Commit 045f5578 authored by Jakub Klinkovský's avatar Jakub Klinkovský
Browse files

Changed the return type of Cuda::checkDevice from bool to void 

The method was either returning true or throwing an exception, so it can
simply return void or throw an exception.
parent c52122bd

src/TNL/Containers/Algorithms/ArrayOperationsCuda_impl.h

+29 −29
Original line number Diff line number Diff line
@@ -11,6 +11,7 @@ 
#pragma once



#include <iostream>

#include <memory>



#include <TNL/tnlConfig.h>

#include <TNL/Math.h>
@@ -112,7 +113,8 @@ setMemory( Element* data, 
   Index blocksNumber = ceil( ( double ) size / ( double ) blockSize. x );

   gridSize. x = min( blocksNumber, Devices::Cuda::getMaxGridSize() );

   setArrayValueCudaKernel<<< gridSize, blockSize >>>( data, size, value );

   return TNL_CHECK_CUDA_DEVICE;

   TNL_CHECK_CUDA_DEVICE;

   return true;

#else

   throw Exceptions::CudaSupportMissing();

#endif
@@ -155,7 +157,8 @@ copyMemory( DestinationElement* destination, 
                  source,

                  size * sizeof( DestinationElement ),

                  cudaMemcpyDeviceToDevice );

      return TNL_CHECK_CUDA_DEVICE;

      TNL_CHECK_CUDA_DEVICE;

      return true;

   }

   else

   {
@@ -164,7 +167,8 @@ copyMemory( DestinationElement* destination, 
      Index blocksNumber = ceil( ( double ) size / ( double ) blockSize. x );

      gridSize. x = min( blocksNumber, Devices::Cuda::getMaxGridSize() );

      copyMemoryCudaToCudaKernel<<< gridSize, blockSize >>>( destination, source, size );

      return TNL_CHECK_CUDA_DEVICE;

      TNL_CHECK_CUDA_DEVICE;

      return true;

   }

#else

   throw Exceptions::CudaSupportMissing();
@@ -248,22 +252,23 @@ copyMemory( DestinationElement* destination, 
                      size * sizeof( DestinationElement ),

                      cudaMemcpyDeviceToHost ) != cudaSuccess )

         std::cerr << "Transfer of data from CUDA device to host failed." << std::endl;

      return TNL_CHECK_CUDA_DEVICE;

      TNL_CHECK_CUDA_DEVICE;

      return true;

   }

   else

   {

      SourceElement* buffer = new SourceElement[ Devices::Cuda::getGPUTransferBufferSize() ];

      std::unique_ptr< SourceElement[] > buffer{ new SourceElement[ Devices::Cuda::getGPUTransferBufferSize() ] };

      Index i( 0 );

      while( i < size )

      {

         if( cudaMemcpy( buffer,

                         &source[ i ],

         if( cudaMemcpy( (void*) buffer.get(),

                         (void*) &source[ i ],

                         min( size - i, Devices::Cuda::getGPUTransferBufferSize() ) * sizeof( SourceElement ),

                         cudaMemcpyDeviceToHost ) != cudaSuccess )

         {

            delete[] buffer;

            std::cerr << "Transfer of data from CUDA device to host failed." << std::endl;

            return TNL_CHECK_CUDA_DEVICE;

            TNL_CHECK_CUDA_DEVICE;

            return true;

         }

         Index j( 0 );

         while( j < Devices::Cuda::getGPUTransferBufferSize() && i + j < size )
@@ -273,7 +278,6 @@ copyMemory( DestinationElement* destination, 
         }

         i += j;

      }

      delete[] buffer;

   }

   return true;

#else
@@ -298,28 +302,24 @@ compareMemory( const Element1* destination, 
   TNL_ASSERT_TRUE( source, "Attempted to compare data through a nullptr." );

   TNL_ASSERT_GE( size, 0, "Array size must be non-negative." );

#ifdef HAVE_CUDA

   Element2* host_buffer = new Element2[ Devices::Cuda::getGPUTransferBufferSize() ];

   std::unique_ptr< Element2[] > host_buffer{ new Element2[ Devices::Cuda::getGPUTransferBufferSize() ] };

   Index compared( 0 );

   while( compared < size )

   {

      Index transfer = min( size - compared, Devices::Cuda::getGPUTransferBufferSize() );

      if( cudaMemcpy( ( void* ) host_buffer,

                      ( void* ) & ( source[ compared ] ),

      if( cudaMemcpy( (void*) host_buffer.get(),

                      (void*) &source[ compared ],

                      transfer * sizeof( Element2 ),

                      cudaMemcpyDeviceToHost ) != cudaSuccess )

      {

         delete[] host_buffer;

         std::cerr << "Transfer of data from CUDA device to host failed." << std::endl;

         return TNL_CHECK_CUDA_DEVICE;

         TNL_CHECK_CUDA_DEVICE;

         return true;

      }

      if( ! ArrayOperations< Devices::Host >::compareMemory( &destination[ compared ], host_buffer, transfer ) )

      {

         delete[] host_buffer;

      if( ! ArrayOperations< Devices::Host >::compareMemory( &destination[ compared ], host_buffer.get(), transfer ) )

         return false;

      }

      compared += transfer;

   }

   delete[] host_buffer;

   return true;

#else

   throw Exceptions::CudaSupportMissing();
@@ -349,11 +349,12 @@ copyMemory( DestinationElement* destination, 
                      size * sizeof( DestinationElement ),

                      cudaMemcpyHostToDevice ) != cudaSuccess )

         std::cerr << "Transfer of data from host to CUDA device failed." << std::endl;

      return TNL_CHECK_CUDA_DEVICE;

      TNL_CHECK_CUDA_DEVICE;

      return true;

   }

   else

   {

      DestinationElement* buffer = new DestinationElement[ Devices::Cuda::getGPUTransferBufferSize() ];

      std::unique_ptr< DestinationElement[] > buffer{ new DestinationElement[ Devices::Cuda::getGPUTransferBufferSize() ] };

      Index i( 0 );

      while( i < size )

      {
@@ -363,18 +364,17 @@ copyMemory( DestinationElement* destination, 
            buffer[ j ] = source[ i + j ];

            j++;

         }

         if( cudaMemcpy( &destination[ i ],

                         buffer,

         if( cudaMemcpy( (void*) &destination[ i ],

                         (void*) buffer.get(),

                         j * sizeof( DestinationElement ),

                         cudaMemcpyHostToDevice ) != cudaSuccess )

         {

            delete[] buffer;

            std::cerr << "Transfer of data from host to CUDA device failed." << std::endl;

            return TNL_CHECK_CUDA_DEVICE;

            TNL_CHECK_CUDA_DEVICE;

            return true;

         }

         i += j;

      }

      delete[] buffer;

      return true;

   }

#else

src/TNL/Containers/Algorithms/Multireduction_impl.h

+2 −1
Original line number Diff line number Diff line
@@ -146,7 +146,8 @@ reduce( Operation& operation, 
      std::cout << "   Multireduction of small data set on CPU took " << timer.getRealTime() << " sec. " << std::endl;

   #endif



   return TNL_CHECK_CUDA_DEVICE;

   TNL_CHECK_CUDA_DEVICE;

   return true;

#else

   throw Exceptions::CudaSupportMissing();

#endif

src/TNL/Containers/Algorithms/Reduction_impl.h

+3 −2
Original line number Diff line number Diff line
@@ -163,7 +163,8 @@ reduce( Operation& operation, 
      #endif

   }



   return TNL_CHECK_CUDA_DEVICE;

   TNL_CHECK_CUDA_DEVICE;

   return true;

#else

   throw Exceptions::CudaSupportMissing();

#endif

src/TNL/Devices/Cuda.cu

+4 −5
Original line number Diff line number Diff line
@@ -103,10 +103,9 @@ void Cuda::printThreadsSetup( const dim3& blockSize, 
}





bool Cuda::checkDevice( const char* file_name, int line, cudaError error )

void Cuda::checkDevice( const char* file_name, int line, cudaError error )

{

   if( error == cudaSuccess )

      return true;

   if( error != cudaSuccess )

      throw Exceptions::CudaRuntimeError( error, file_name, line );

}

src/TNL/Devices/Cuda.h

+2 −2
Original line number Diff line number Diff line
@@ -153,9 +153,9 @@ class Cuda 
    * of calling cudaGetLastError() inside the method.

    * We recommend to use macro 'TNL_CHECK_CUDA_DEVICE' defined bellow.

    */

   static bool checkDevice( const char* file_name, int line, cudaError error );

   static void checkDevice( const char* file_name, int line, cudaError error );

#else

   static bool checkDevice() { return false; };

   static void checkDevice() {}

#endif

   

   static void configSetup( Config::ConfigDescription& config, const String& prefix = "" );