1. adding top level configuration class and making shader and memory configuration

   components of this class.
2. clock memory pipeline no. subwarp times for each shader clock and increase
   rob-size for texture cache (trying to improve correlation, currently at 0.9218)
3. start to modify shader stats to add back features for visualizer (warp 
   divergence distribution kind of working again)

passing cuda 3.1 regression and ptxplus correlation tests

[git-p4: depot-paths = "//depot/gpgpu_sim_research/fermi/distribution/": change = 7909]

1 files changed, 5 insertions, 5 deletions

diff --git a/libcuda/cuda_runtime_api.cc b/libcuda/cuda_runtime_api.cc
index 93f7512..1990076 100644
--- a/libcuda/cuda_runtime_api.cc
+++ b/libcuda/cuda_runtime_api.cc
@@ -183,7 +183,7 @@ void register_ptx_function( const char *name, function_info *impl )
 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->num_shader(); }
+   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();
@@ -282,7 +282,7 @@ class _cuda_device_id *GPGPUSim_Init()
       prop->warpSize = the_gpu->wrp_size();
       prop->clockRate = the_gpu->shader_clock();
 #if (CUDART_VERSION >= 2010)
-      prop->multiProcessorCount = the_gpu->num_shader();
+      prop->multiProcessorCount = the_gpu->get_config().num_shader();
 #endif
       the_gpu->set_prop(prop);
       the_device = new _cuda_device_id(the_gpu);
@@ -1103,7 +1103,7 @@ void** CUDARTAPI __cudaRegisterFatBinary( void *fatCubin )
    unsigned max_capability=0;
    unsigned selected_capability=0;
    bool found=false;
-   unsigned forced_max_capability = context->get_device()->get_gpgpu()->get_forced_max_capability();
+   unsigned forced_max_capability = context->get_device()->get_gpgpu()->get_config().get_forced_max_capability();
    while( info->ptx[num_ptx_versions].gpuProfileName != NULL ) {
       unsigned capability=0;
       sscanf(info->ptx[num_ptx_versions].gpuProfileName,"compute_%u",&capability);
@@ -1129,9 +1129,9 @@ void** CUDARTAPI __cudaRegisterFatBinary( void *fatCubin )
              info->ident, info->ptx[selected_capability].gpuProfileName );
       symbol_table *symtab;
       const char *ptx = info->ptx[selected_capability].ptx;
-      if(context->get_device()->get_gpgpu()->convert_to_ptxplus() ) {
+      if(context->get_device()->get_gpgpu()->get_config().convert_to_ptxplus() ) {
            char *ptxplus_str = gpgpu_ptx_sim_convert_ptx_to_ptxplus(ptx, info->cubin[selected_capability].cubin, source_num++,
-                                                                    context->get_device()->get_gpgpu()->saved_converted_ptxplus());
+                                                  context->get_device()->get_gpgpu()->get_config().saved_converted_ptxplus());
            symtab=gpgpu_ptx_sim_load_ptx_from_string(ptxplus_str,source_num);
            context->add_binary(symtab,fat_cubin_handle);
            gpgpu_ptxinfo_load_from_string(ptx,source_num);