SparseConvNet/cudaUtilities.h at master · SpiderMonkey1975/SparseConvNet · GitHub

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#pragma once
#include <cublas_v2.h>
#include <vector>
#include <iostream>
//Utilities to
//// check for CUDA errors,
//// use cublasSgemm for row-major matrix multiplication,
////  ...


// https://gist.github.com/ashwin/2652488#file-cudaerrorcheck-cu
// Define this to turn on error checking
#define CUDA_ERROR_CHECK

#define cudaSafeCall( err ) __cudaSafeCall( err, __FILE__, __LINE__ )
#define cudaCheckError() { __cudaCheckError( __FILE__, __LINE__ ); }

inline void __cudaSafeCall( cudaError err, const char *file, const int line )
{
#ifdef CUDA_ERROR_CHECK
  if ( cudaSuccess != err )
    {
      std::cout << "cudaSafeCall() failed at " << file <<":" <<line<< " " << cudaGetErrorString( err )<<"\n"<<std::flush;
      exit( -1 );
    }
#endif
  return;
}

inline void __cudaCheckError( const char *file, const int line ) {
#ifdef CUDA_ERROR_CHECK
  cudaError err = cudaGetLastError();
  if ( cudaSuccess != err )
    {
      std::cout << "cudaCheckError() failed at " << file <<":" <<line<< " " << cudaGetErrorString( err )<<"\n"<<std::flush;
      exit( -1 );
    }

  // More careful checking. However, this will affect performance. Comment away if needed.
  err = cudaDeviceSynchronize();
  if( cudaSuccess != err )
    {
      std::cout << "cudaCheckError() failed at " << file <<":" <<line<< " " << cudaGetErrorString( err )<<"\n"<<std::flush;
      exit( -1 );
    }
#endif

  return;
}


static void cublasError(cublasStatus_t error,const char* file = 0, int linenumber = 0);

#define NTHREADS 512
#define KERNELBLOCKSIZE 32

#ifdef CUDAUTILITIES_CU
cublasHandle_t cublasHandle;
#else
extern cublasHandle_t cublasHandle;
#endif

int intRound(int a, int d);
int intRoundUp(int a, int d);


int initializeGPU( );

//////////////////////////////////////////////////////////////////////////////////////////////////
//GEMM for matrices in row major form. ///////////////////////////////////////////////////////////
//A is l*m, B is m*r, C is l*r. Set C to alpha A B + beta C.
void d_rowMajorSGEMM_alphaAB_betaC (cublasHandle_t handle,
                                    float* A, float* B, float* C,
                                    int l, int m, int r,
                                    float alpha, float beta, const char* file = 0, int linenumber = 0);
//A^t is l*m, B is m*r, C is l*r
void d_rowMajorSGEMM_alphaAtB_betaC (cublasHandle_t handle,
                                     float* A, float* B, float* C,
                                     int l, int m, int r,
                                     float alpha, float beta, const char* file = 0, int linenumber = 0);
//A is l*m, B^t is m*r, C is l*r
void d_rowMajorSGEMM_alphaABt_betaC (cublasHandle_t handle,
                                     float* A, float* B, float* C,
                                     int l, int m, int r,
                                     float alpha, float beta, const char* file = 0, int linenumber = 0);
//A^t is l*m, B^t is m*r, C is l*r
void d_rowMajorSGEMM_alphaAtBt_betaC (cublasHandle_t handle,
                                      float* A, float* B, float* C,
                                      int l, int m, int r,
                                      float alpha, float beta, const char* file = 0, int linenumber = 0);
///////////////////////////////////////////////////////////////////////////////////////////////////

class cudaMemStream {
public:
  int pinnedMemorySize;
  void* pinnedMemory;
  cudaStream_t stream;
  cudaMemStream();
  ~cudaMemStream();
};

#ifdef CUDAUTILITIES_CU
cudaMemStream *cnnMemStream;
#else
extern cudaMemStream *cnnMemStream;
#endif