tsgGpuWrappers.hpp File Reference

Wrappers to GPU functionality. More...

#include "tsgAcceleratedDataStructures.hpp"

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Namespaces
	TasGrid
	Encapsulates the Tasmanian Sparse Grid module.
	TasGrid::TasGpu
	Wrappers around custom CUDA kernels to handle domain transforms and basis evaluations, the kernels are instantiated in tsgCudaKernels.cu.

Functions
template<typename scalar_type >
void	TasGrid::TasGpu::solveLSmultiGPU (AccelerationContext const *acceleration, int n, int m, scalar_type A[], int nrhs, scalar_type B[])
	Least squares solver with data sitting on the gpu device. More...
template<typename scalar_type >
void	TasGrid::TasGpu::solveLSmultiOOC (AccelerationContext const *acceleration, int n, int m, scalar_type A[], int nrhs, scalar_type B[])
	Identical to TasGpu::solveLSmultiGPU() but the arrays are on the CPU and the MAGMA out-of-core implementation is used.
template<typename scalar_type >
void	TasGrid::TasGpu::solveLSmulti (AccelerationContext const *acceleration, int n, int m, scalar_type A[], int nrhs, scalar_type B[])
	Identical to TasGpu::solveLSmultiGPU() but the data starts with the CPU and gets uploaded to the GPU first.
void	TasGrid::TasGpu::factorizePLU (AccelerationContext const *acceleration, int n, double A[], int_gpu_lapack ipiv[])
	Factorize , arrays are on the GPU.
void	TasGrid::TasGpu::solvePLU (AccelerationContext const *acceleration, char trans, int n, double const A[], int_gpu_lapack const ipiv[], double b[])
	Solve A x = b using a PLU factorization.
void	TasGrid::TasGpu::solvePLU (AccelerationContext const *acceleration, char trans, int n, double const A[], int_gpu_lapack const ipiv[], int nrhs, double B[])
	Solve A x = b using a PLU factorization, B is in row-major format.
template<typename scalar_type >
void	TasGrid::TasGpu::denseMultiply (AccelerationContext const *acceleration, int M, int N, int K, typename GpuVector< scalar_type >::value_type alpha, GpuVector< scalar_type > const &A, GpuVector< scalar_type > const &B, typename GpuVector< scalar_type >::value_type beta, scalar_type C[])
	Wrapper to GPU BLAS that multiplies dense matrices (e.g., cuBlas, MAGMA). More...
template<typename scalar_type >
void	TasGrid::TasGpu::denseMultiplyMixed (AccelerationContext const *acceleration, int M, int N, int K, typename GpuVector< scalar_type >::value_type alpha, GpuVector< scalar_type > const &A, scalar_type const B[], typename GpuVector< scalar_type >::value_type beta, scalar_type C[])
	Identical to TasGpu::denseMultiply() but both B and C are array in CPU memory.
template<typename scalar_type >
void	TasGrid::TasGpu::sparseMultiply (AccelerationContext const *acceleration, int M, int N, int K, typename GpuVector< scalar_type >::value_type alpha, const GpuVector< scalar_type > &A, const GpuVector< int > &pntr, const GpuVector< int > &indx, const GpuVector< scalar_type > &vals, scalar_type C[])
	Wrapper to GPU methods that multiplies a sparse and a dense matrix. More...
template<typename T >
void	TasGrid::TasGpu::sparseMultiplyMixed (AccelerationContext const *acceleration, int M, int N, int K, typename GpuVector< T >::value_type alpha, const GpuVector< T > &A, const std::vector< int > &pntr, const std::vector< int > &indx, const std::vector< T > &vals, T C[])
	Identical to TasGpu::sparseMultiply() but the sparse matrix and the result C are in CPU memory.

Detailed Description

Wrappers to GPU functionality.

Author

Miroslav Stoyanov

The header contains definitions of various operations that can be performed on the GPU devices with the corresponding GPU backend.