//#include "mat_mul.h"
#include <mpi.h> 
#include <cstdio>
#include <cuda_runtime.h>
#include "util.h"
#include "convolution.h"

#define CUDA_CALL(f)                                                           \
  {                                                                            \
    cudaError_t err = (f);                                                     \
    if (err != cudaSuccess) {                                                  \
      fprintf(stderr, "CUDA error at [%s:%d] %d %s\n", __FILE__, __LINE__,     \
              err, cudaGetErrorString(err));                                   \
      exit(1);                                                                 \
    }                                                                          \
  }

#define TS 8
//#define WPT 8
//#define RTS (TS/WPT)

#define MAX_NUM_GPU 4

static float *input, *output, *filter;
static float *in_d[MAX_NUM_GPU], *out_d[MAX_NUM_GPU], *fil_d[MAX_NUM_GPU];
static int N, C, H, W;
static int K, R, S;
static int pad;
static int dilation;
static int stride;
static int mpi_rank, mpi_world_size;
static int num_devices = 1;
static int size[2];
static int NN[MAX_NUM_GPU];
static int OH, OW;
//int num_devices = 4;

__global__ void conv(float *_input, float *_output, float *_filter, int _N, int _C, int _H, int _W, int _K, int _R, int _S, int _pad, int _dilation, int _stride) {
  //int i = blockDim.x * blockIdx.x + threadIdx.x;
  //int j = blockDim.y * blockIdx.y + threadIdx.y;
  //const int row = threadIdx.x;
  //const int col = threadIdx.y;
  const int globalRow = blockDim.x * blockIdx.x + threadIdx.x;
  const int globalCol = blockDim.y * blockIdx.y + threadIdx.y;
  int OH, OW;
//  const int large_M = Mend[num_devices]-Mbegin[0];

  
   OH = (_H + 2 * _pad - _dilation * (_R - 1) - 1) / _stride + 1; 
   OW = (_W + 2 * _pad - _dilation * (_S - 1) - 1) / _stride + 1; 

   
   int n, k, w;
   w = globalCol;
   n = w / (_K * OW);
   w = w - n * (_K * OW);
   k = w / OW;
   w = w - k * OW;

   int col = w;
   int row = globalRow;

   if (globalRow >= OH || globalCol >= _N*_K*OW) return;

   int start_row = row * _stride - _pad;
   int start_col = col * _stride - _pad;

   float o = 0.0f;
   for(int c = 0; c < _C; c++){
	  for(int i =0; i < _R; i++){
		 for(int j=0; j < _S ; j++){
			int h = start_row + i*_dilation;
		        int w = start_col + j*_dilation;
	                if (h<0 || w<0 || h >= _H || w>= _W) continue;
		        float in = _input[n*_C*_W*_H + c*_W*_H + h*_W + w];
		        float fil = _filter[k*_C*_R*_S + c*_R*_S + i*_S + j];
		        o += in * fil;	
                 }
	  }
   }
   
   _output[n*_K*OH*OW + k*OH*OW + row*OW + col] = o;

}
// Array of device (GPU) pointers
//static float *a_d[MAX_NUM_GPU];
//static float *b_d[MAX_NUM_GPU];
//static float *c_d[MAX_NUM_GPU];
//static int M, N, K;
//static int Mbegin[MAX_NUM_GPU], Mend[MAX_NUM_GPU];

void convolution(float *_input, float *_output, float *_filter, int _N, int _C, int _H, int _W, int _K, int _R, int _S, int _pad, int _dilation, int _stride) {

  int offset = 0;
  MPI_Request request;
  MPI_Status status;

  input = _input;
  output = _output;
  filter = _filter;

  if(mpi_rank == 0 && mpi_world_size == 2 && size[1] != 0){
	  MPI_Isend(&input[size[0]*C*H*W], size[1]*C*H*W, MPI_FLOAT, 1, 0, MPI_COMM_WORLD, &request);
	  MPI_Isend(filter, _K*_C*_R*_S, MPI_FLOAT, 1, 0, MPI_COMM_WORLD, &request);
	  if(size[mpi_rank]<MAX_NUM_GPU){
		  num_devices = size[mpi_rank];
	  }
  }
  else if(mpi_rank == 1 && size[mpi_rank] != 0){
	  alloc_tensor(&input, size[1], C, H, W);
	  alloc_tensor(&output, size[1], K, OH, OW);
	  alloc_tensor(&filter, _K, _C, _R, _S);
	  MPI_Recv(input, size[1]*C*H*W, MPI_FLOAT, 0, 0, MPI_COMM_WORLD, &status);
	  MPI_Recv(filter, _K*_C*_R*_S, MPI_FLOAT, 0, 0, MPI_COMM_WORLD, &status);
	  if (size[mpi_rank] < MAX_NUM_GPU){
		  num_devices = size[mpi_rank];
	  }
  }

  offset = 0;
  for (int i =0; i < num_devices; i++){
	  CUDA_CALL(cudaMemcpy(in_d[i], input + offset, NN[i]*C*H*W*sizeof(float), cudaMemcpyHostToDevice));
	  CUDA_CALL(cudaMemcpy(fil_d[i], filter, K*C*R*S*sizeof(float), cudaMemcpyHostToDevice));
	  offset += NN[i] * C * H * W;
  }
 
  for (int i=0; i<num_devices; i++){
	  CUDA_CALL( cudaDeviceSynchronize());
  }

  for(int i=0; i<num_devices; i++){
	  dim3 gridDim((OH+TS-1)/TS, (NN[i]*K*OW +TS-1)/TS, 1);
	  dim3 blockDim(TS, TS, 1);

	  CUDA_CALL( cudaSetDevice(i) );
	  conv<<<gridDim, blockDim>>>(in_d[i], out_d[i], fil_d[i], NN[i], _C, _H, _W, _K, _R, _S, _pad, _dilation, _stride);
  }

  // DO NOT REMOVE; NEEDED FOR TIME MEASURE
  for (int i =0; i < num_devices; i++){
	  CUDA_CALL( cudaSetDevice(i) );
	  CUDA_CALL( cudaDeviceSynchronize() );
  }

  offset = 0;
  for(int i =0; i < num_devices; i++){
	  CUDA_CALL( cudaSetDevice(i));
	  CUDA_CALL( cudaMemcpy(output + offset, out_d[i], NN[i]*K*OH*OW*sizeof(float),cudaMemcpyDeviceToHost));
	  offset += NN[i]*K*OH*OW;
  }

  for(int i =0; i < num_devices; i++){
	  CUDA_CALL( cudaSetDevice(i));
	  CUDA_CALL( cudaDeviceSynchronize());
  }

  if(mpi_rank ==0 && mpi_world_size == 2 && size[1] != 0){
	  MPI_Recv(&output[size[0]*K*OH*OW], size[1]*K*OH*OW, MPI_FLOAT, 1, 0, MPI_COMM_WORLD, &status);
  }else if(mpi_rank == 1 && size[1] != 0){
	  MPI_Isend(output, size[1]*K*OH*OW, MPI_FLOAT, 0, 0, MPI_COMM_WORLD, &request);
  }
}


void convolution_init(int _N, int _C, int _H, int _W, int _K, int _R, int _S, int _pad, int _dilation, int _stride) {
  N = _N; C = _C; H = _H; W = _W;
  K = _K; R = _R; S = _S;
  pad = _pad;
  dilation = _dilation;
  stride = _stride;

  MPI_Comm_rank(MPI_COMM_WORLD, &mpi_rank);
  MPI_Comm_size(MPI_COMM_WORLD, &mpi_world_size);

  OH = (H + 2 * pad - dilation * (R - 1) - 1) / stride + 1; 
  OW = (W + 2 * pad - dilation * (S - 1) - 1) / stride + 1; 

  if (mpi_world_size == 2 && _N > 4) size[1] = _N/2;
  else size[1] = 0;
  size[0] = N - size[1];

  if (size[mpi_rank] < MAX_NUM_GPU){
	  num_devices = size[mpi_rank];
	  for (int i = 0; i < size[mpi_rank]; i++){
		  NN[i]=1;}
  } else{
	  num_devices = MAX_NUM_GPU;
	  int quotient = size[mpi_rank] / MAX_NUM_GPU;
	  int remain = size[mpi_rank] % MAX_NUM_GPU;
	  for (int i = 0; i < MAX_NUM_GPU; i++){
		  NN[i] = quotient;
		  if (i < remain){ NN[i]++;}
	  }
  } 
 for (int i = 0 ; i < num_devices ; i++) {
     CUDA_CALL( cudaSetDevice(i) );
     CUDA_CALL( cudaMalloc(&in_d[i], NN[i]*C*H*W*sizeof(float)) );
     CUDA_CALL( cudaMalloc(&out_d[i], NN[i]*K*OH*OW*sizeof(float)) );
     CUDA_CALL( cudaMalloc(&fil_d[i], K*C*R*S*sizeof(float)) );
   }
}

void convolution_final(int _N, int _C, int _H, int _W, int _K, int _R, int _S, int _pad, int _dilation, int _stride) {
}