error (tested on CUDA 4.0/4.1/4.2) - printf("WARNING: Failed to execute: %s\n", command); - printf(" Executable binary does not contain any GPU kernel.\n"); - parse_output = false; - } else { - printf("ERROR: Failed to execute: %s\n", command); - exit(1); - } - } +CUresult CUDAAPI cuModuleLoad(CUmodule *module, const char *fname) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} - if (parse_output) { - printf("Parsing file %s\n", fname); - cuobjdump_in = fopen(fname, "r"); +CUresult CUDAAPI cuModuleLoadData(CUmodule *module, const void *image) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} - cuobjdump_parse(); - fclose(cuobjdump_in); - printf("Done parsing!!!\n"); - } else { - printf("Parsing skipped for %s\n", fname); - } +CUresult CUDAAPI cuModuleLoadDataEx(CUmodule *module, const void *image, + unsigned int numOptions, + CUjit_option *options, + void **optionValues) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} - if (context->get_device()->get_gpgpu()->get_config().experimental_lib_support()){ - //Experimental library support - //Currently only for cufft +CUresult CUDAAPI cuModuleLoadFatBinary(CUmodule *module, const void *fatCubin) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} - std::stringstream cmd; - cmd << "ldd " << app_binary << " | grep $CUDA_INSTALL_PATH | awk \'{print $3}\' > _tempfile_.txt"; - int result = system(cmd.str().c_str()); - if(result){ - std::cout << "Failed to execute: " << cmd.str() << std::endl; - exit(1); - } - std::ifstream libsf; - libsf.open("_tempfile_.txt"); - if(!libsf.is_open()) { - std::cout << "Failed to open: _tempfile_.txt" << std::endl; - exit(1); - } +CUresult CUDAAPI cuModuleUnload(CUmodule hmod) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} - //Save the original section list - std::list<cuobjdumpSection*> tmpsl = cuobjdumpSectionList; - cuobjdumpSectionList.clear(); +CUresult CUDAAPI cuModuleGetFunction(CUfunction *hfunc, CUmodule hmod, + const char *name) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} - std::string line; - std::getline(libsf, line); - std::cout << "DOING: " << line << std::endl; - int cnt=1; - while(libsf.good()){ - std::stringstream libcodfn; - libcodfn << "_cuobjdump_complete_lib_" << cnt << "_"; - cmd.str(""); //resetting - cmd << "$CUDA_INSTALL_PATH/bin/cuobjdump -ptx -elf -sass "; - cmd << line; - cmd << " > "; - cmd << libcodfn.str(); - std::cout << "Running cuobjdump on " << line << std::endl; - std::cout << "Using command: " << cmd.str() << std::endl; - result = system(cmd.str().c_str()); - if(result) {printf("ERROR: Failed to execute: %s\n", command); exit(1);} - std::cout << "Done" << std::endl; +#if CUDART_VERSION >= 3020 +CUresult CUDAAPI cuModuleGetGlobal(CUdeviceptr *dptr, size_t *bytes, + CUmodule hmod, const char *name) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +#endif /* CUDART_VERSION >= 3020 */ - std::cout << "Trying to parse " << libcodfn.str() << std::endl; - cuobjdump_in = fopen(libcodfn.str().c_str(), "r"); - cuobjdump_parse(); - fclose(cuobjdump_in); - std::getline(libsf, line); - } - libSectionList = cuobjdumpSectionList; +CUresult CUDAAPI cuModuleGetTexRef(CUtexref *pTexRef, CUmodule hmod, + const char *name) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} - //Restore the original section list - cuobjdumpSectionList = tmpsl; - } +CUresult CUDAAPI cuModuleGetSurfRef(CUsurfref *pSurfRef, CUmodule hmod, + const char *name) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -//! Read file into char* -//TODO: convert this to C++ streams, will be way cleaner -char* readfile (const std::string filename){ - assert (filename != ""); - FILE* fp = fopen(filename.c_str(),"r"); - if (!fp) { - std::cout << "ERROR: Could not open file %s for reading\n" << filename << std::endl; - assert (0); - } - // finding size of the file - int filesize= 0; - fseek (fp , 0 , SEEK_END); +#if CUDART_VERSION >= 6050 - filesize = ftell (fp); - fseek (fp, 0, SEEK_SET); - // allocate and copy the entire ptx - char* ret = (char*)malloc((filesize +1)* sizeof(char)); - fread(ret,1,filesize,fp); - ret[filesize]='\0'; - fclose(fp); - return ret; +CUresult CUDAAPI cuLinkCreate(unsigned int numOptions, CUjit_option *options, + void **optionValues, CUlinkState *stateOut) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + // currently do not support options or multiple CUlinkStates + return CUDA_SUCCESS; } -//! Function that helps debugging -void printSectionList(std::list<cuobjdumpSection*> sl) { - std::list<cuobjdumpSection*>::iterator iter; - for ( iter = sl.begin(); - iter != sl.end(); - iter++ - ){ - (*iter)->print(); - } +CUresult CUDAAPI cuLinkAddData(CUlinkState state, CUjitInputType type, + void *data, size_t size, const char *name, + unsigned int numOptions, CUjit_option *options, + void **optionValues) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + assert(type == CU_JIT_INPUT_PTX); + cuda_not_implemented(__my_func__, __LINE__); + return CUDA_ERROR_UNKNOWN; } -//! Remove unecessary sm versions from the section list -std::list<cuobjdumpSection*> pruneSectionList(std::list<cuobjdumpSection*> cuobjdumpSectionList, CUctx_st *context) { - unsigned forced_max_capability = context->get_device()->get_gpgpu()->get_config().get_forced_max_capability(); +CUresult CUDAAPI cuLinkAddFile(CUlinkState state, CUjitInputType type, + const char *path, unsigned int numOptions, + CUjit_option *options, void **optionValues) { + return cuLinkAddFileInternal(state, type, path, numOptions, options, + optionValues); +} +#endif - //For ptxplus, force the max capability to 19 if it's higher or unspecified(0) - if (context->get_device()->get_gpgpu()->get_config().convert_to_ptxplus()){ - if ( (forced_max_capability == 0) || - (forced_max_capability >= 20)){ - printf("GPGPU-Sim: WARNING: Capability >= 20 are not supported in PTXPlus\n\tSetting forced_max_capability to 19\n"); - forced_max_capability = 19; - } - } +#if CUDART_VERSION >= 5050 - std::list<cuobjdumpSection*> prunedList; +CUresult CUDAAPI cuLinkComplete(CUlinkState state, void **cubinOut, + size_t *sizeOut) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + // all cuLink* function are implemented to block until completion so nothing + // to do here + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuLinkDestroy(CUlinkState state) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + // currently do not support options or multiple CUlinkStates + return CUDA_SUCCESS; +} - //Find the highest capability (that is lower than the forced maximum) for each cubin file - //and set it in cuobjdumpSectionMap. Do this only for ptx sections - std::map<std::string, unsigned> cuobjdumpSectionMap; - int min_ptx_capability_found=0; - for ( std::list<cuobjdumpSection*>::iterator iter = cuobjdumpSectionList.begin(); - iter != cuobjdumpSectionList.end(); - iter++){ - unsigned capability = (*iter)->getArch(); - if(dynamic_cast<cuobjdumpPTXSection*>(*iter) != NULL){ - if(capability<min_ptx_capability_found || min_ptx_capability_found==0) - min_ptx_capability_found=capability; - if (capability <= forced_max_capability || forced_max_capability==0) { - if((cuobjdumpSectionMap.find((*iter)->getIdentifier())==cuobjdumpSectionMap.end()) - || (cuobjdumpSectionMap[(*iter)->getIdentifier()] < capability)) - cuobjdumpSectionMap[(*iter)->getIdentifier()] = capability; - } - } - } +#endif /* CUDART_VERSION >= 5050 */ - //Throw away the sections with the lower capabilites and push those with the highest in - //the pruned list - for ( std::list<cuobjdumpSection*>::iterator iter = cuobjdumpSectionList.begin(); - iter != cuobjdumpSectionList.end(); - iter++){ - unsigned capability = (*iter)->getArch(); - if(capability == cuobjdumpSectionMap[(*iter)->getIdentifier()]){ - prunedList.push_back(*iter); - } else { - delete *iter; - } - } - if(prunedList.empty()){ - printf("Error: No PTX sections found with sm capability that is lower than current forced maximum capability \n minimum ptx capability found = %u, maximum forced ptx capability = %u \n User might want to change either the forced maximum capability from gpgpusim configuration or update the compilation to generate the required PTX version\n",min_ptx_capability_found,forced_max_capability); - abort(); - } - return prunedList; +#if CUDART_VERSION >= 3020 +CUresult CUDAAPI cuMemGetInfo(size_t *free, size_t *total) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -//! Merge all PTX sections that have a specific identifier into one file -std::list<cuobjdumpSection*> mergeMatchingSections(std::list<cuobjdumpSection*> cuobjdumpSectionList, std::string identifier){ - const char *ptxcode = ""; - std::list<cuobjdumpSection*>::iterator old_iter; - cuobjdumpPTXSection* old_ptxsection = NULL; - cuobjdumpPTXSection* ptxsection; - std::list<cuobjdumpSection*> mergedList; +CUresult CUDAAPI cuMemAlloc(CUdeviceptr *dptr, size_t bytesize) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} - for ( std::list<cuobjdumpSection*>::iterator iter = cuobjdumpSectionList.begin(); - iter != cuobjdumpSectionList.end(); - iter++){ - if((ptxsection=dynamic_cast<cuobjdumpPTXSection*>(*iter)) != NULL && - strcmp(ptxsection->getIdentifier().c_str(), identifier.c_str()) == 0){ - // Read and remove the last PTX section - if (old_ptxsection != NULL) { - ptxcode = readfile(old_ptxsection->getPTXfilename()); - // remove ptx file? - delete *old_iter; - } +CUresult CUDAAPI cuMemAllocPitch(CUdeviceptr *dptr, size_t *pPitch, + size_t WidthInBytes, size_t Height, + unsigned int ElementSizeBytes) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} - // Append all the PTX from the last PTX section into the current PTX section - // Add 50 to ptxcode to ignore the information regarding version/target/address_size - if (strlen(ptxcode) >= 50) { - FILE *ptxfile = fopen((ptxsection->getPTXfilename()).c_str(), "a"); - fprintf(ptxfile, "%s", ptxcode + 50); - fclose(ptxfile); - } +CUresult CUDAAPI cuMemFree(CUdeviceptr dptr) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} - old_iter = iter; - old_ptxsection = ptxsection; - } - // Store all non-PTX sections and PTX sections with non-matching identifiers - else { - mergedList.push_back(*iter); - } - } +CUresult CUDAAPI cuMemGetAddressRange(CUdeviceptr *pbase, size_t *psize, + CUdeviceptr dptr) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} - // Store the final PTX section - mergedList.push_back(*old_iter); +CUresult CUDAAPI cuMemAllocHost(void **pp, size_t bytesize) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +#endif /* CUDART_VERSION >= 3020 */ - return mergedList; +CUresult CUDAAPI cuMemFreeHost(void *p) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -//! Merge any PTX sections with matching identifiers -std::list<cuobjdumpSection*> mergeSections(std::list<cuobjdumpSection*> cuobjdumpSectionList){ - std::vector<std::string> identifier; - cuobjdumpPTXSection* ptxsection; +CUresult CUDAAPI cuMemHostAlloc(void **pp, size_t bytesize, + unsigned int Flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} - // Add all identifiers present in PTX sections to a vector - for ( std::list<cuobjdumpSection*>::iterator iter = cuobjdumpSectionList.begin(); - iter != cuobjdumpSectionList.end(); - iter++){ - if((ptxsection=dynamic_cast<cuobjdumpPTXSection*>(*iter)) != NULL){ - std::string current_id = ptxsection->getIdentifier(); +#if CUDART_VERSION >= 3020 +CUresult CUDAAPI cuMemHostGetDevicePointer(CUdeviceptr *pdptr, void *p, + unsigned int Flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +#endif /* CUDART_VERSION >= 3020 */ - // If we haven't yet seen a given identifier, add it to the vector - if (std::find(identifier.begin(), identifier.end(), current_id) == identifier.end()) { - identifier.push_back(current_id); - } - } - } +CUresult CUDAAPI cuMemHostGetFlags(unsigned int *pFlags, void *p) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} - // Call mergeMatchingSections on all identifiers in the vector - for ( std::vector<std::string>::iterator iter = identifier.begin(); - iter != identifier.end(); - iter++) { - cuobjdumpSectionList = mergeMatchingSections(cuobjdumpSectionList, *iter); - } +#if CUDART_VERSION >= 6000 - return cuobjdumpSectionList; +CUresult CUDAAPI cuMemAllocManaged(CUdeviceptr *dptr, size_t bytesize, + unsigned int flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } +#endif /* CUDART_VERSION >= 6000 */ -//! Within the section list, find the ELF section corresponding to a given identifier -cuobjdumpELFSection* findELFSectionInList(std::list<cuobjdumpSection*> sectionlist, const std::string identifier){ +#if CUDART_VERSION >= 4010 - std::list<cuobjdumpSection*>::iterator iter; - for ( iter = sectionlist.begin(); - iter != sectionlist.end(); - iter++ - ){ - cuobjdumpELFSection* elfsection; - if((elfsection=dynamic_cast<cuobjdumpELFSection*>(*iter)) != NULL){ - if(elfsection->getIdentifier() == identifier) - return elfsection; - } - } - return NULL; +CUresult CUDAAPI cuDeviceGetByPCIBusId(CUdevice *dev, const char *pciBusId) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -//! Find an ELF section in all the known lists -cuobjdumpELFSection* findELFSection(const std::string identifier){ - cuobjdumpELFSection* sec = findELFSectionInList(cuobjdumpSectionList, identifier); - if (sec!=NULL)return sec; - sec = findELFSectionInList(libSectionList, identifier); - if (sec!=NULL)return sec; - std::cout << "Could not find " << identifier << std::endl; - assert(0 && "Could not find the required ELF section"); - return NULL; +CUresult CUDAAPI cuDeviceGetPCIBusId(char *pciBusId, int len, CUdevice dev) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -//! Within the section list, find the PTX section corresponding to a given identifier -cuobjdumpPTXSection* findPTXSectionInList(std::list<cuobjdumpSection*> sectionlist, const std::string identifier){ - std::list<cuobjdumpSection*>::iterator iter; - for ( iter = sectionlist.begin(); - iter != sectionlist.end(); - iter++ - ){ - cuobjdumpPTXSection* ptxsection; - if((ptxsection=dynamic_cast<cuobjdumpPTXSection*>(*iter)) != NULL){ - if(ptxsection->getIdentifier() == identifier) - return ptxsection; - else { - extern bool g_cdp_enabled; - if(g_cdp_enabled) { - printf("Warning: __cudaRegisterFatBinary needs %s, but find PTX section with %s\n", - identifier.c_str(), ptxsection->getIdentifier().c_str()); - return ptxsection; - } - } - } - } - return NULL; +CUresult CUDAAPI cuIpcGetEventHandle(CUipcEventHandle *pHandle, CUevent event) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -//! Find an PTX section in all the known lists -cuobjdumpPTXSection* findPTXSection(const std::string identifier){ - cuobjdumpPTXSection* sec = findPTXSectionInList(cuobjdumpSectionList, identifier); - if (sec!=NULL)return sec; - sec = findPTXSectionInList(libSectionList, identifier); - if (sec!=NULL)return sec; - std::cout << "Could not find " << identifier << std::endl; - assert(0 && "Could not find the required PTX section"); - return NULL; +CUresult CUDAAPI cuIpcOpenEventHandle(CUevent *phEvent, + CUipcEventHandle handle) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } +CUresult CUDAAPI cuIpcGetMemHandle(CUipcMemHandle *pHandle, CUdeviceptr dptr) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuIpcOpenMemHandle(CUdeviceptr *pdptr, CUipcMemHandle handle, + unsigned int Flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} -//! Extract the code using cuobjdump and remove unnecessary sections -void cuobjdumpInit(){ - CUctx_st *context = GPGPUSim_Context(); - extract_code_using_cuobjdump(); //extract all the output of cuobjdump to _cuobjdump_*.* - cuobjdumpSectionList = pruneSectionList(cuobjdumpSectionList, context); - cuobjdumpSectionList = mergeSections(cuobjdumpSectionList); +CUresult CUDAAPI cuIpcCloseMemHandle(CUdeviceptr dptr) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -std::map<int, std::string> fatbinmap; -std::map<int, bool>fatbin_registered; -std::map<std::string, symbol_table*> name_symtab; +#endif /* CUDART_VERSION >= 4010 */ -//! Keep track of the association between filename and cubin handle -void cuobjdumpRegisterFatBinary(unsigned int handle, const char* filename){ - fatbinmap[handle] = filename; +#if CUDART_VERSION >= 6050 +CUresult CUDAAPI cuMemHostRegister(void *p, size_t bytesize, + unsigned int Flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +__host__ cudaError_t cudaHostRegister(void *ptr, size_t size, + unsigned int flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return g_last_cudaError = cudaSuccess; } -//! Either submit PTX for simulation or convert SASS to PTXPlus and submit it -void cuobjdumpParseBinary(unsigned int handle){ +__host__ cudaError_t cudaProfilerStart() { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return g_last_cudaError = cudaSuccess; +} - if(fatbin_registered[handle]) return; - fatbin_registered[handle] = true; - CUctx_st *context = GPGPUSim_Context(); - std::string fname = fatbinmap[handle]; +__host__ cudaError_t cudaProfilerStop() { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return g_last_cudaError = cudaSuccess; +} - if (name_symtab.find(fname) != name_symtab.end()) { - symbol_table *symtab = name_symtab[fname]; - context->add_binary(symtab, handle); - return; - } +#endif +#if CUDART_VERSION >= 4000 - unsigned max_capability = 0; - for ( std::list<cuobjdumpSection*>::iterator iter = cuobjdumpSectionList.begin(); - iter != cuobjdumpSectionList.end(); - iter++){ - unsigned capability = (*iter)->getArch(); - if (capability > max_capability) max_capability = capability; - } - if (max_capability > 20) printf("WARNING: No guarantee that PTX will be parsed for SM version %u\n", max_capability); +CUresult CUDAAPI cuMemHostUnregister(void *p) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} - cuobjdumpPTXSection* ptx = findPTXSection(fname); - symbol_table *symtab; - char *ptxcode; - const char *override_ptx_name = getenv("PTX_SIM_KERNELFILE"); - if (override_ptx_name == NULL or getenv("PTX_SIM_USE_PTX_FILE") == NULL) { - ptxcode = readfile(ptx->getPTXfilename()); - } else { - printf("GPGPU-Sim PTX: overriding embedded ptx with '%s' (PTX_SIM_USE_PTX_FILE is set)\n", override_ptx_name); - ptxcode = readfile(override_ptx_name); - } - if(context->get_device()->get_gpgpu()->get_config().convert_to_ptxplus() ) { - cuobjdumpELFSection* elfsection = findELFSection(ptx->getIdentifier()); - assert (elfsection!= NULL); - char *ptxplus_str = gpgpu_ptx_sim_convert_ptx_and_sass_to_ptxplus( - ptx->getPTXfilename(), - elfsection->getELFfilename(), - elfsection->getSASSfilename()); - symtab=gpgpu_ptx_sim_load_ptx_from_string(ptxplus_str, handle); - printf("Adding %s with cubin handle %u\n", ptx->getPTXfilename().c_str(), handle); - context->add_binary(symtab, handle); - gpgpu_ptxinfo_load_from_string( ptxcode, handle, max_capability ); - delete[] ptxplus_str; - } else { - symtab=gpgpu_ptx_sim_load_ptx_from_string(ptxcode, handle); - printf("Adding %s with cubin handle %u\n", ptx->getPTXfilename().c_str(), handle); - context->add_binary(symtab, handle); - gpgpu_ptxinfo_load_from_string( ptxcode, handle, max_capability ); - } - load_static_globals(symtab,STATIC_ALLOC_LIMIT,0xFFFFFFFF,context->get_device()->get_gpgpu()); - load_constants(symtab,STATIC_ALLOC_LIMIT,context->get_device()->get_gpgpu()); - name_symtab[fname] = symtab; +CUresult CUDAAPI cuMemcpy(CUdeviceptr dst, CUdeviceptr src, size_t ByteCount) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} - //TODO: Remove temporarily files as per configurations +CUresult CUDAAPI cuMemcpyPeer(CUdeviceptr dstDevice, CUcontext dstContext, + CUdeviceptr srcDevice, CUcontext srcContext, + size_t ByteCount) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -void** CUDARTAPI __cudaRegisterFatBinary( void *fatCubin ) -{ -#if (CUDART_VERSION < 2010) - printf("GPGPU-Sim PTX: ERROR ** this version of GPGPU-Sim requires CUDA 2.1 or higher\n"); - exit(1); -#endif - CUctx_st *context = GPGPUSim_Context(); - static unsigned next_fat_bin_handle = 1; - if(context->get_device()->get_gpgpu()->get_config().use_cuobjdump()) { - // The following workaround has only been verified on 64-bit systems. - if (sizeof(void*) == 4) - printf("GPGPU-Sim PTX: FatBin file name extraction has not been tested on 32-bit system.\n"); +#endif /* CUDART_VERSION >= 4000 */ - #if (CUDART_VERSION <= 6000) - // FatBin handle from the .fatbin.c file (one of the intermediate files generated by NVCC) - typedef struct {int m; int v; const unsigned long long* d; char* f;} __fatDeviceText __attribute__ ((aligned (8))); - __fatDeviceText * fatDeviceText = (__fatDeviceText *) fatCubin; +#if CUDART_VERSION >= 3020 +CUresult CUDAAPI cuMemcpyHtoD(CUdeviceptr dstDevice, const void *srcHost, + size_t ByteCount) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} - // Extract the source code file name that generate the given FatBin. - // - Obtains the pointer to the actual fatbin structure from the FatBin handle (fatCubin). - // - An integer inside the fatbin structure contains the relative offset to the source code file name. - // - This offset differs among different CUDA and GCC versions. - char * pfatbin = (char*) fatDeviceText->d; - int offset = *((int*)(pfatbin+48)); - char * filename = (pfatbin+16+offset); - #else - const char * filename = "default"; - #endif - // The extracted file name is associated with a fat_cubin_handle passed - // into cudaLaunch(). Inside cudaLaunch(), the associated file name is - // used to find the PTX/SASS section from cuobjdump, which contains the - // PTX/SASS code for the launched kernel function. - // This allows us to work around the fact that cuobjdump only outputs the - // file name associated with each section. - unsigned long long fat_cubin_handle = next_fat_bin_handle; - next_fat_bin_handle++; - printf("GPGPU-Sim PTX: __cudaRegisterFatBinary, fat_cubin_handle = %llu, filename=%s\n", fat_cubin_handle, filename); - /*! - * This function extracts all data from all files in first call - * then for next calls, only returns the appropriate number - */ - assert(fat_cubin_handle >= 1); - if (fat_cubin_handle==1) cuobjdumpInit(); - cuobjdumpRegisterFatBinary(fat_cubin_handle, filename); +CUresult CUDAAPI cuMemcpyDtoH(void *dstHost, CUdeviceptr srcDevice, + size_t ByteCount) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} - return (void**)fat_cubin_handle; - } -#if (CUDART_VERSION < 8000) - else { - static unsigned source_num=1; - unsigned long long fat_cubin_handle = next_fat_bin_handle++; - __cudaFatCudaBinary *info = (__cudaFatCudaBinary *)fatCubin; - assert( info->version >= 3 ); - unsigned num_ptx_versions=0; - unsigned max_capability=0; - unsigned selected_capability=0; - bool found=false; - unsigned forced_max_capability = context->get_device()->get_gpgpu()->get_config().get_forced_max_capability(); - if (!info->ptx){ - printf("ERROR: Cannot find ptx code in cubin file\n" - "\tIf you are using CUDA 4.0 or higher, please enable -gpgpu_ptx_use_cuobjdump or downgrade to CUDA 3.1\n"); - exit(1); - } - while( info->ptx[num_ptx_versions].gpuProfileName != NULL ) { - unsigned capability=0; - sscanf(info->ptx[num_ptx_versions].gpuProfileName,"compute_%u",&capability); - printf("GPGPU-Sim PTX: __cudaRegisterFatBinary found PTX versions for '%s', ", info->ident); - printf("capability = %s\n", info->ptx[num_ptx_versions].gpuProfileName ); - if( forced_max_capability ) { - if( capability > max_capability && capability <= forced_max_capability ) { - found = true; - max_capability=capability; - selected_capability = num_ptx_versions; - } - } else { - if( capability > max_capability ) { - found = true; - max_capability=capability; - selected_capability = num_ptx_versions; - } - } - num_ptx_versions++; - } - if( found ) { - printf("GPGPU-Sim PTX: Loading PTX for %s, capability = %s\n", - info->ident, info->ptx[selected_capability].gpuProfileName ); - symbol_table *symtab; - const char *ptx = info->ptx[selected_capability].ptx; - if(context->get_device()->get_gpgpu()->get_config().convert_to_ptxplus() ) { - printf("GPGPU-Sim PTX: ERROR ** PTXPlus is only supported through cuobjdump\n" - "\tEither enable cuobjdump or disable PTXPlus in your configuration file\n"); - exit(1); - } else { - symtab=gpgpu_ptx_sim_load_ptx_from_string(ptx,source_num); - context->add_binary(symtab,fat_cubin_handle); - gpgpu_ptxinfo_load_from_string( ptx, source_num, max_capability ); - } - source_num++; - load_static_globals(symtab,STATIC_ALLOC_LIMIT,0xFFFFFFFF,context->get_device()->get_gpgpu()); - load_constants(symtab,STATIC_ALLOC_LIMIT,context->get_device()->get_gpgpu()); - } else { - printf("GPGPU-Sim PTX: warning -- did not find an appropriate PTX in cubin\n"); - } - return (void**)fat_cubin_handle; - } -#else - else { - printf("ERROR ** __cudaRegisterFatBinary() needs to be updated\n"); - abort(); - } -#endif +CUresult CUDAAPI cuMemcpyDtoD(CUdeviceptr dstDevice, CUdeviceptr srcDevice, + size_t ByteCount) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -void __cudaUnregisterFatBinary(void **fatCubinHandle) -{ - ; +CUresult CUDAAPI cuMemcpyDtoA(CUarray dstArray, size_t dstOffset, + CUdeviceptr srcDevice, size_t ByteCount) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -cudaError_t cudaDeviceReset ( void ) { - // Should reset the simulated GPU - return g_last_cudaError = cudaSuccess; +CUresult CUDAAPI cuMemcpyAtoD(CUdeviceptr dstDevice, CUarray srcArray, + size_t srcOffset, size_t ByteCount) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -cudaError_t CUDARTAPI cudaDeviceSynchronize(void){ - // I don't know what this should do - return g_last_cudaError = cudaSuccess; + +CUresult CUDAAPI cuMemcpyHtoA(CUarray dstArray, size_t dstOffset, + const void *srcHost, size_t ByteCount) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } +CUresult CUDAAPI cuMemcpyAtoH(void *dstHost, CUarray srcArray, size_t srcOffset, + size_t ByteCount) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} -void CUDARTAPI __cudaRegisterFunction( - void **fatCubinHandle, - const char *hostFun, - char *deviceFun, - const char *deviceName, - int thread_limit, - uint3 *tid, - uint3 *bid, - dim3 *bDim, - dim3 *gDim -) -{ - CUctx_st *context = GPGPUSim_Context(); - unsigned fat_cubin_handle = (unsigned)(unsigned long long)fatCubinHandle; - printf("GPGPU-Sim PTX: __cudaRegisterFunction %s : hostFun 0x%p, fat_cubin_handle = %u\n", - deviceFun, hostFun, fat_cubin_handle); - if(context->get_device()->get_gpgpu()->get_config().use_cuobjdump()) - cuobjdumpParseBinary(fat_cubin_handle); - context->register_function( fat_cubin_handle, hostFun, deviceFun ); +CUresult CUDAAPI cuMemcpyAtoA(CUarray dstArray, size_t dstOffset, + CUarray srcArray, size_t srcOffset, + size_t ByteCount) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -extern void __cudaRegisterVar( - void **fatCubinHandle, - char *hostVar, //pointer to...something - char *deviceAddress, //name of variable - const char *deviceName, //name of variable (same as above) - int ext, - int size, - int constant, - int global ) -{ - printf("GPGPU-Sim PTX: __cudaRegisterVar: hostVar = %p; deviceAddress = %s; deviceName = %s\n", hostVar, deviceAddress, deviceName); - printf("GPGPU-Sim PTX: __cudaRegisterVar: Registering const memory space of %d bytes\n", size); - if(GPGPUSim_Context()->get_device()->get_gpgpu()->get_config().use_cuobjdump()) - cuobjdumpParseBinary((unsigned)(unsigned long long)fatCubinHandle); - fflush(stdout); - if ( constant && !global && !ext ) { - gpgpu_ptx_sim_register_const_variable(hostVar,deviceName,size); - } else if ( !constant && !global && !ext ) { - gpgpu_ptx_sim_register_global_variable(hostVar,deviceName,size); - } else cuda_not_implemented(__my_func__,__LINE__); +CUresult CUDAAPI cuMemcpy2D(const CUDA_MEMCPY2D *pCopy) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } +CUresult CUDAAPI cuMemcpy2DUnaligned(const CUDA_MEMCPY2D *pCopy) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} -void __cudaRegisterShared( - void **fatCubinHandle, - void **devicePtr -) -{ - // we don't do anything here - printf("GPGPU-Sim PTX: __cudaRegisterShared\n" ); +CUresult CUDAAPI cuMemcpy3D(const CUDA_MEMCPY3D *pCopy) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } +#endif /* CUDART_VERSION >= 3020 */ -void CUDARTAPI __cudaRegisterSharedVar( - void **fatCubinHandle, - void **devicePtr, - size_t size, - size_t alignment, - int storage -) -{ - // we don't do anything here - printf("GPGPU-Sim PTX: __cudaRegisterSharedVar\n" ); +#if CUDART_VERSION >= 4000 +CUresult CUDAAPI cuMemcpy3DPeer(const CUDA_MEMCPY3D_PEER *pCopy) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -void __cudaRegisterTexture( - void **fatCubinHandle, - const struct textureReference *hostVar, - const void **deviceAddress, - const char *deviceName, - int dim, - int norm, - int ext -) //passes in a newly created textureReference -{ - std::string devStr (deviceName); - #if (CUDART_VERSION > 4020) - if (devStr.size() > 2 && devStr.data()[0] == ':' && devStr.data()[1] == ':') - devStr = devStr.replace(0, 2, ""); - #endif - CUctx_st *context = GPGPUSim_Context(); - gpgpu_t *gpu = context->get_device()->get_gpgpu(); - printf("GPGPU-Sim PTX: in __cudaRegisterTexture:\n"); - gpu->gpgpu_ptx_sim_bindNameToTexture(devStr.data(), hostVar, dim, norm, ext); - printf("GPGPU-Sim PTX: int dim = %d\n", dim); - printf("GPGPU-Sim PTX: int norm = %d\n", norm); - printf("GPGPU-Sim PTX: int ext = %d\n", ext); - printf("GPGPU-Sim PTX: Execution warning: Not finished implementing \"%s\"\n", __my_func__ ); +CUresult CUDAAPI cuMemcpyAsync(CUdeviceptr dst, CUdeviceptr src, + size_t ByteCount, CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -#ifndef OPENGL_SUPPORT -typedef unsigned long GLuint; -#endif +CUresult CUDAAPI cuMemcpyPeerAsync(CUdeviceptr dstDevice, CUcontext dstContext, + CUdeviceptr srcDevice, CUcontext srcContext, + size_t ByteCount, CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +#endif /* CUDART_VERSION >= 4000 */ -cudaError_t cudaGLRegisterBufferObject(GLuint bufferObj) -{ - printf("GPGPU-Sim PTX: Execution warning: ignoring call to \"%s\"\n", __my_func__ ); - return g_last_cudaError = cudaSuccess; +#if CUDART_VERSION >= 3020 +CUresult CUDAAPI cuMemcpyHtoDAsync(CUdeviceptr dstDevice, const void *srcHost, + size_t ByteCount, CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -struct glbmap_entry { - GLuint m_bufferObj; - void *m_devPtr; - size_t m_size; - struct glbmap_entry *m_next; -}; -typedef struct glbmap_entry glbmap_entry_t; +CUresult CUDAAPI cuMemcpyDtoHAsync(void *dstHost, CUdeviceptr srcDevice, + size_t ByteCount, CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} -glbmap_entry_t* g_glbmap = NULL; +CUresult CUDAAPI cuMemcpyDtoDAsync(CUdeviceptr dstDevice, CUdeviceptr srcDevice, + size_t ByteCount, CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} -cudaError_t cudaGLMapBufferObject(void** devPtr, GLuint bufferObj) -{ -#ifdef OPENGL_SUPPORT - GLint buffer_size=0; - CUctx_st* ctx = GPGPUSim_Context(); +CUresult CUDAAPI cuMemcpyHtoAAsync(CUarray dstArray, size_t dstOffset, + const void *srcHost, size_t ByteCount, + CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} - glbmap_entry_t *p = g_glbmap; - while ( p && p->m_bufferObj != bufferObj ) - p = p->m_next; - if ( p == NULL ) { - glBindBuffer(GL_ARRAY_BUFFER,bufferObj); - glGetBufferParameteriv(GL_ARRAY_BUFFER,GL_BUFFER_SIZE,&buffer_size); - assert( buffer_size != 0 ); - *devPtr = ctx->get_device()->get_gpgpu()->gpu_malloc(buffer_size); +CUresult CUDAAPI cuMemcpyAtoHAsync(void *dstHost, CUarray srcArray, + size_t srcOffset, size_t ByteCount, + CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} - // create entry and insert to front of list - glbmap_entry_t *n = (glbmap_entry_t *) calloc(1,sizeof(glbmap_entry_t)); - n->m_next = g_glbmap; - g_glbmap = n; +CUresult CUDAAPI cuMemcpy2DAsync(const CUDA_MEMCPY2D *pCopy, CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} - // initialize entry - n->m_bufferObj = bufferObj; - n->m_devPtr = *devPtr; - n->m_size = buffer_size; +CUresult CUDAAPI cuMemcpy3DAsync(const CUDA_MEMCPY3D *pCopy, CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +#endif /* CUDART_VERSION >= 3020 */ - p = n; - } else { - buffer_size = p->m_size; - *devPtr = p->m_devPtr; - } +#if CUDART_VERSION >= 4000 +CUresult CUDAAPI cuMemcpy3DPeerAsync(const CUDA_MEMCPY3D_PEER *pCopy, + CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +#endif /* CUDART_VERSION >= 4000 */ - if ( *devPtr ) { - char *data = (char *) calloc(p->m_size,1); - glGetBufferSubData(GL_ARRAY_BUFFER,0,buffer_size,data); - memcpy_to_gpu( (size_t) *devPtr, data, buffer_size ); - free(data); - printf("GPGPU-Sim PTX: cudaGLMapBufferObject %zu bytes starting at 0x%llx..\n", (size_t)buffer_size, - (unsigned long long) *devPtr); - return g_last_cudaError = cudaSuccess; - } else { - return g_last_cudaError = cudaErrorMemoryAllocation; - } +#if CUDART_VERSION >= 3020 +CUresult CUDAAPI cuMemsetD8(CUdeviceptr dstDevice, unsigned char uc, size_t N) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} - return g_last_cudaError = cudaSuccess; -#else - fflush(stdout); - fflush(stderr); - printf("GPGPU-Sim PTX: GPGPU-Sim support for OpenGL integration disabled -- exiting\n"); - fflush(stdout); - exit(50); -#endif +CUresult CUDAAPI cuMemsetD16(CUdeviceptr dstDevice, unsigned short us, + size_t N) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -cudaError_t cudaGLUnmapBufferObject(GLuint bufferObj) -{ -#ifdef OPENGL_SUPPORT - glbmap_entry_t *p = g_glbmap; - while ( p && p->m_bufferObj != bufferObj ) - p = p->m_next; - if ( p == NULL ) - return g_last_cudaError = cudaErrorUnknown; +CUresult CUDAAPI cuMemsetD32(CUdeviceptr dstDevice, unsigned int ui, size_t N) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} - char *data = (char *) calloc(p->m_size,1); - memcpy_from_gpu( data,(size_t)p->m_devPtr,p->m_size ); - glBufferSubData(GL_ARRAY_BUFFER,0,p->m_size,data); - free(data); +CUresult CUDAAPI cuMemsetD2D8(CUdeviceptr dstDevice, size_t dstPitch, + unsigned char uc, size_t Width, size_t Height) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} - return g_last_cudaError = cudaSuccess; -#else - fflush(stdout); - fflush(stderr); - printf("GPGPU-Sim PTX: support for OpenGL integration disabled -- exiting\n"); - fflush(stdout); - exit(50); -#endif +CUresult CUDAAPI cuMemsetD2D16(CUdeviceptr dstDevice, size_t dstPitch, + unsigned short us, size_t Width, size_t Height) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -cudaError_t cudaGLUnregisterBufferObject(GLuint bufferObj) -{ - printf("GPGPU-Sim PTX: Execution warning: ignoring call to \"%s\"\n", __my_func__ ); - return g_last_cudaError = cudaSuccess; +CUresult CUDAAPI cuMemsetD2D32(CUdeviceptr dstDevice, size_t dstPitch, + unsigned int ui, size_t Width, size_t Height) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -#if (CUDART_VERSION >= 2010) +CUresult CUDAAPI cuMemsetD8Async(CUdeviceptr dstDevice, unsigned char uc, + size_t N, CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} -cudaError_t CUDARTAPI cudaHostAlloc(void **pHost, size_t bytes, unsigned int flags) -{ - *pHost = malloc(bytes); - if( *pHost ) - return g_last_cudaError = cudaSuccess; - else - return g_last_cudaError = cudaErrorMemoryAllocation; +CUresult CUDAAPI cuMemsetD16Async(CUdeviceptr dstDevice, unsigned short us, + size_t N, CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -cudaError_t CUDARTAPI cudaHostGetDevicePointer(void **pDevice, void *pHost, unsigned int flags) -{ - cuda_not_implemented(__my_func__,__LINE__); - return g_last_cudaError = cudaErrorUnknown; +CUresult CUDAAPI cuMemsetD32Async(CUdeviceptr dstDevice, unsigned int ui, + size_t N, CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -cudaError_t CUDARTAPI cudaSetValidDevices(int *device_arr, int len) -{ - cuda_not_implemented(__my_func__,__LINE__); - return g_last_cudaError = cudaErrorUnknown; +CUresult CUDAAPI cuMemsetD2D8Async(CUdeviceptr dstDevice, size_t dstPitch, + unsigned char uc, size_t Width, + size_t Height, CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -cudaError_t CUDARTAPI cudaSetDeviceFlags( int flags ) -{ - cuda_not_implemented(__my_func__,__LINE__); - return g_last_cudaError = cudaErrorUnknown; +CUresult CUDAAPI cuMemsetD2D16Async(CUdeviceptr dstDevice, size_t dstPitch, + unsigned short us, size_t Width, + size_t Height, CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -cudaError_t CUDARTAPI cudaFuncGetAttributes(struct cudaFuncAttributes *attr, const char *hostFun ) -{ - CUctx_st *context = GPGPUSim_Context(); - function_info *entry = context->get_kernel(hostFun); - if( entry ) { - const struct gpgpu_ptx_sim_info *kinfo = entry->get_kernel_info(); - attr->sharedSizeBytes = kinfo->smem; - attr->constSizeBytes = kinfo->cmem; - attr->localSizeBytes = kinfo->lmem; - attr->numRegs = kinfo->regs; - attr->maxThreadsPerBlock = 0; // from pragmas? -#if CUDART_VERSION >= 3000 - attr->ptxVersion = kinfo->ptx_version; - attr->binaryVersion = kinfo->sm_target; -#endif - } - return g_last_cudaError = cudaSuccess; +CUresult CUDAAPI cuMemsetD2D32Async(CUdeviceptr dstDevice, size_t dstPitch, + unsigned int ui, size_t Width, + size_t Height, CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -cudaError_t CUDARTAPI cudaEventCreateWithFlags(cudaEvent_t *event, int flags) -{ - CUevent_st *e = new CUevent_st(flags==cudaEventBlockingSync); - g_timer_events[e->get_uid()] = e; -#if CUDART_VERSION >= 3000 - *event = e; -#else - *event = e->get_uid(); -#endif - return g_last_cudaError = cudaSuccess; +CUresult CUDAAPI cuArrayCreate(CUarray *pHandle, + const CUDA_ARRAY_DESCRIPTOR *pAllocateArray) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -cudaError_t CUDARTAPI cudaDriverGetVersion(int *driverVersion) -{ - *driverVersion = CUDART_VERSION; - return g_last_cudaError = cudaErrorUnknown; +CUresult CUDAAPI cuArrayGetDescriptor(CUDA_ARRAY_DESCRIPTOR *pArrayDescriptor, + CUarray hArray) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } +#endif /* CUDART_VERSION >= 3020 */ -cudaError_t CUDARTAPI cudaRuntimeGetVersion(int *runtimeVersion) -{ - *runtimeVersion = CUDART_VERSION; - return g_last_cudaError = cudaErrorUnknown; +CUresult CUDAAPI cuArrayDestroy(CUarray hArray) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -#if CUDART_VERSION >= 3000 -__host__ cudaError_t CUDARTAPI cudaFuncSetCacheConfig(const char *func, enum cudaFuncCache cacheConfig ) -{ - CUctx_st *context = GPGPUSim_Context(); - context->get_device()->get_gpgpu()->set_cache_config(context->get_kernel(func)->get_name(), (FuncCache)cacheConfig); - return g_last_cudaError = cudaSuccess; +#if CUDART_VERSION >= 3020 +CUresult CUDAAPI cuArray3DCreate( + CUarray *pHandle, const CUDA_ARRAY3D_DESCRIPTOR *pAllocateArray) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -//Jin: hack for cdp -__host__ cudaError_t CUDARTAPI cudaDeviceSetLimit(enum cudaLimit limit, size_t value) { - return g_last_cudaError = cudaSuccess; +CUresult CUDAAPI cuArray3DGetDescriptor( + CUDA_ARRAY3D_DESCRIPTOR *pArrayDescriptor, CUarray hArray) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -#endif +#endif /* CUDART_VERSION >= 3020 */ + +#if CUDART_VERSION >= 5000 + +CUresult CUDAAPI +cuMipmappedArrayCreate(CUmipmappedArray *pHandle, + const CUDA_ARRAY3D_DESCRIPTOR *pMipmappedArrayDesc, + unsigned int numMipmapLevels) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuMipmappedArrayGetLevel(CUarray *pLevelArray, + CUmipmappedArray hMipmappedArray, + unsigned int level) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuMipmappedArrayDestroy(CUmipmappedArray hMipmappedArray) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +#endif /* CUDART_VERSION >= 5000 */ + +/** @} */ /* END CUDA_MEM */ + +#if CUDART_VERSION >= 4000 +CUresult CUDAAPI cuPointerGetAttribute(void *data, + CUpointer_attribute attribute, + CUdeviceptr ptr) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +#endif /* CUDART_VERSION >= 4000 */ + +#if CUDART_VERSION >= 8000 +__host__ cudaError_t CUDARTAPI cudaCreateTextureObject( + cudaTextureObject_t *pTexObject, const cudaResourceDesc *pResDesc, + const cudaTextureDesc *pTexDesc, const cudaResourceViewDesc *pResViewDesc) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + cuda_not_implemented(__my_func__, __LINE__); + return g_last_cudaError = cudaSuccess; +} + +CUresult CUDAAPI cuMemPrefetchAsync(CUdeviceptr devPtr, size_t count, + CUdevice dstDevice, CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuMemAdvise(CUdeviceptr devPtr, size_t count, + CUmem_advise advice, CUdevice device) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuMemRangeGetAttribute(void *data, size_t dataSize, + CUmem_range_attribute attribute, + CUdeviceptr devPtr, size_t count) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuMemRangeGetAttributes(void **data, size_t *dataSizes, + CUmem_range_attribute *attributes, + size_t numAttributes, + CUdeviceptr devPtr, size_t count) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +#endif /* CUDART_VERSION >= 8000 */ + +#if CUDART_VERSION >= 6000 +CUresult CUDAAPI cuPointerSetAttribute(const void *value, + CUpointer_attribute attribute, + CUdeviceptr ptr) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +#endif /* CUDART_VERSION >= 6000 */ + +#if CUDART_VERSION >= 7000 +CUresult CUDAAPI cuPointerGetAttributes(unsigned int numAttributes, + CUpointer_attribute *attributes, + void **data, CUdeviceptr ptr) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +#endif /* CUDART_VERSION >= 7000 */ + +/** @} */ /* END CUDA_UNIFIED */ + +CUresult CUDAAPI cuStreamCreate(CUstream *phStream, unsigned int Flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuStreamCreateWithPriority(CUstream *phStream, + unsigned int flags, int priority) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuStreamGetPriority(CUstream hStream, int *priority) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuStreamGetFlags(CUstream hStream, unsigned int *flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuStreamWaitEvent(CUstream hStream, CUevent hEvent, + unsigned int Flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuStreamAddCallback(CUstream hStream, + CUstreamCallback callback, void *userData, + unsigned int flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +#if CUDART_VERSION >= 6000 + +CUresult CUDAAPI cuStreamAttachMemAsync(CUstream hStream, CUdeviceptr dptr, + size_t length, unsigned int flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +#endif /* CUDART_VERSION >= 6000 */ + +CUresult CUDAAPI cuStreamQuery(CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuStreamSynchronize(CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +#if CUDART_VERSION >= 4000 +CUresult CUDAAPI cuStreamDestroy(CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +#endif /* CUDART_VERSION >= 4000 */ + +/** @} */ /* END CUDA_STREAM */ + +CUresult CUDAAPI cuEventCreate(CUevent *phEvent, unsigned int Flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuEventRecord(CUevent hEvent, CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuEventQuery(CUevent hEvent) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuEventSynchronize(CUevent hEvent) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +#if CUDART_VERSION >= 4000 +CUresult CUDAAPI cuEventDestroy(CUevent hEvent) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +#endif /* CUDART_VERSION >= 4000 */ + +CUresult CUDAAPI cuEventElapsedTime(float *pMilliseconds, CUevent hStart, + CUevent hEnd) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +#if CUDART_VERSION >= 8000 +CUresult CUDAAPI cuStreamWaitValue32(CUstream stream, CUdeviceptr addr, + cuuint32_t value, unsigned int flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuStreamWriteValue32(CUstream stream, CUdeviceptr addr, + cuuint32_t value, unsigned int flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuStreamBatchMemOp(CUstream stream, unsigned int count, + CUstreamBatchMemOpParams *paramArray, + unsigned int flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +#endif /* CUDART_VERSION >= 8000 */ +/** @} */ /* END CUDA_EVENT */ + +CUresult CUDAAPI cuFuncGetAttribute(int *pi, CUfunction_attribute attrib, + CUfunction hfunc) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuFuncSetCacheConfig(CUfunction hfunc, CUfunc_cache config) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +#if CUDART_VERSION >= 4020 +CUresult CUDAAPI cuFuncSetSharedMemConfig(CUfunction hfunc, + CUsharedconfig config) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} #endif -cudaError_t CUDARTAPI cudaGLSetGLDevice(int device) -{ - printf("GPGPU-Sim PTX: Execution warning: ignoring call to \"%s\"\n", __my_func__ ); - return g_last_cudaError = cudaErrorUnknown; +#if CUDART_VERSION >= 4000 +CUresult CUDAAPI cuLaunchKernel(CUfunction f, unsigned int gridDimX, + unsigned int gridDimY, unsigned int gridDimZ, + unsigned int blockDimX, unsigned int blockDimY, + unsigned int blockDimZ, + unsigned int sharedMemBytes, CUstream hStream, + void **kernelParams, void **extra) { + return cuLaunchKernelInternal(f, gridDimX, gridDimY, gridDimZ, blockDimX, + blockDimY, blockDimZ, sharedMemBytes, hStream, + kernelParams, extra); } +#endif /* CUDART_VERSION >= 4000 */ -typedef void* HGPUNV; +/** @} */ /* END CUDA_EXEC */ -cudaError_t CUDARTAPI cudaWGLGetDevice(int *device, HGPUNV hGpu) -{ - cuda_not_implemented(__my_func__,__LINE__); - return g_last_cudaError = cudaErrorUnknown; +CUresult CUDAAPI cuFuncSetBlockShape(CUfunction hfunc, int x, int y, int z) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -void CUDARTAPI __cudaMutexOperation(int lock) -{ - cuda_not_implemented(__my_func__,__LINE__); +CUresult CUDAAPI cuFuncSetSharedSize(CUfunction hfunc, unsigned int bytes) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -void CUDARTAPI __cudaTextureFetch(const void *tex, void *index, int integer, void *val) -{ - cuda_not_implemented(__my_func__,__LINE__); +CUresult CUDAAPI cuParamSetSize(CUfunction hfunc, unsigned int numbytes) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } +CUresult CUDAAPI cuParamSeti(CUfunction hfunc, int offset, unsigned int value) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -namespace cuda_math { +CUresult CUDAAPI cuParamSetf(CUfunction hfunc, int offset, float value) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} -void CUDARTAPI __cudaMutexOperation(int lock) -{ - cuda_not_implemented(__my_func__,__LINE__); +CUresult CUDAAPI cuParamSetv(CUfunction hfunc, int offset, void *ptr, + unsigned int numbytes) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -void CUDARTAPI __cudaTextureFetch(const void *tex, void *index, int integer, void *val) -{ - cuda_not_implemented(__my_func__,__LINE__); +CUresult CUDAAPI cuLaunch(CUfunction f) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -int CUDARTAPI __cudaSynchronizeThreads(void**, void*) -{ - //TODO This function should syncronize if we support Asyn kernel calls - return g_last_cudaError = cudaSuccess; +CUresult CUDAAPI cuLaunchGrid(CUfunction f, int grid_width, int grid_height) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } +CUresult CUDAAPI cuLaunchGridAsync(CUfunction f, int grid_width, + int grid_height, CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -//////// +CUresult CUDAAPI cuParamSetTexRef(CUfunction hfunc, int texunit, + CUtexref hTexRef) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +/** @} */ /* END CUDA_EXEC_DEPRECATED */ -extern int ptx_parse(); -extern int ptx__scan_string(const char*); -extern FILE *ptx_in; +#if CUDART_VERSION >= 6050 -extern int ptxinfo_parse(); -extern int ptxinfo_debug; -extern FILE *ptxinfo_in; +CUresult CUDAAPI cuOccupancyMaxActiveBlocksPerMultiprocessor( + int *numBlocks, CUfunction func, int blockSize, size_t dynamicSMemSize) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} -/// static functions +CUresult CUDAAPI cuOccupancyMaxActiveBlocksPerMultiprocessorWithFlags( + int *numBlocks, CUfunction func, int blockSize, size_t dynamicSMemSize, + unsigned int flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} -static int load_static_globals( symbol_table *symtab, unsigned min_gaddr, unsigned max_gaddr, gpgpu_t *gpu ) -{ - printf( "GPGPU-Sim PTX: loading globals with explicit initializers... \n" ); - fflush(stdout); - int ng_bytes=0; - symbol_table::iterator g=symtab->global_iterator_begin(); +CUresult CUDAAPI cuOccupancyMaxPotentialBlockSize( + int *minGridSize, int *blockSize, CUfunction func, + CUoccupancyB2DSize blockSizeToDynamicSMemSize, size_t dynamicSMemSize, + int blockSizeLimit) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} - for ( ; g!=symtab->global_iterator_end(); g++) { - symbol *global = *g; - if ( global->has_initializer() ) { - printf( "GPGPU-Sim PTX: initializing '%s' ... ", global->name().c_str() ); - unsigned addr=global->get_address(); - const type_info *type = global->type(); - type_info_key ti=type->get_key(); - size_t size; - int t; - ti.type_decode(size,t); - int nbytes = size/8; - int offset=0; - std::list<operand_info> init_list = global->get_initializer(); - for ( std::list<operand_info>::iterator i=init_list.begin(); i!=init_list.end(); i++ ) { - operand_info op = *i; - ptx_reg_t value = op.get_literal_value(); - assert( (addr+offset+nbytes) < min_gaddr ); // min_gaddr is start of "heap" for cudaMalloc - gpu->get_global_memory()->write(addr+offset,nbytes,&value,NULL,NULL); // assuming little endian here - offset+=nbytes; - ng_bytes+=nbytes; - } - printf(" wrote %u bytes\n", offset ); - } - } - printf( "GPGPU-Sim PTX: finished loading globals (%u bytes total).\n", ng_bytes ); - fflush(stdout); - return ng_bytes; +CUresult CUDAAPI cuOccupancyMaxPotentialBlockSizeWithFlags( + int *minGridSize, int *blockSize, CUfunction func, + CUoccupancyB2DSize blockSizeToDynamicSMemSize, size_t dynamicSMemSize, + int blockSizeLimit, unsigned int flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } -static int load_constants( symbol_table *symtab, addr_t min_gaddr, gpgpu_t *gpu ) -{ - printf( "GPGPU-Sim PTX: loading constants with explicit initializers... " ); - fflush(stdout); - int nc_bytes = 0; - symbol_table::iterator g=symtab->const_iterator_begin(); +/** @} */ /* END CUDA_OCCUPANCY */ +#endif /* CUDART_VERSION >= 6050 */ - for ( ; g!=symtab->const_iterator_end(); g++) { - symbol *constant = *g; - if ( constant->is_const() && constant->has_initializer() ) { +CUresult CUDAAPI cuTexRefSetArray(CUtexref hTexRef, CUarray hArray, + unsigned int Flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} - // get the constant element data size - int basic_type; - size_t num_bits; - constant->type()->get_key().type_decode(num_bits,basic_type); +CUresult CUDAAPI cuTexRefSetMipmappedArray(CUtexref hTexRef, + CUmipmappedArray hMipmappedArray, + unsigned int Flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} - std::list<operand_info> init_list = constant->get_initializer(); - int nbytes_written = 0; - for ( std::list<operand_info>::iterator i=init_list.begin(); i!=init_list.end(); i++ ) { - operand_info op = *i; - ptx_reg_t value = op.get_literal_value(); - int nbytes = num_bits/8; - switch ( op.get_type() ) { - case int_t: assert(nbytes >= 1); break; - case float_op_t: assert(nbytes == 4); break; - case double_op_t: assert(nbytes >= 4); break; // account for double DEMOTING - default: - abort(); - } - unsigned addr=constant->get_address() + nbytes_written; - assert( addr+nbytes < min_gaddr ); +#if CUDART_VERSION >= 3020 +CUresult CUDAAPI cuTexRefSetAddress(size_t *ByteOffset, CUtexref hTexRef, + CUdeviceptr dptr, size_t bytes) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} - gpu->get_global_memory()->write(addr,nbytes,&value,NULL,NULL); // assume little endian (so u8 is the first byte in u32) - nc_bytes+=nbytes; - nbytes_written += nbytes; - } - } - } - printf( " done.\n"); - fflush(stdout); - return nc_bytes; +CUresult CUDAAPI cuTexRefSetAddress2D(CUtexref hTexRef, + const CUDA_ARRAY_DESCRIPTOR *desc, + CUdeviceptr dptr, size_t Pitch) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } +#endif /* CUDART_VERSION >= 3020 */ -kernel_info_t *gpgpu_cuda_ptx_sim_init_grid( const char *hostFun, - gpgpu_ptx_sim_arg_list_t args, - struct dim3 gridDim, - struct dim3 blockDim, - CUctx_st* context ) -{ - function_info *entry = context->get_kernel(hostFun); - kernel_info_t *result = new kernel_info_t(gridDim,blockDim,entry); - if( entry == NULL ) { - printf("GPGPU-Sim PTX: ERROR launching kernel -- no PTX implementation found for %p\n", hostFun); - abort(); - } - unsigned argcount=args.size(); - unsigned argn=1; - for( gpgpu_ptx_sim_arg_list_t::iterator a = args.begin(); a != args.end(); a++ ) { - entry->add_param_data(argcount-argn,&(*a)); - argn++; - } +CUresult CUDAAPI cuTexRefSetFormat(CUtexref hTexRef, CUarray_format fmt, + int NumPackedComponents) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuTexRefSetAddressMode(CUtexref hTexRef, int dim, + CUaddress_mode am) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuTexRefSetFilterMode(CUtexref hTexRef, CUfilter_mode fm) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuTexRefSetMipmapFilterMode(CUtexref hTexRef, + CUfilter_mode fm) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuTexRefSetMipmapLevelBias(CUtexref hTexRef, float bias) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuTexRefSetMipmapLevelClamp(CUtexref hTexRef, + float minMipmapLevelClamp, + float maxMipmapLevelClamp) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuTexRefSetMaxAnisotropy(CUtexref hTexRef, + unsigned int maxAniso) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuTexRefSetBorderColor(CUtexref hTexRef, float *pBorderColor) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuTexRefSetFlags(CUtexref hTexRef, unsigned int Flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +#if CUDART_VERSION >= 3020 +CUresult CUDAAPI cuTexRefGetAddress(CUdeviceptr *pdptr, CUtexref hTexRef) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +#endif /* CUDART_VERSION >= 3020 */ + +CUresult CUDAAPI cuTexRefGetArray(CUarray *phArray, CUtexref hTexRef) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuTexRefGetMipmappedArray(CUmipmappedArray *phMipmappedArray, + CUtexref hTexRef) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuTexRefGetAddressMode(CUaddress_mode *pam, CUtexref hTexRef, + int dim) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuTexRefGetFilterMode(CUfilter_mode *pfm, CUtexref hTexRef) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuTexRefGetFormat(CUarray_format *pFormat, int *pNumChannels, + CUtexref hTexRef) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuTexRefGetMipmapFilterMode(CUfilter_mode *pfm, + CUtexref hTexRef) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuTexRefGetMipmapLevelBias(float *pbias, CUtexref hTexRef) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuTexRefGetMipmapLevelClamp(float *pminMipmapLevelClamp, + float *pmaxMipmapLevelClamp, + CUtexref hTexRef) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuTexRefGetMaxAnisotropy(int *pmaxAniso, CUtexref hTexRef) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuTexRefGetBorderColor(float *pBorderColor, CUtexref hTexRef) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuTexRefGetFlags(unsigned int *pFlags, CUtexref hTexRef) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuTexRefCreate(CUtexref *pTexRef) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuTexRefDestroy(CUtexref hTexRef) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuSurfRefSetArray(CUsurfref hSurfRef, CUarray hArray, + unsigned int Flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuSurfRefGetArray(CUarray *phArray, CUsurfref hSurfRef) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +/** @} */ /* END CUDA_SURFREF */ + +#if CUDART_VERSION >= 5000 +CUresult CUDAAPI +cuTexObjectCreate(CUtexObject *pTexObject, const CUDA_RESOURCE_DESC *pResDesc, + const CUDA_TEXTURE_DESC *pTexDesc, + const CUDA_RESOURCE_VIEW_DESC *pResViewDesc) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuTexObjectDestroy(CUtexObject texObject) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuTexObjectGetResourceDesc(CUDA_RESOURCE_DESC *pResDesc, + CUtexObject texObject) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuTexObjectGetTextureDesc(CUDA_TEXTURE_DESC *pTexDesc, + CUtexObject texObject) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuTexObjectGetResourceViewDesc( + CUDA_RESOURCE_VIEW_DESC *pResViewDesc, CUtexObject texObject) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +/** @} */ /* END CUDA_TEXOBJECT */ + +CUresult CUDAAPI cuSurfObjectCreate(CUsurfObject *pSurfObject, + const CUDA_RESOURCE_DESC *pResDesc) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuSurfObjectDestroy(CUsurfObject surfObject) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuSurfObjectGetResourceDesc(CUDA_RESOURCE_DESC *pResDesc, + CUsurfObject surfObject) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +#endif /* CUDART_VERSION >= 5000 */ + +#if CUDART_VERSION >= 4000 +CUresult CUDAAPI cuDeviceCanAccessPeer(int *canAccessPeer, CUdevice dev, + CUdevice peerDev) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuDeviceGetP2PAttribute(int *value, + CUdevice_P2PAttribute attrib, + CUdevice srcDevice, + CUdevice dstDevice) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuCtxEnablePeerAccess(CUcontext peerContext, + unsigned int Flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuCtxDisablePeerAccess(CUcontext peerContext) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +/** @} */ /* END CUDA_PEER_ACCESS */ +#endif /* CUDART_VERSION >= 4000 */ + +CUresult CUDAAPI cuGraphicsUnregisterResource(CUgraphicsResource resource) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuGraphicsSubResourceGetMappedArray( + CUarray *pArray, CUgraphicsResource resource, unsigned int arrayIndex, + unsigned int mipLevel) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +#if CUDART_VERSION >= 5000 + +CUresult CUDAAPI cuGraphicsResourceGetMappedMipmappedArray( + CUmipmappedArray *pMipmappedArray, CUgraphicsResource resource) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +#endif /* CUDART_VERSION >= 5000 */ + +#if CUDART_VERSION >= 3020 +CUresult CUDAAPI cuGraphicsResourceGetMappedPointer( + CUdeviceptr *pDevPtr, size_t *pSize, CUgraphicsResource resource) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +#endif /* CUDART_VERSION >= 3020 */ + +CUresult CUDAAPI cuGraphicsResourceSetMapFlags(CUgraphicsResource resource, + unsigned int flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuGraphicsMapResources(unsigned int count, + CUgraphicsResource *resources, + CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuGraphicsUnmapResources(unsigned int count, + CUgraphicsResource *resources, + CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +/** @} */ /* END CUDA_GRAPHICS */ + +CUresult CUDAAPI cuGetExportTable(const void **ppExportTable, + const CUuuid *pExportTableId) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + cudaError_t e = cudaGetExportTable(ppExportTable, pExportTableId); + assert(e == cudaSuccess); + return CUDA_SUCCESS; +} + +#if defined(CUDART_VERSION_INTERNAL) || \ + (CUDART_VERSION >= 4000 && CUDART_VERSION < 6050) +CUresult CUDAAPI cuMemHostRegister(void *p, size_t bytesize, + unsigned int Flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +#endif /* defined(CUDART_VERSION_INTERNAL) || (CUDART_VERSION >= 4000 && \ + CUDART_VERSION < 6050) */ + +#if defined(CUDART_VERSION_INTERNAL) || \ + (CUDART_VERSION >= 5050 && CUDART_VERSION < 6050) +CUresult CUDAAPI cuLinkCreate(unsigned int numOptions, CUjit_option *options, + void **optionValues, CUlinkState *stateOut) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuLinkAddData(CUlinkState state, CUjitInputType type, + void *data, size_t size, const char *name, + unsigned int numOptions, CUjit_option *options, + void **optionValues) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuLinkAddFile(CUlinkState state, CUjitInputType type, + const char *path, unsigned int numOptions, + CUjit_option *options, void **optionValues) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +#endif /* CUDART_VERSION_INTERNAL || (CUDART_VERSION >= 5050 && CUDART_VERSION \ + < 6050) */ + +#if defined(CUDART_VERSION_INTERNAL) || \ + (CUDART_VERSION >= 3020 && CUDART_VERSION < 4010) +CUresult CUDAAPI cuTexRefSetAddress2D_v2(CUtexref hTexRef, + const CUDA_ARRAY_DESCRIPTOR *desc, + CUdeviceptr dptr, size_t Pitch) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +#endif /* CUDART_VERSION_INTERNAL || (CUDART_VERSION >= 3020 && CUDART_VERSION \ + < 4010) */ + +#if defined(CUDART_VERSION_INTERNAL) || CUDART_VERSION < 4000 +CUresult CUDAAPI cuCtxDestroy(CUcontext ctx) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuCtxPopCurrent(CUcontext *pctx) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuCtxPushCurrent(CUcontext ctx) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuStreamDestroy(CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuEventDestroy(CUevent hEvent) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +#endif /* CUDART_VERSION_INTERNAL || CUDART_VERSION < 4000 */ + +#if defined(CUDART_VERSION_INTERNAL) +CUresult CUDAAPI cuMemcpyHtoD_v2(CUdeviceptr dstDevice, const void *srcHost, + size_t ByteCount) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuMemcpyDtoH_v2(void *dstHost, CUdeviceptr srcDevice, + size_t ByteCount) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuMemcpyDtoD_v2(CUdeviceptr dstDevice, CUdeviceptr srcDevice, + size_t ByteCount) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuMemcpyDtoA_v2(CUarray dstArray, size_t dstOffset, + CUdeviceptr srcDevice, size_t ByteCount) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuMemcpyAtoD_v2(CUdeviceptr dstDevice, CUarray srcArray, + size_t srcOffset, size_t ByteCount) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuMemcpyHtoA_v2(CUarray dstArray, size_t dstOffset, + const void *srcHost, size_t ByteCount) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuMemcpyAtoH_v2(void *dstHost, CUarray srcArray, + size_t srcOffset, size_t ByteCount) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuMemcpyAtoA_v2(CUarray dstArray, size_t dstOffset, + CUarray srcArray, size_t srcOffset, + size_t ByteCount) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuMemcpyHtoAAsync_v2(CUarray dstArray, size_t dstOffset, + const void *srcHost, size_t ByteCount, + CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuMemcpyAtoHAsync_v2(void *dstHost, CUarray srcArray, + size_t srcOffset, size_t ByteCount, + CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuMemcpy2D_v2(const CUDA_MEMCPY2D *pCopy) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuMemcpy2DUnaligned_v2(const CUDA_MEMCPY2D *pCopy) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuMemcpy3D_v2(const CUDA_MEMCPY3D *pCopy) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuMemcpyHtoDAsync_v2(CUdeviceptr dstDevice, + const void *srcHost, size_t ByteCount, + CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuMemcpyDtoHAsync_v2(void *dstHost, CUdeviceptr srcDevice, + size_t ByteCount, CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuMemcpyDtoDAsync_v2(CUdeviceptr dstDevice, + CUdeviceptr srcDevice, size_t ByteCount, + CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuMemcpy2DAsync_v2(const CUDA_MEMCPY2D *pCopy, + CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuMemcpy3DAsync_v2(const CUDA_MEMCPY3D *pCopy, + CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuMemsetD8_v2(CUdeviceptr dstDevice, unsigned char uc, + size_t N) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuMemsetD16_v2(CUdeviceptr dstDevice, unsigned short us, + size_t N) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuMemsetD32_v2(CUdeviceptr dstDevice, unsigned int ui, + size_t N) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuMemsetD2D8_v2(CUdeviceptr dstDevice, size_t dstPitch, + unsigned char uc, size_t Width, + size_t Height) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuMemsetD2D16_v2(CUdeviceptr dstDevice, size_t dstPitch, + unsigned short us, size_t Width, + size_t Height) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuMemsetD2D32_v2(CUdeviceptr dstDevice, size_t dstPitch, + unsigned int ui, size_t Width, + size_t Height) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuMemcpy(CUdeviceptr dst, CUdeviceptr src, size_t ByteCount) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuMemcpyAsync(CUdeviceptr dst, CUdeviceptr src, + size_t ByteCount, CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuMemcpyPeer(CUdeviceptr dstDevice, CUcontext dstContext, + CUdeviceptr srcDevice, CUcontext srcContext, + size_t ByteCount) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuMemcpyPeerAsync(CUdeviceptr dstDevice, CUcontext dstContext, + CUdeviceptr srcDevice, CUcontext srcContext, + size_t ByteCount, CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuMemcpy3DPeer(const CUDA_MEMCPY3D_PEER *pCopy) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuMemcpy3DPeerAsync(const CUDA_MEMCPY3D_PEER *pCopy, + CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +CUresult CUDAAPI cuMemsetD8Async(CUdeviceptr dstDevice, unsigned char uc, + size_t N, CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuMemsetD16Async(CUdeviceptr dstDevice, unsigned short us, + size_t N, CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuMemsetD32Async(CUdeviceptr dstDevice, unsigned int ui, + size_t N, CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuMemsetD2D8Async(CUdeviceptr dstDevice, size_t dstPitch, + unsigned char uc, size_t Width, + size_t Height, CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuMemsetD2D16Async(CUdeviceptr dstDevice, size_t dstPitch, + unsigned short us, size_t Width, + size_t Height, CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuMemsetD2D32Async(CUdeviceptr dstDevice, size_t dstPitch, + unsigned int ui, size_t Width, + size_t Height, CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} - entry->finalize(result->get_param_memory()); - g_ptx_kernel_count++; - fflush(stdout); +CUresult CUDAAPI cuStreamGetPriority(CUstream hStream, int *priority) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuStreamGetFlags(CUstream hStream, unsigned int *flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuStreamWaitEvent(CUstream hStream, CUevent hEvent, + unsigned int Flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuStreamAddCallback(CUstream hStream, + CUstreamCallback callback, void *userData, + unsigned int flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuStreamAttachMemAsync(CUstream hStream, CUdeviceptr dptr, + size_t length, unsigned int flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuStreamQuery(CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuStreamSynchronize(CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuEventRecord(CUevent hEvent, CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuLaunchKernel(CUfunction f, unsigned int gridDimX, + unsigned int gridDimY, unsigned int gridDimZ, + unsigned int blockDimX, unsigned int blockDimY, + unsigned int blockDimZ, + unsigned int sharedMemBytes, CUstream hStream, + void **kernelParams, void **extra) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuGraphicsMapResources(unsigned int count, + CUgraphicsResource *resources, + CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuGraphicsUnmapResources(unsigned int count, + CUgraphicsResource *resources, + CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuMemPrefetchAsync(CUdeviceptr devPtr, size_t count, + CUdevice dstDevice, CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuStreamWriteValue32(CUstream stream, CUdeviceptr addr, + cuuint32_t value, unsigned int flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuStreamWaitValue32(CUstream stream, CUdeviceptr addr, + cuuint32_t value, unsigned int flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult CUDAAPI cuStreamBatchMemOp(CUstream stream, unsigned int count, + CUstreamBatchMemOpParams *paramArray, + unsigned int flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +#endif + +CUresult cuProfilerInitialize(const char *configFile, const char *outputFile, + CUoutput_mode outputMode) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult cuProfilerStart(void) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +CUresult cuProfilerStop(void) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +//_ptds + +extern "C" CUresult CUDAAPI cuMemcpy_ptds(CUdeviceptr dst, CUdeviceptr src, + size_t ByteCount) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +extern "C" CUresult CUDAAPI cuMemcpyPeer_ptds(CUdeviceptr dstDevice, + CUcontext dstContext, + CUdeviceptr srcDevice, + CUcontext srcContext, + size_t ByteCount) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +extern "C" CUresult CUDAAPI cuMemcpyHtoD_v2_ptds(CUdeviceptr dstDevice, + const void *srcHost, + size_t ByteCount) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +extern "C" CUresult CUDAAPI cuMemcpyDtoH_v2_ptds(void *dstHost, + CUdeviceptr srcDevice, + size_t ByteCount) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +extern "C" CUresult CUDAAPI cuMemcpyDtoD_v2_ptds(CUdeviceptr dstDevice, + CUdeviceptr srcDevice, + size_t ByteCount) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +extern "C" CUresult CUDAAPI +cuMemcpy2DUnaligned_v2_ptds(const CUDA_MEMCPY2D *pCopy) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +extern "C" CUresult CUDAAPI cuMemcpy3D_v2_ptds(const CUDA_MEMCPY3D *pCopy) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +extern "C" CUresult CUDAAPI +cuMemcpy3DPeer_ptds(const CUDA_MEMCPY3D_PEER *pCopy) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +extern "C" CUresult CUDAAPI cuMemsetD8_v2_ptds(CUdeviceptr dstDevice, + unsigned char uc, + unsigned int N) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +extern "C" CUresult CUDAAPI cuMemsetD16_v2_ptds(CUdeviceptr dstDevice, + unsigned short us, + unsigned int N) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +extern "C" CUresult CUDAAPI cuMemsetD32_v2_ptds(CUdeviceptr dstDevice, + unsigned int ui, + unsigned int N) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +extern "C" CUresult CUDAAPI cuMemsetD2D8_v2_ptds(CUdeviceptr dstDevice, + unsigned int dstPitch, + unsigned char uc, + unsigned int Width, + unsigned int Height) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +extern "C" CUresult CUDAAPI cuMemsetD2D16_v2_ptds(CUdeviceptr dstDevice, + unsigned int dstPitch, + unsigned short us, + unsigned int Width, + unsigned int Height) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +extern "C" CUresult CUDAAPI cuMemsetD2D32_v2_ptds(CUdeviceptr dstDevice, + unsigned int dstPitch, + unsigned int ui, + unsigned int Width, + unsigned int Height) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +//_ptsz +extern "C" CUresult CUDAAPI +cuMemcpy3DPeer_ptsz(const CUDA_MEMCPY3D_PEER *pCopy) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +extern "C" CUresult CUDAAPI cuMemcpyAsync_ptsz(CUdeviceptr dst, CUdeviceptr src, + size_t ByteCount, + CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +extern "C" CUresult CUDAAPI cuMemcpyPeerAsync_ptsz( + CUdeviceptr dstDevice, CUcontext dstContext, CUdeviceptr srcDevice, + CUcontext srcContext, size_t ByteCount, CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +extern "C" CUresult CUDAAPI cuMemcpyHtoAAsync_v2_ptsz(CUarray dstArray, + size_t dstOffset, + const void *srcHost, + size_t ByteCount, + CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +extern "C" CUresult CUDAAPI cuMemcpyAtoHAsync_v2_ptsz(void *dstHost, + CUarray srcArray, + size_t srcOffset, + size_t ByteCount, + CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +extern "C" CUresult CUDAAPI cuMemcpyHtoDAsync_v2_ptsz(CUdeviceptr dstDevice, + const void *srcHost, + size_t ByteCount, + CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +extern "C" CUresult CUDAAPI cuMemcpyDtoHAsync_v2_ptsz(void *dstHost, + CUdeviceptr srcDevice, + size_t ByteCount, + CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +extern "C" CUresult CUDAAPI cuMemcpyDtoDAsync_v2_ptsz(CUdeviceptr dstDevice, + CUdeviceptr srcDevice, + size_t ByteCount, + CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +extern "C" CUresult CUDAAPI cuMemcpy2DAsync_v2_ptsz(const CUDA_MEMCPY2D *pCopy, + CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +extern "C" CUresult CUDAAPI cuMemcpy3DAsync_v2_ptsz(const CUDA_MEMCPY3D *pCopy, + CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +extern "C" CUresult CUDAAPI +cuMemcpy3DPeerAsync_ptsz(const CUDA_MEMCPY3D_PEER *pCopy, CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +extern "C" CUresult CUDAAPI cuMemsetD8Async_ptsz(CUdeviceptr dstDevice, + unsigned char uc, size_t N, + CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +extern "C" CUresult CUDAAPI cuMemsetD2D8Async_ptsz(CUdeviceptr dstDevice, + size_t dstPitch, + unsigned char uc, + size_t Width, size_t Height, + CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +extern "C" CUresult CUDAAPI cuLaunchKernel_ptsz( + CUfunction f, unsigned int gridDimX, unsigned int gridDimY, + unsigned int gridDimZ, unsigned int blockDimX, unsigned int blockDimY, + unsigned int blockDimZ, unsigned int sharedMemBytes, CUstream hStream, + void **kernelParams, void **extra) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +extern "C" CUresult CUDAAPI cuEventRecord_ptsz(CUevent hEvent, + CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +extern "C" CUresult CUDAAPI cuStreamWriteValue32_ptsz(CUstream stream, + CUdeviceptr addr, + cuuint32_t value, + unsigned int flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +extern "C" CUresult CUDAAPI cuStreamWaitValue32_ptsz(CUstream stream, + CUdeviceptr addr, + cuuint32_t value, + unsigned int flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +extern "C" CUresult CUDAAPI cuStreamBatchMemOp_ptsz( + CUstream stream, unsigned int count, CUstreamBatchMemOpParams *paramArray, + unsigned int flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +extern "C" CUresult CUDAAPI cuStreamGetPriority_ptsz(CUstream hStream, + int *priority) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +extern "C" CUresult CUDAAPI cuStreamGetFlags_ptsz(CUstream hStream, + unsigned int *flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +extern "C" CUresult CUDAAPI cuStreamWaitEvent_ptsz(CUstream hStream, + CUevent hEvent, + unsigned int Flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +extern "C" CUresult CUDAAPI cuStreamAddCallback_ptsz(CUstream hStream, + CUstreamCallback callback, + void *userData, + unsigned int flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +extern "C" CUresult CUDAAPI cuStreamSynchronize_ptsz(CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +extern "C" CUresult CUDAAPI cuStreamQuery_ptsz(CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} +extern "C" CUresult CUDAAPI cuStreamAttachMemAsync_ptsz(CUstream hStream, + CUdeviceptr dptr, + size_t length, + unsigned int flags) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +extern "C" CUresult CUDAAPI cuGraphicsMapResources_ptsz( + unsigned int count, CUgraphicsResource *resources, CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} + +extern "C" CUresult CUDAAPI cuGraphicsUnmapResources_ptsz( + unsigned int count, CUgraphicsResource *resources, CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; +} - return result; +extern "C" CUresult CUDAAPI cuMemPrefetchAsync_ptsz(CUdeviceptr devPtr, + size_t count, + CUdevice dstDevice, + CUstream hStream) { + if (g_debug_execution >= 3) { + announce_call(__my_func__); + } + printf("WARNING: this function has not been implemented yet."); + return CUDA_SUCCESS; } |