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 *    notice, this list of conditions and the following disclaimer.
 *  * Redistributions in binary form must reproduce the above copyright
 *    notice, this list of conditions and the following disclaimer in the
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 *  * Neither the name of NVIDIA CORPORATION nor the names of its
 *    contributors may be used to endorse or promote products derived
 *    from this software without specific prior written permission.
 *
 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
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#include <stdio.h>
#include <stdlib.h>
// Define some error checking macros.
#define cudaErrCheck(stat) { cudaErrCheck_((stat), __FILE__, __LINE__); }
void cudaErrCheck_(cudaError_t stat, const char *file, int line) {
   if (stat != cudaSuccess) {
      fprintf(stderr, "CUDA Error: %s %s %d\n", cudaGetErrorString(stat), file, line);
   }
}


#include <mma.h>
using namespace nvcuda;

// Must be multiples of 16 for wmma code to work
#define MATRIX_M (32)
#define MATRIX_N (32)
#define MATRIX_K (32)



// The only dimensions currently supported by WMMA
const int WMMA_M = 16;
const int WMMA_N = 16;
const int WMMA_K = 16;

__global__ void wmma_example(half *a, half *b, float *c, int M, int N, int K, float alpha, float beta) {
   // Leading dimensions. Packed with no transpositions.
   int lda = M;
   int ldb = K;
   int ldc = M;

   // Tile using a 2D grid
   int warpM = (blockIdx.x * blockDim.x + threadIdx.x) / warpSize;
   int warpN = (blockIdx.y * blockDim.y + threadIdx.y);
 
   // Declare the fragments
   wmma::fragment<wmma::matrix_a, WMMA_M, WMMA_N, WMMA_K, half, wmma::row_major> a_frag;
   wmma::fragment<wmma::matrix_b, WMMA_M, WMMA_N, WMMA_K, half, wmma::row_major> b_frag;
   wmma::fragment<wmma::accumulator, WMMA_M, WMMA_N, WMMA_K, float> acc_frag;
   wmma::fragment<wmma::accumulator, WMMA_M, WMMA_N, WMMA_K, float> c_frag;

   wmma::fill_fragment(acc_frag, 0.0f);

   // Loop over k
   for (int i = 0; i < K; i += WMMA_K) {
      int aRow = warpM * WMMA_M;
      int aCol = i;

      int bRow = i;
      int bCol = warpN * WMMA_N;

      // Bounds checking
      if (aRow < M && aCol < K && bRow < K && bCol < N) {
         // Load the inputs
         wmma::load_matrix_sync(a_frag, a + aRow * lda+ aCol , lda);
         wmma::load_matrix_sync(b_frag, b + bRow * ldb+ bCol , ldb);
 
         // Perform the matrix multiplication
         wmma::mma_sync(acc_frag, a_frag, b_frag, acc_frag);

      }
   }

   // Load in the current value of c, scale it by beta, and add this our result scaled by alpha
   int cRow = warpM * WMMA_M;
   int cCol = warpN * WMMA_N;

   if (cRow < M && cCol < N) {
      wmma::load_matrix_sync(c_frag, c + cRow*ldc + cCol , ldc, wmma::mem_row_major);


      for(int i=0; i < c_frag.num_elements; i++) {
         c_frag.x[i] = alpha * acc_frag.x[i] + beta * c_frag.x[i];
      }

      // Store the output
      wmma::store_matrix_sync(c + cRow *ldc + cCol , c_frag, ldc, wmma::mem_row_major);
   }
}

__global__ void convertFp32ToFp16 (half *out, float *in, int n) {
   int idx = blockDim.x * blockIdx.x + threadIdx.x;
   if (idx < n) {
      out[idx] = in[idx];
   }
}

int main(int argc, char* argv[]) {
   float *a_fp32;
   float *b_fp32;
   half *a_fp16;
   half *b_fp16;

   float *c;
   float *c_wmma;

   float *d_host_wmma;
   float *d_cal_host_wmma;
   float *a_host_wmma;
   float *b_host_wmma;
   float *c_host_wmma;
   
   
   cudaEvent_t startWMMA;
   cudaEvent_t stopWMMA;
   
   
   cudaErrCheck(cudaEventCreate(&startWMMA));
   cudaErrCheck(cudaEventCreate(&stopWMMA));
   
   // Use tensor cores
   cudaErrCheck(cudaMalloc((void**)&a_fp32, MATRIX_M * MATRIX_K * sizeof(float)));
   cudaErrCheck(cudaMalloc((void**)&b_fp32, MATRIX_K * MATRIX_N * sizeof(float)));
   cudaErrCheck(cudaMalloc((void**)&a_fp16, MATRIX_M * MATRIX_K * sizeof(half)));
   cudaErrCheck(cudaMalloc((void**)&b_fp16, MATRIX_K * MATRIX_N * sizeof(half)));

   cudaErrCheck(cudaMalloc((void**)&c, MATRIX_M * MATRIX_N * sizeof(float)));
   cudaErrCheck(cudaMalloc((void**)&c_wmma, MATRIX_M * MATRIX_N * sizeof(float)));

   d_host_wmma      = (float*)malloc(MATRIX_M * MATRIX_N * sizeof(float));
   d_cal_host_wmma      = (float*)malloc(MATRIX_M * MATRIX_N * sizeof(float));
   c_host_wmma = (float*)malloc(MATRIX_M * MATRIX_N * sizeof(float));
   a_host_wmma      = (float*)malloc(MATRIX_M * MATRIX_K * sizeof(float));
   b_host_wmma      = (float*)malloc(MATRIX_K * MATRIX_N * sizeof(float));


   printf("INITIAL_MATRIX_A\n"); 
   for(int m=0;m<MATRIX_M;m++){
	for(int n=0;n<MATRIX_K;n++){
		a_host_wmma[m*MATRIX_K+n]= (rand()%3);///3.0; 
		printf("%.2f ",a_host_wmma[m*MATRIX_K+n]);
	}
	printf("\n");
   }
   printf("INITIAL_MATRIX_B\n"); 
   for(int m=0;m<MATRIX_K;m++){
	for(int n=0;n<MATRIX_N;n++){
		b_host_wmma[m*MATRIX_N+n]=(rand()%3);///3.0;
		printf("%.2f ",b_host_wmma[m*MATRIX_K+n]);
	}
	printf("\n");
   }
   printf("INITIAL_MATRIX_C\n"); 
   for(int m=0;m<MATRIX_M;m++){
	for(int n=0;n<MATRIX_N;n++){
		c_host_wmma[m*MATRIX_N+n]= (rand()%3);///3.0;
		printf("%.2f ",c_host_wmma[m*MATRIX_K+n]);
	}
	printf("\n");
   }

   cudaErrCheck(cudaMemcpy(a_fp32,a_host_wmma,  MATRIX_M * MATRIX_K * sizeof(float), cudaMemcpyHostToDevice));
   cudaErrCheck(cudaMemcpy(b_fp32,b_host_wmma,  MATRIX_K * MATRIX_N * sizeof(float), cudaMemcpyHostToDevice));

   convertFp32ToFp16 <<< (MATRIX_M * MATRIX_K + 255) / 256, 256 >>> (a_fp16, a_fp32, MATRIX_M * MATRIX_K);
   convertFp32ToFp16 <<< (MATRIX_K * MATRIX_N + 255) / 256, 256 >>> (b_fp16, b_fp32, MATRIX_K * MATRIX_N);

   cudaErrCheck(cudaMemcpy(c, c_host_wmma,  MATRIX_M * MATRIX_N * sizeof(float), cudaMemcpyHostToDevice));
   cudaErrCheck(cudaMemcpy(c_wmma, c, MATRIX_M * MATRIX_N * sizeof(float), cudaMemcpyDeviceToDevice));

   float alpha = 1.0f;
   float beta = 1.0f;


   printf("\nM = %d, N = %d, K = %d. alpha = %f, beta = %f\n\n", MATRIX_M, MATRIX_N, MATRIX_K, alpha, beta);
   
   // First: using WMMA
   dim3 gridDim;
   dim3 blockDim;
 
   // blockDim.x must be a multple of warpSize
   // 128x4 means we have 16 warps and a block computes a 64x64 output tile
   blockDim.x = 64;
   blockDim.y = 2;

   gridDim.x = (MATRIX_M + (WMMA_M * blockDim.x / 32 - 1)) / (WMMA_M * blockDim.x / 32);
   gridDim.y = (MATRIX_N + WMMA_N * blockDim.y - 1) / (WMMA_N * blockDim.y);
   printf("GRID:X=%d,Y=%d\n",gridDim.x,gridDim.y);
   printf("BLOCK:X=%d,Y=%d\n",blockDim.x,blockDim.y);
   
   printf("Running with wmma...\n");
   cudaErrCheck(cudaEventRecord(startWMMA));
   wmma_example <<< gridDim, blockDim >>> (a_fp16, b_fp16, c_wmma, MATRIX_M, MATRIX_N, MATRIX_K, alpha, beta);
   cudaErrCheck(cudaEventRecord(stopWMMA));
   cudaErrCheck(cudaEventSynchronize(stopWMMA));

   printf("\nChecking results...\n");
   cudaErrCheck(cudaMemcpy(d_host_wmma, c_wmma, MATRIX_M * MATRIX_N * sizeof(float), cudaMemcpyDeviceToHost));
   
   int t=200000000;  
   while(t-->0);
 
   for(int m=0;m<MATRIX_M;m++){
	for(int n=0;n<MATRIX_N;n++){
		d_cal_host_wmma[m*MATRIX_N+n]=0;
		for(int k=0;k<MATRIX_K;k++){
			d_cal_host_wmma[m*MATRIX_N+n]+=	a_host_wmma[m*MATRIX_K+k]*b_host_wmma[k*MATRIX_K+n];
		}
		d_cal_host_wmma[m*MATRIX_N+n]+=c_host_wmma[m*MATRIX_N+n];
	}
   }
   printf("cal:d\n"); 
   for(int m=0;m<MATRIX_M;m++){
	for(int n=0;n<MATRIX_N;n++){
		printf("%.2f ",d_cal_host_wmma[m*MATRIX_K+n]);
	}
	printf("\n");
  }
   printf("wmma:d\n"); 
   for(int m=0;m<MATRIX_M;m++){
	for(int n=0;n<MATRIX_N;n++){
		printf("%.2f ",d_host_wmma[m*MATRIX_K+n]);
	}
	printf("\n");
   }
   int suc=1;
   float relative_error;
   for(int m=0;m<MATRIX_M;m++){
	for(int n=0;n<MATRIX_N;n++){
 		relative_error=100*abs(d_cal_host_wmma[m*MATRIX_N+n]-d_host_wmma[m*MATRIX_N+n])/d_host_wmma[m*MATRIX_N+n];
		printf("relative_error=%f\n",relative_error);
		if((int)relative_error>1)
		{	
			printf("ERROR:\n");
			suc=0;
			printf("ROW=%d,COL=%d:cpu=%f,gpgpusim=%f\n",m,n,d_cal_host_wmma[m*MATRIX_N+n],d_host_wmma[m*MATRIX_N+n]);
		}
	}
   }
   if(suc==1)
	printf("COMPLETED_SUCCESSFULLY\n");
   
   //int errors = 0;
   //for (int i = 0; i < MATRIX_M * MATRIX_N; i++) {
   //   float v1 = c_host_wmma[i];
   //   float v2 = c_host_cublas[i];
   //   if (v1 / v2 > 1.0001 || v2 / v1 > 1.0001 || abs(v1 - v2) > 1e-5) {
   //      errors++;
   //      if (errors < 10) printf("%f %f\n", v1, v2);
   //   }
   //}
   
   float wmmaTime;
   cudaErrCheck(cudaEventElapsedTime(&wmmaTime, startWMMA, stopWMMA));
   printf("wmma took %fms\n", wmmaTime);
   
   cudaErrCheck(cudaEventDestroy(startWMMA));
   cudaErrCheck(cudaEventDestroy(stopWMMA));
   cudaErrCheck(cudaFree(a_fp32));
   cudaErrCheck(cudaFree(b_fp32));
   cudaErrCheck(cudaFree(a_fp16));
   cudaErrCheck(cudaFree(b_fp16));
   cudaErrCheck(cudaFree(c));
   cudaErrCheck(cudaFree(c_wmma));
   free(d_host_wmma);
   free(c_host_wmma);
   cudaErrCheck(cudaDeviceReset());
   return 0;
}