Debuging benchmarks. (3fdeb2a6) · Commits · TNL / tnl-dev

tests/tnl-benchmarks.cpp

+3 −4

Original line number	Diff line number	Diff line
		@@ -18,8 +18,7 @@

		#include <core/tnlLongVectorHost.h>
		#include <core/tnlLongVectorCUDA.h>
		#include <../tests/unit-tests/core/tnl-cuda-kernels.h>
		//#include <tnl-benchmarks.h>
		#include <tnl-benchmarks.h>


		int main( int argc, char* argv[] )
		@@ -33,7 +32,7 @@ int main( int argc, char* argv[] )
		double host_to_device_band_width;
		double device_to_host_band_width;
		double device_to_device_band_width;
		/*

		transferBenchmark< int >( size,
		host_to_host_band_width,
		host_to_device_band_width,
		@@ -52,7 +51,7 @@ int main( int argc, char* argv[] )
		cout << "Benchmarking reduction of double ..." << endl;
		for( int i = 0; i <= 6; i ++ )
		reductionBenchmark< double >( size / 2, i );
		*/

		#endif
		return EXIT_SUCCESS;
		}

tests/tnl-benchmarks.h

+39 −38

Original line number	Diff line number	Diff line
		@@ -19,7 +19,8 @@
		#define TNLBENCHMARKS_H_

		#include <core/mfuncs.h>
		#include <core/tnlTimerCUDA.h>
		#include <core/tnlTimerCPU.h>
		#include <../tests/unit-tests/core/tnl-cuda-kernels.h>

		template< class T >
		bool transferBenchmark( const int size,
		@@ -41,7 +42,7 @@ bool transferBenchmark( const int size,
		long int bytes = cycles * size * sizeof( int );
		long int mega_byte = 1 << 20;

		tnlTimerCUDA timer;
		tnlTimerCPU timer;
		timer. Reset();
		for( int i = 0; i < cycles; i ++ )
		if( ! host_vector2. copyFrom( host_vector ) )
		@@ -147,87 +148,87 @@ void reductionBenchmark( const int size,
		tnlCPUReductionMax( host_vector, sum );
		case 1:
		tnlCUDASimpleReduction1Sum( size,
		device_vector. Data(),
		device_vector. getVector(),
		sum,
		device_aux. Data() );
		device_aux. getVector() );
		tnlCUDASimpleReduction1Min( size,
		device_vector. Data(),
		device_vector. getVector(),
		min,
		device_aux. Data() );
		device_aux. getVector() );
		tnlCUDASimpleReduction1Max( size,
		device_vector. Data(),
		device_vector. getVector(),
		max,
		device_aux. Data() );
		device_aux. getVector() );
		break;
		case 2:
		tnlCUDASimpleReduction2Sum( size,
		device_vector. Data(),
		device_vector. getVector(),
		sum,
		device_aux. Data() );
		device_aux. getVector() );
		tnlCUDASimpleReduction2Min( size,
		device_vector. Data(),
		device_vector. getVector(),
		min,
		device_aux. Data() );
		device_aux. getVector() );
		tnlCUDASimpleReduction2Max( size,
		device_vector. Data(),
		device_vector. getVector(),
		max,
		device_aux. Data() );
		device_aux. getVector() );
		break;
		case 3:
		tnlCUDASimpleReduction3Sum( size,
		device_vector. Data(),
		device_vector. getVector(),
		sum,
		device_aux. Data() );
		device_aux. getVector() );
		tnlCUDASimpleReduction3Min( size,
		device_vector. Data(),
		device_vector. getVector(),
		min,
		device_aux. Data() );
		device_aux. getVector() );
		tnlCUDASimpleReduction3Max( size,
		device_vector. Data(),
		device_vector. getVector(),
		max,
		device_aux. Data() );
		device_aux. getVector() );
		break;
		case 4:
		tnlCUDASimpleReduction4Sum( size,
		device_vector. Data(),
		device_vector. getVector(),
		sum,
		device_aux. Data() );
		device_aux. getVector() );
		tnlCUDASimpleReduction4Min( size,
		device_vector. Data(),
		device_vector. getVector(),
		min,
		device_aux. Data() );
		device_aux. getVector() );
		tnlCUDASimpleReduction4Max( size,
		device_vector. Data(),
		device_vector. getVector(),
		max,
		device_aux. Data() );
		device_aux. getVector() );
		break;
		case 5:
		tnlCUDASimpleReduction5Sum( size,
		device_vector. Data(),
		device_vector. getVector(),
		sum,
		device_aux. Data() );
		device_aux. getVector() );
		tnlCUDASimpleReduction5Min( size,
		device_vector. Data(),
		device_vector. getVector(),
		min,
		device_aux. Data() );
		device_aux. getVector() );
		tnlCUDASimpleReduction5Max( size,
		device_vector. Data(),
		device_vector. getVector(),
		max,
		device_aux. Data() );
		device_aux. getVector() );
		break;
		default:
		tnlCUDAReductionSum( size,
		device_vector. Data(),
		device_vector. getVector(),
		sum,
		device_aux. Data() );
		device_aux. getVector() );
		tnlCUDAReductionMin( size,
		device_vector. Data(),
		device_vector. getVector(),
		min,
		device_aux. Data() );
		device_aux. getVector() );
		tnlCUDAReductionMax( size,
		device_vector. Data(),
		device_vector. getVector(),
		max,
		device_aux. Data() );
		device_aux. getVector() );

		}
		}