lab/5/data science/1e/main.cu

#include <stdint.h>

template <typename T, int TILE_SIZE>
__global__ void mat_mul(T *A, T *B, T *C, int N, int M, int K) {
    __shared__ T sA[TILE_SIZE][TILE_SIZE];
    __shared__ T sB[TILE_SIZE][TILE_SIZE];
    
    int bx = blockIdx.x, by = blockIdx.y;
    int tx = threadIdx.x, ty = threadIdx.y;
    
    int row = by * TILE_SIZE + ty;
    int col = bx * TILE_SIZE + tx;

    if (col >= K || row >= M) return;
    
    T sum = 0;

    int tiles_len = (M + TILE_SIZE - 1) / TILE_SIZE;
    
    for (int tile = 0; tile < tiles_len; tile++) {
        int aCol = tile * TILE_SIZE + tx;
        int bRow = tile * TILE_SIZE + ty;

        if (aCol < M) {
            sA[ty][tx] = A[row * M + aCol];
        } else {
            sA[ty][tx] = 0;
        }

        sB[ty][tx] = (T)((uint64_t)B[bRow * K + col] & ((uint64_t)(bRow >= M) - 1));
        __syncthreads();
        
        for (int k = 0; k < TILE_SIZE; k++) {
            sum += sA[ty][k] * sB[k][tx];
        }
    }

    C[row * K + col] = sum;
}

template <typename T>
__global__ void dumb_mat_mul(T *A, T *B, T *C, int N, int M, int K) {
    int col = blockIdx.x * blockDim.x + threadIdx.x;
    int row = blockIdx.y * blockDim.y + threadIdx.y;

    if (col >= K || row >= M) return;

    T sum = 0;
    for (int i = 0; i < M; i++) {
        sum += A[row * M + i] * B[i * K + col];
    }
    C[row * K + col] = sum;
}

#define N 1024
#define M 1024
#define K 1024
#define NO_PRINT 1
#define GRID_DIM 1
#define BLOCK_DIM 32

#define MAT_TYPE int
#define MAT_FMT "%d\t"
#define A_LEN (N * M)
#define B_LEN (M * K)
#define C_LEN (N * K)
#define A_SIZE (sizeof(MAT_TYPE) * N * M)
#define B_SIZE (sizeof(MAT_TYPE) * M * K)
#define C_SIZE (sizeof(MAT_TYPE) * N * K)

#include <cstdio>
#include <random>
#include <chrono>
using namespace std::chrono;

template <typename T>
void mat_print(T *a, const char *fmt, int n, int m) {
    for (auto row = 0; row < n; row++) {
        for (auto col = 0; col < m; col++) {
            printf(fmt, a[row * m + col]);
        }
        printf("\n");
    }
}

int main() {
    std::random_device rd;
    std::mt19937 engine(rd());
    std::uniform_int_distribution<MAT_TYPE> dist(1, 10);

    auto buf = (MAT_TYPE *)malloc(A_SIZE + B_SIZE + C_SIZE);
    for (auto i = 0; i < A_LEN + B_LEN; i++) {
        buf[i] = dist(engine);
    }

    MAT_TYPE *a = buf;
    MAT_TYPE *b = a + A_LEN;
    MAT_TYPE *c = b + B_LEN;

#if NO_PRINT==0
    printf("\na\n");
    mat_print(a, MAT_FMT, N, M);
    printf("\nb\n");
    mat_print(b, MAT_FMT, M, K);
#endif

    MAT_TYPE *d_a, *d_b, *d_c;
    cudaMalloc(&d_a, A_SIZE);
    cudaMalloc(&d_b, B_SIZE);
    cudaMalloc(&d_c, C_SIZE);

    cudaMemcpy(d_a, a, A_SIZE, cudaMemcpyHostToDevice);
    cudaMemcpy(d_b, b, B_SIZE, cudaMemcpyHostToDevice);

    dim3 gridDim(GRID_DIM, GRID_DIM);
    dim3 blockDim(BLOCK_DIM, BLOCK_DIM);

    int cycles = 0;
    microseconds duration(0);

    while (duration.count() < 1e6) {
        auto start = high_resolution_clock::now();
        mat_mul<MAT_TYPE, BLOCK_DIM><<<gridDim, blockDim>>>(d_a, d_b, d_c, N, M, K);
        cudaDeviceSynchronize();
        auto end = high_resolution_clock::now();

        cycles++;
        duration += duration_cast<microseconds>(end - start);
    }

#if NO_PRINT==0
    cudaMemcpy(c, d_c, C_SIZE, cudaMemcpyDeviceToHost);
    printf("\nc\n");
    mat_print(c, MAT_FMT, N, K);
#endif
    printf("optimized mul take %f usec avg in %d cycles\n", (float)(duration.count()) / cycles, cycles);

    cycles = 0;
    duration = microseconds(0);
    while (duration.count() < 1e6) {
        auto start = high_resolution_clock::now();
        dumb_mat_mul<MAT_TYPE><<<gridDim, blockDim>>>(d_a, d_b, d_c, N, M, K);
        cudaDeviceSynchronize();
        auto end = high_resolution_clock::now();

        cycles++;
        duration += duration_cast<microseconds>(end - start);
    }

#if NO_PRINT==0
    cudaMemcpy(c, d_c, C_SIZE, cudaMemcpyDeviceToHost);
    printf("\nc\n");
    mat_print(c, MAT_FMT, N, K);
#endif
    printf("dumb mul take %f usec avg in %d cycles\n", (float)(duration.count()) / cycles, cycles);

    cudaFree(a);
    cudaFree(b);
    cudaFree(c);
    free(buf);
}