#include <cstdio>

#include "matmul.h"

#define CHECK_CUDA(call)                                              \
  do {                                                                \
    cudaError_t status_ = call;                                       \
    if (status_ != cudaSuccess) {                                     \
      fprintf(stderr, "CUDA error (%s:%d): %s\n", __FILE__, __LINE__, \
              cudaGetErrorString(status_));                           \
      exit(EXIT_FAILURE);                                             \
    }                                                                 \
  } while (0)

static __global__ void matmul_kernel(float *A, float *B, float *C, int M, int N,
                                     int K) {
  int i = blockDim.x * blockIdx.x + threadIdx.x;
  int j = blockDim.y * blockIdx.y + threadIdx.y;
  if (i >= M || j >= N) return;
  float sum = 0.0;
  for (int k = 0; k < K; ++k) sum += A[i * K + k] * B[k * N + j];
  C[i * N + j] = sum;
}

static float *A_gpu, *B_gpu, *C_gpu;

void matmul_naive_initialize(size_t M, size_t N, size_t K) {
  CHECK_CUDA(cudaMalloc(&A_gpu, M * K * sizeof(float)));
  CHECK_CUDA(cudaMalloc(&B_gpu, K * N * sizeof(float)));
  CHECK_CUDA(cudaMalloc(&C_gpu, M * N * sizeof(float)));
}

void matmul_naive(float *A, float *B, float *C, size_t M, size_t N, size_t K) {
  CHECK_CUDA(
      cudaMemcpy(A_gpu, A, M * K * sizeof(float), cudaMemcpyHostToDevice));
  CHECK_CUDA(
      cudaMemcpy(B_gpu, B, K * N * sizeof(float), cudaMemcpyHostToDevice));

  dim3 blockDim(32, 32);
  dim3 gridDim((M + 32 - 1) / 32, (N + 32 - 1) / 32);
  matmul_kernel<<<gridDim, blockDim>>>(A_gpu, B_gpu, C_gpu, M, N, K);
  CHECK_CUDA(cudaGetLastError());
  CHECK_CUDA(
      cudaMemcpy(C, C_gpu, M * N * sizeof(float), cudaMemcpyDeviceToHost));
}

void matmul_naive_finalize(size_t M, size_t N, size_t K) {
  CHECK_CUDA(cudaFree(A_gpu));
  CHECK_CUDA(cudaFree(B_gpu));
  CHECK_CUDA(cudaFree(C_gpu));
}