#include "mat_mul.h"

#include <cstdio>
#include <cuda_runtime.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 MAX_NUM_GPU 4
int num_devices = 0;

#define TILE_SIZE       32
#define WORK_PER_THREAD 8
#define REG_TILE_SIZE   (TILE_SIZE / WORK_PER_THREAD)
#define min(A, B)       (((A)>(B))?(B):(A))

__global__ void sgemm(float *A, float *B, float *C, int M, int N, int K)
{
  int lr = threadIdx.x;
  int lc = threadIdx.y;
  int gr = blockIdx.x * TILE_SIZE + lr;
  int gc = blockIdx.y * TILE_SIZE + lc;

  // printf("(gr, gc): (%d, %d), (lr, lc): (%d, %d)\n", gr, gc, lr, lc);

  __shared__ float A_mini[TILE_SIZE][TILE_SIZE];
  __shared__ float B_mini[TILE_SIZE][TILE_SIZE];

  float temp[WORK_PER_THREAD];
  for(int i = 0; i < WORK_PER_THREAD; i++)
  {
    temp[i] = 0.0;
  }

  int tiles = (K + TILE_SIZE - 1) / TILE_SIZE;
  int tr = lr;
  int tc = lc;

  for(int tile = 0; tile < tiles; tile++)
  {
    int tileRow = lr;
    int tileCol = lc;

    int Arow = gr;
    int Acol = tc;
    int Brow = tr;
    int Bcol = gc;
    for(int work = 0; work < WORK_PER_THREAD; work++)
    {
      // if(gr == 32 && gc >= 32 && tile == 1 && work == 0)
      // {
      //   printf("(gr, gc): (%d, %d), A_mini[%d][%d], B_mini[%d][%d], A[%d][%d], B[%d][%d]\n", gr, gc, (lr + work * REG_TILE_SIZE), lc, (lr + work * REG_TILE_SIZE), lc, (gr + work * REG_TILE_SIZE), tc, (tr + work * REG_TILE_SIZE), gc);
      // }
      
      if(Arow < M && Acol < K) 
      {
        A_mini[tileRow][tileCol] = A[Arow * K + tc];
      }
      else
      {
        A_mini[tileRow][tileCol] = 0.0;
      }
      
      if(Brow < K && Bcol < N)
      {
        B_mini[tileRow][tileCol] = B[Brow * N + gc];  
      }
      else
      {
        B_mini[tileRow][tileCol] = 0.0;
      }

      tileRow += REG_TILE_SIZE;
      Arow += REG_TILE_SIZE;
      Brow += REG_TILE_SIZE;
    }
    __syncthreads();

    // if(gr == 32 && gc == 32 && tile == 1)
    // {
    //   printf("(gr, gc): (%d, %d), (lr, lc): (%d, %d)\n", gr, gc, lr, lc);
    //   printf("------ A_mini ------\n");
    //   for(int i = 0; i < TILE_SIZE; i++)
    //   {
    //     for(int j = 0; j < TILE_SIZE; j++)
    //     {
    //       printf("%.3f ", A_mini[i][j]);
    //     }
    //     printf("\n");
    //   }

    //   printf("------ B_mini ------\n");
    //   for(int i = 0; i < TILE_SIZE; i++)
    //   {
    //     for(int j = 0; j < TILE_SIZE; j++)
    //     {
    //       printf("%.3f ", B_mini[i][j]);
    //     }
    //     printf("\n");
    //   }

    //   printf("------ C ------\n");
    //   for(int i = 0; i < M; i++)
    //   {
    //     for(int j = 0; j < N; j++)
    //     {
    //       printf("%.3f ", C[i * N + j]);
    //     }
    //     printf("\n");
    //   }
    // }

    for(int k = 0; k < TILE_SIZE; k++)
    {
      int AtileRow = lr;
      int BtileCol = lc;
      for(int work = 0; work < WORK_PER_THREAD; work++)
      {
        temp[work] += A_mini[AtileRow][k] * B_mini[k][BtileCol];
        AtileRow += REG_TILE_SIZE;
      }
    } 
    __syncthreads();

    tr += TILE_SIZE;
    tc += TILE_SIZE;
  }

  int Crow = gr;
  int Ccol = gc;  
  for(int work = 0; work < WORK_PER_THREAD; work++)
  {
    if(Crow < M && Ccol < N)
    {
      C[Crow * N + Ccol] = temp[work];
    }
    Crow += REG_TILE_SIZE;
  }
}

// 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], Mlen[MAX_NUM_GPU];

void mat_mul(float *_A, float *_B, float *_C, int _M, int _N, int _K)
{

  // Launch kernel on every GPU
  for (int i = 0; i < num_devices; i++)
  {
    dim3 blockDim(TILE_SIZE / WORK_PER_THREAD, TILE_SIZE);
    dim3 gridDim((Mlen[i] + TILE_SIZE - 1) / TILE_SIZE, (N + TILE_SIZE - 1) / TILE_SIZE);

    // printf("Device #%d (gridDim.x, gridDim.y): (%d, %d), (blockDim.x, blockDim.y): (%d, %d)\n", i, gridDim.x, gridDim.y, blockDim.x, blockDim.y);
  
    CUDA_CALL(cudaSetDevice(i));
    sgemm <<< gridDim, blockDim >>> (a_d[i], b_d[i], c_d[i], Mlen[i], N, K);
  }

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

void mat_mul_init(float *A, float *B, float *C, int _M, int _N, int _K)
{
  M = _M, N = _N, K = _K;

  CUDA_CALL(cudaGetDeviceCount(&num_devices));
  // num_devices = 1;

  printf("Using %d devices\n", num_devices);
  for (int i = 0; i < num_devices; i++)
  {
    cudaDeviceProp prop;
    CUDA_CALL(cudaGetDeviceProperties(&prop, i));

    // Try printing more detailed information here
    printf("[GPU %d] %s\n", i, prop.name);
  }

  if (num_devices <= 0)
  {
    printf("No CUDA device found. Aborting\n");
    exit(1);
  }

  // Setup problem size for each GPU
  for (int i = 0; i < num_devices; i++)
  {
    Mbegin[i] = (M / num_devices) * i + min(i, M % num_devices);
    Mend[i] = (M / num_devices) * (i + 1) + min(i + 1, M % num_devices);
    Mlen[i] = Mend[i] - Mbegin[i];
    // printf("Device #%d (Mbegin, Mend, Mlen): (%d, %d, %d)\n", i, Mbegin[i], Mend[i], Mlen[i]);
  }

  // Allocate device memory for each GPU
  for (int i = 0; i < num_devices; i++)
  {
    CUDA_CALL(cudaSetDevice(i));
    CUDA_CALL(cudaMalloc(&a_d[i], Mlen[i] * K * sizeof(float)));
    CUDA_CALL(cudaMalloc(&b_d[i], K * N * sizeof(float)));
    CUDA_CALL(cudaMalloc(&c_d[i], Mlen[i] * N * sizeof(float)));
  }

  // Upload A and B matrix to every GPU
  for (int i = 0; i < num_devices; i++)
  {
    CUDA_CALL(cudaSetDevice(i));
    CUDA_CALL(cudaMemcpy(a_d[i], A + Mbegin[i] * K,
                         Mlen[i] * K * sizeof(float),
                         cudaMemcpyHostToDevice));
    CUDA_CALL(cudaMemcpy(b_d[i], B, K * N * sizeof(float), cudaMemcpyHostToDevice));
  }

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

void mat_mul_final(float *A, float *B, float *C, int M, int N, int K)
{
  // Do any post-matmul cleanup work here.

  // Download C matrix from GPUs
  for (int i = 0; i < num_devices; i++)
  {
    CUDA_CALL(cudaSetDevice(i));
    CUDA_CALL(cudaMemcpy(C + Mbegin[i] * N, c_d[i],
                         Mlen[i] * N * sizeof(float),
                         cudaMemcpyDeviceToHost));
  }

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