mp3.cu

#include <wb.h>

#define wbCheck(stmt)                                                          \
  do {                                                                         \
    cudaError_t err = stmt;                                                    \
    if (err != cudaSuccess) {                                                  \
      wbLog(ERROR, "Failed to run stmt ", #stmt);                              \
      wbLog(ERROR, "Got CUDA error ...  ", cudaGetErrorString(err));           \
      return -1;                                                               \
    }                                                                          \
  } while (0)
#define TILE_WIDTH 16

// Compute C = A * B
__global__ void matrixMultiplyShared(float *A, float *B, float *C, int numARows,
                                     int numAColumns, int numBRows,
                                     int numBColumns, int numCRows,
                                     int numCColumns) {
  //@@ Insert code to implement matrix multiplication here
  //@@ You have to use shared memory for this MP
  int r = blockIdx.y * blockDim.y + threadIdx.y, c = blockIdx.x * blockDim.x + threadIdx.x;
  __shared__ float ds_A[TILE_WIDTH][TILE_WIDTH];
  __shared__ float ds_B[TILE_WIDTH][TILE_WIDTH];

  float cValue = 0;
  for(int t = 0; t < (numAColumns - 1)/TILE_WIDTH + 1; t++) {
    ds_A[threadIdx.y][threadIdx.x] = (r < numARows && t * TILE_WIDTH + threadIdx.x < numAColumns) ? 
                A[r * numAColumns + t * TILE_WIDTH + threadIdx.x] : 0;
    ds_B[threadIdx.y][threadIdx.x] = (t * TILE_WIDTH + threadIdx.y < numBRows && c < numBColumns) ? 
                B[(t * TILE_WIDTH + threadIdx.y) * numBColumns + c] : 0;
    __syncthreads();

    for(int i = 0; i < TILE_WIDTH; i++) 
      cValue += ds_A[threadIdx.y][i] * ds_B[i][threadIdx.x];
    __syncthreads();
  }
  if(r < numCRows && c < numCColumns) C[r * numCColumns + c] = cValue;
}

int main(int argc, char **argv) {
  wbArg_t args;
  float *hostA; // The A matrix
  float *hostB; // The B matrix
  float *hostC; // The output C matrix
  float *deviceA;
  float *deviceB;
  float *deviceC;
  int numARows;    // number of rows in the matrix A
  int numAColumns; // number of columns in the matrix A
  int numBRows;    // number of rows in the matrix B
  int numBColumns; // number of columns in the matrix B
  int numCRows;    // number of rows in the matrix C (you have to set this)
  int numCColumns; // number of columns in the matrix C (you have to set this)

  args = wbArg_read(argc, argv);

  wbTime_start(Generic, "Importing data and creating memory on host");
  hostA =
      ( float * )wbImport(wbArg_getInputFile(args, 0), &numARows, &numAColumns);
  hostB =
      ( float * )wbImport(wbArg_getInputFile(args, 1), &numBRows, &numBColumns);
  //@@ Set numCRows and numCColumns
  numCRows = numARows;
  numCColumns = numBColumns;
  //@@ Allocate the hostC matrix
  int aSize = numARows * numAColumns * sizeof(float), bSize = numBRows * numBColumns * sizeof(float), cSize = numCRows * numCColumns * sizeof(float); 
  hostC = ( float * )malloc(cSize); 
  wbTime_stop(Generic, "Importing data and creating memory on host");

  wbLog(TRACE, "The dimensions of A are ", numARows, " x ", numAColumns);
  wbLog(TRACE, "The dimensions of B are ", numBRows, " x ", numBColumns);

  wbTime_start(GPU, "Allocating GPU memory.");
  //@@ Allocate GPU memory here
  cudaMalloc((void **) &deviceA, aSize);
  cudaMalloc((void **) &deviceB, bSize);
  cudaMalloc((void **) &deviceC, cSize);
  wbTime_stop(GPU, "Allocating GPU memory.");

  wbTime_start(GPU, "Copying input memory to the GPU.");
  //@@ Copy memory to the GPU here
  cudaMemcpy(deviceA, hostA, aSize, cudaMemcpyHostToDevice);
  cudaMemcpy(deviceB, hostB, bSize, cudaMemcpyHostToDevice);
  wbTime_stop(GPU, "Copying input memory to the GPU.");

  //@@ Initialize the grid and block dimensions here
  dim3 dimGrid((numCColumns - 1) / TILE_WIDTH + 1, (numCRows - 1) / TILE_WIDTH + 1, 1);
  dim3 dimBlock(TILE_WIDTH, TILE_WIDTH, 1);
  wbTime_start(Compute, "Performing CUDA computation");
  //@@ Launch the GPU Kernel here
  matrixMultiplyShared<<<dimGrid, dimBlock>>>(deviceA, deviceB, deviceC, numARows, numAColumns, numBRows, numBColumns, numCRows, numCColumns);
  cudaDeviceSynchronize();
  wbTime_stop(Compute, "Performing CUDA computation");

  wbTime_start(Copy, "Copying output memory to the CPU");
  //@@ Copy the GPU memory back to the CPU here
  cudaMemcpy(hostC, deviceC, cSize, cudaMemcpyDeviceToHost);
  wbTime_stop(Copy, "Copying output memory to the CPU");

  wbTime_start(GPU, "Freeing GPU Memory");
  //@@ Free the GPU memory here
  cudaFree(deviceA); cudaFree(deviceB); cudaFree(deviceC);
  wbTime_stop(GPU, "Freeing GPU Memory");

  wbSolution(args, hostC, numCRows, numCColumns);

  free(hostA);
  free(hostB);
  free(hostC);

  return 0;
}