// developed by Mahmoud Khairy, Purdue Univ
// abdallm@purdue.edu

#include <math.h>
#include <stdio.h>
#include <time.h>
#include <fstream>
#include <iostream>
#include <sstream>
#include <string>
#include <vector>

#include "../../libcuda/gpgpu_context.h"
#include "../abstract_hardware_model.h"
#include "../cuda-sim/cuda-sim.h"
#include "../gpgpu-sim/gpu-sim.h"
#include "../gpgpusim_entrypoint.h"
#include "../option_parser.h"
#include "ISA_Def/trace_opcode.h"
#include "trace_driven.h"

/* TO DO:
 * NOTE: the current version of trace-driven is functionally working fine,
 * but we still need to improve traces compression and simulation speed.
 * This includes:
 * 1- Prefetch concurrent thread that prefetches traces from disk (to not be
 * limited by disk speed) 2- traces compression format a. cfg format and remove
 * thread/block Id from the head b. using zlib library to save in binary format
 *
 * 3- Efficient memory improvement (save string not objects - parse only 10 in
 * the buffer) 4- Seeking capability - thread scheduler (save tb index and warp
 * index info in the traces header) 5- Get rid off traces intermediate files -
 * change the tracer
 */

int main(int argc, const char** argv) {
  gpgpu_context* m_gpgpu_context = new gpgpu_context();
  gpgpu_sim* m_gpgpu_sim =
      m_gpgpu_context->gpgpu_trace_sim_init_perf(argc, argv);
  m_gpgpu_sim->init();

  // for each kernel
  // load file
  // parse and create kernel info
  // launch
  // while loop till the end of the end kernel execution
  // prints stats

  trace_parser tracer(m_gpgpu_sim->get_config().get_traces_filename(),
                      m_gpgpu_sim, m_gpgpu_context);
  trace_config config(m_gpgpu_sim);

  std::vector<std::string> commandlist = tracer.parse_kernellist_file();
  bool first_kernel = true;

  for (unsigned i = 0; i < commandlist.size(); ++i) {
    trace_kernel_info_t* kernel_info = NULL;
    if (commandlist[i].substr(0, 6) == "Memcpy") {
      size_t addre, Bcount;
      tracer.parse_memcpy_info(commandlist[i], addre, Bcount);
      std::cout << commandlist[i] << std::endl;
      m_gpgpu_sim->perf_memcpy_to_gpu(addre, Bcount);
      continue;
    } else {
      // skip the first unimportant initialization kernel
      if (m_gpgpu_sim->get_config().is_skip_first_kernel() && first_kernel) {
        first_kernel = false;
        continue;
      }
      kernel_info = tracer.parse_kernel_info(commandlist[i], &config);
      m_gpgpu_sim->launch(kernel_info);
    }

    bool active = false;
    bool sim_cycles = false;
    bool break_limit = false;

    do {
      if (!m_gpgpu_sim->active()) break;

      // performance simulation
      if (m_gpgpu_sim->active()) {
        m_gpgpu_sim->cycle();
        sim_cycles = true;
        m_gpgpu_sim->deadlock_check();
      } else {
        if (m_gpgpu_sim->cycle_insn_cta_max_hit()) {
          m_gpgpu_context->the_gpgpusim->g_stream_manager
              ->stop_all_running_kernels();
          break_limit = true;
        }
      }

      active = m_gpgpu_sim->active();

    } while (active);

    if (kernel_info) {
      tracer.kernel_finalizer(kernel_info);
      m_gpgpu_sim->print_stats();
    }

    if (sim_cycles) {
      m_gpgpu_sim->update_stats();
      m_gpgpu_context->print_simulation_time();
    }

    if (break_limit) {
      printf(
          "GPGPU-Sim: ** break due to reaching the maximum cycles (or "
          "instructions) **\n");
      fflush(stdout);
      exit(1);
    }
  }

  // we print this message to inform the gpgpu-simulation stats_collect script
  // that we are done
  printf("GPGPU-Sim: *** simulation thread exiting ***\n");
  printf("GPGPU-Sim: *** exit detected ***\n");

  return 1;
}