Date: 2016-07-24T16:53:28+00:00

Actual source code: cusparsematimpl.h
petsc-3.7.3 2016-07-24
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4: #include <../src/vec/vec/impls/seq/seqcuda/cudavecimpl.h> 6: #if CUDA_VERSION>=4020 7: #include <cusparse_v2.h> 8: #else 9: #include <cusparse.h> 10: #endif 12: #include <algorithm> 13: #include <vector> 15: #include <thrust/device_vector.h> 16: #include <thrust/device_ptr.h> 17: #include <thrust/transform.h> 18: #include <thrust/functional.h> 20: #if defined(PETSC_USE_COMPLEX) 21: #if defined(PETSC_USE_REAL_SINGLE) 22: #define cusparse_solve(a,b,c,d,e,f,g,h,i,j,k) cusparseCcsrsv_solve((a),(b),(c),(cuComplex*)(d),(e),(cuComplex*)(f),(g),(h),(i),(cuComplex*)(j),(cuComplex*)(k)) 23: #define cusparse_analysis(a,b,c,d,e,f,g,h,i) cusparseCcsrsv_analysis((a),(b),(c),(d),(e),(cuComplex*)(f),(g),(h),(i)) 24: #define cusparse_csr_spmv(a,b,c,d,e,f,g,h,i,j,k,l,m) cusparseCcsrmv((a),(b),(c),(d),(e),(cuComplex*)(f),(g),(cuComplex*)(h),(i),(j),(cuComplex*)(k),(cuComplex*)(l),(cuComplex*)(m)) 25: #define cusparse_csr2csc(a,b,c,d,e,f,g,h,i,j,k,l) cusparseCcsr2csc((a),(b),(c),(d),(cuComplex*)(e),(f),(g),(cuComplex*)(h),(i),(j),(k),(l)) 26: #define cusparse_hyb_spmv(a,b,c,d,e,f,g,h) cusparseChybmv((a),(b),(cuComplex*)(c),(d),(e),(cuComplex*)(f),(cuComplex*)(g),(cuComplex*)(h)) 27: #define cusparse_csr2hyb(a,b,c,d,e,f,g,h,i,j) cusparseCcsr2hyb((a),(b),(c),(d),(cuComplex*)(e),(f),(g),(h),(i),(j)) 28: #define cusparse_hyb2csr(a,b,c,d,e,f) cusparseChyb2csr((a),(b),(c),(cuComplex*)(d),(e),(f)) 29: cuFloatComplex ALPHA = {1.0f, 0.0f}; 30: cuFloatComplex BETA = {0.0f, 0.0f}; 31: #elif defined(PETSC_USE_REAL_DOUBLE) 32: #define cusparse_solve(a,b,c,d,e,f,g,h,i,j,k) cusparseZcsrsv_solve((a),(b),(c),(cuDoubleComplex*)(d),(e),(cuDoubleComplex*)(f),(g),(h),(i),(cuDoubleComplex*)(j),(cuDoubleComplex*)(k)) 33: #define cusparse_analysis(a,b,c,d,e,f,g,h,i) cusparseZcsrsv_analysis((a),(b),(c),(d),(e),(cuDoubleComplex*)(f),(g),(h),(i)) 34: #define cusparse_csr_spmv(a,b,c,d,e,f,g,h,i,j,k,l,m) cusparseZcsrmv((a),(b),(c),(d),(e),(cuDoubleComplex*)(f),(g),(cuDoubleComplex*)(h),(i),(j),(cuDoubleComplex*)(k),(cuDoubleComplex*)(l),(cuDoubleComplex*)(m)) 35: #define cusparse_csr2csc(a,b,c,d,e,f,g,h,i,j,k,l) cusparseZcsr2csc((a),(b),(c),(d),(cuDoubleComplex*)(e),(f),(g),(cuDoubleComplex*)(h),(i),(j),(k),(l)) 36: #define cusparse_hyb_spmv(a,b,c,d,e,f,g,h) cusparseZhybmv((a),(b),(cuDoubleComplex*)(c),(d),(e),(cuDoubleComplex*)(f),(cuDoubleComplex*)(g),(cuDoubleComplex*)(h)) 37: #define cusparse_csr2hyb(a,b,c,d,e,f,g,h,i,j) cusparseZcsr2hyb((a),(b),(c),(d),(cuDoubleComplex*)(e),(f),(g),(h),(i),(j)) 38: #define cusparse_hyb2csr(a,b,c,d,e,f) cusparseZhyb2csr((a),(b),(c),(cuDoubleComplex*)(d),(e),(f)) 39: cuDoubleComplex ALPHA = {1.0, 0.0}; 40: cuDoubleComplex BETA = {0.0, 0.0}; 41: #endif 42: #else 43: PetscScalar ALPHA = 1.0; 44: PetscScalar BETA = 0.0; 45: #if defined(PETSC_USE_REAL_SINGLE) 46: #define cusparse_solve cusparseScsrsv_solve 47: #define cusparse_analysis cusparseScsrsv_analysis 48: #define cusparse_csr_spmv cusparseScsrmv 49: #define cusparse_csr2csc cusparseScsr2csc 50: #define cusparse_hyb_spmv cusparseShybmv 51: #define cusparse_csr2hyb cusparseScsr2hyb 52: #define cusparse_hyb2csr cusparseShyb2csr 53: #elif defined(PETSC_USE_REAL_DOUBLE) 54: #define cusparse_solve cusparseDcsrsv_solve 55: #define cusparse_analysis cusparseDcsrsv_analysis 56: #define cusparse_csr_spmv cusparseDcsrmv 57: #define cusparse_csr2csc cusparseDcsr2csc 58: #define cusparse_hyb_spmv cusparseDhybmv 59: #define cusparse_csr2hyb cusparseDcsr2hyb 60: #define cusparse_hyb2csr cusparseDhyb2csr 61: #endif 62: #endif 64: #define THRUSTINTARRAY32 thrust::device_vector<int> 65: #define THRUSTINTARRAY thrust::device_vector<PetscInt> 66: #define THRUSTARRAY thrust::device_vector<PetscScalar> 68: /* A CSR matrix structure */ 69: struct CsrMatrix { 70: PetscInt num_rows; 71: PetscInt num_cols; 72: PetscInt num_entries; 73: THRUSTINTARRAY32 *row_offsets; 74: THRUSTINTARRAY32 *column_indices; 75: THRUSTARRAY *values; 76: }; 78: //#define CUSPMATRIXCSR32 cusp::csr_matrix<int,PetscScalar,cusp::device_memory> 80: /* This is struct holding the relevant data needed to a MatSolve */ 81: struct Mat_SeqAIJCUSPARSETriFactorStruct { 82: /* Data needed for triangular solve */ 83: cusparseMatDescr_t descr; 84: cusparseSolveAnalysisInfo_t solveInfo; 85: cusparseOperation_t solveOp; 86: CsrMatrix *csrMat; 87: }; 89: /* This is struct holding the relevant data needed to a MatMult */ 90: struct Mat_SeqAIJCUSPARSEMultStruct { 91: void *mat; /* opaque pointer to a matrix. This could be either a cusparseHybMat_t or a CsrMatrix */ 92: cusparseMatDescr_t descr; /* Data needed to describe the matrix for a multiply */ 93: THRUSTINTARRAY *cprowIndices; /* compressed row indices used in the parallel SpMV */ 94: PetscScalar *alpha; /* pointer to a device "scalar" storing the alpha parameter in the SpMV */ 95: PetscScalar *beta; /* pointer to a device "scalar" storing the beta parameter in the SpMV */ 96: }; 98: /* This is a larger struct holding all the triangular factors for a solve, transpose solve, and 99: any indices used in a reordering */ 100: struct Mat_SeqAIJCUSPARSETriFactors { 101: Mat_SeqAIJCUSPARSETriFactorStruct *loTriFactorPtr; /* pointer for lower triangular (factored matrix) on GPU */ 102: Mat_SeqAIJCUSPARSETriFactorStruct *upTriFactorPtr; /* pointer for upper triangular (factored matrix) on GPU */ 103: Mat_SeqAIJCUSPARSETriFactorStruct *loTriFactorPtrTranspose; /* pointer for lower triangular (factored matrix) on GPU for the transpose (useful for BiCG) */ 104: Mat_SeqAIJCUSPARSETriFactorStruct *upTriFactorPtrTranspose; /* pointer for upper triangular (factored matrix) on GPU for the transpose (useful for BiCG)*/ 105: THRUSTINTARRAY *rpermIndices; /* indices used for any reordering */ 106: THRUSTINTARRAY *cpermIndices; /* indices used for any reordering */ 107: THRUSTARRAY *workVector; 108: cusparseHandle_t handle; /* a handle to the cusparse library */ 109: PetscInt nnz; /* number of nonzeros ... need this for accurate logging between ICC and ILU */ 110: }; 112: /* This is a larger struct holding all the matrices for a SpMV, and SpMV Tranpose */ 113: struct Mat_SeqAIJCUSPARSE { 114: Mat_SeqAIJCUSPARSEMultStruct *mat; /* pointer to the matrix on the GPU */ 115: Mat_SeqAIJCUSPARSEMultStruct *matTranspose; /* pointer to the matrix on the GPU (for the transpose ... useful for BiCG) */ 116: THRUSTARRAY *workVector; /*pointer to a workvector to which we can copy the relevant indices of a vector we want to multiply */ 117: PetscInt nonzerorow; /* number of nonzero rows ... used in the flop calculations */ 118: MatCUSPARSEStorageFormat format; /* the storage format for the matrix on the device */ 119: cudaStream_t stream; /* a stream for the parallel SpMV ... this is not owned and should not be deleted */ 120: cusparseHandle_t handle; /* a handle to the cusparse library ... this may not be owned (if we're working in parallel i.e. multiGPUs) */ 121: }; 123: PETSC_INTERN PetscErrorCode MatCUSPARSECopyToGPU(Mat); 124: PETSC_INTERN PetscErrorCode MatCUSPARSESetStream(Mat, const cudaStream_t stream); 125: PETSC_INTERN PetscErrorCode MatCUSPARSESetHandle(Mat, const cusparseHandle_t handle); 126: PETSC_INTERN PetscErrorCode MatCUSPARSEClearHandle(Mat); 127: #endif