Maneesh Gupta
411 lines
18 KiB
Plaintext
411 lines
18 KiB
Plaintext
// RUN: %run_test hipify "%s" "%t" %hipify_args %clang_args
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// CHECK: #include <hip/hip_runtime.h>
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// CHECK: #include <hipsparse.h>
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// CHECK: #include <hipblas.h>
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#include <cuda.h>
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#include <cusparse_v2.h>
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#include <cublas_v2.h>
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#include <cstring>
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#include <cassert>
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#include <cstdio>
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#define Min(x,y) ((x)<(y)?(x):(y))
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#define Max(x,y) ((x)>(y)?(x):(y))
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#define Abs(x) ((x)>(0)?(x):-(x))
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// CHECK: static void CudaCheckCore(hipError_t code, const char *file, int line) {
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static void CudaCheckCore(cudaError_t code, const char *file, int line) {
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// CHECK: if (code != hipSuccess) {
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if (code != cudaSuccess) {
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// CHECK: fprintf(stderr,"Cuda Error %d : %s %s %d\n", code, hipGetErrorString(code), file, line);
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fprintf(stderr,"Cuda Error %d : %s %s %d\n", code, cudaGetErrorString(code), file, line);
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exit(code);
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}
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}
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#define CudaCheck( test ) { CudaCheckCore((test), __FILE__, __LINE__); }
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// CHECK: #define CudaCheckAfterCall() { CudaCheckCore((hipGetLastError()), __FILE__, __LINE__); }
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#define CudaCheckAfterCall() { CudaCheckCore((cudaGetLastError()), __FILE__, __LINE__); }
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// CHECK: static const char * GetErrorString(hipsparseStatus_t error) {
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static const char * GetErrorString(cusparseStatus_t error) {
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switch (error) {
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// CHECK: case HIPSPARSE_STATUS_SUCCESS:
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case CUSPARSE_STATUS_SUCCESS:
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return "The operation completed successfully.";
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// CHECK: case HIPSPARSE_STATUS_NOT_INITIALIZED:
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case CUSPARSE_STATUS_NOT_INITIALIZED:
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return "The cuSPARSE library was not initialized. This is usually caused by the lack of a prior call, an error in the CUDA Runtime API called by the cuSPARSE routine, or an error in the hardware setup.\n" \
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"To correct: call cusparseCreate() prior to the function call; and check that the hardware, an appropriate version of the driver, and the cuSPARSE library are correctly installed.";
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// CHECK: case HIPSPARSE_STATUS_ALLOC_FAILED:
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case CUSPARSE_STATUS_ALLOC_FAILED:
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return "Resource allocation failed inside the cuSPARSE library. This is usually caused by a cudaMalloc() failure.\n"\
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"To correct: prior to the function call, deallocate previously allocated memory as much as possible.";
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// CHECK: case HIPSPARSE_STATUS_INVALID_VALUE:
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case CUSPARSE_STATUS_INVALID_VALUE:
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return "An unsupported value or parameter was passed to the function (a negative vector size, for example).\n"\
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"To correct: ensure that all the parameters being passed have valid values.";
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// CHECK: case HIPSPARSE_STATUS_ARCH_MISMATCH:
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case CUSPARSE_STATUS_ARCH_MISMATCH:
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return "The function requires a feature absent from the device architecture; usually caused by the lack of support for atomic operations or double precision.\n"\
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"To correct: compile and run the application on a device with appropriate compute capability, which is 1.1 for 32-bit atomic operations and 1.3 for double precision.";
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// CHECK: case HIPSPARSE_STATUS_MAPPING_ERROR:
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case CUSPARSE_STATUS_MAPPING_ERROR:
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return "An access to GPU memory space failed, which is usually caused by a failure to bind a texture.\n"\
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"To correct: prior to the function call, unbind any previously bound textures.";
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// CHECK: case HIPSPARSE_STATUS_EXECUTION_FAILED:
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case CUSPARSE_STATUS_EXECUTION_FAILED:
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return "The GPU program failed to execute. This is often caused by a launch failure of the kernel on the GPU, which can be caused by multiple reasons.\n"\
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"To correct: check that the hardware, an appropriate version of the driver, and the cuSPARSE library are correctly installed.";
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// CHECK: case HIPSPARSE_STATUS_INTERNAL_ERROR:
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case CUSPARSE_STATUS_INTERNAL_ERROR:
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return "An internal cuSPARSE operation failed. This error is usually caused by a cudaMemcpyAsync() failure.\n"\
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"To correct: check that the hardware, an appropriate version of the driver, and the cuSPARSE library are correctly installed. Also, check that the memory passed as a parameter to the routine is not being deallocated prior to the routine’s completion.";
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// CHECK: case HIPSPARSE_STATUS_MATRIX_TYPE_NOT_SUPPORTED:
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// CHECK: "To correct: check that the fields in hipsparseMatDescr_t descrA were set correctly.";
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case CUSPARSE_STATUS_MATRIX_TYPE_NOT_SUPPORTED:
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return "The matrix type is not supported by this function. This is usually caused by passing an invalid matrix descriptor to the function.\n"\
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"To correct: check that the fields in cusparseMatDescr_t descrA were set correctly.";
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}
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return "<unknown>";
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}
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// CHECK: static void CudaSparseCheckCore(hipsparseStatus_t code, const char *file, int line) {
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static void CudaSparseCheckCore(cusparseStatus_t code, const char *file, int line) {
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// CHECK: if (code != HIPSPARSE_STATUS_SUCCESS) {
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if (code != CUSPARSE_STATUS_SUCCESS) {
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fprintf(stderr,"Cuda Error %d : %s %s %d\n", code, GetErrorString(code), file, line);
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exit(code);
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}
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}
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#define CudaSparseCheck( test ) { CudaSparseCheckCore((test), __FILE__, __LINE__); }
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// Alloc and copy
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template <class ObjectType>
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ObjectType* allocAndCopy(const ObjectType src[], const int size) {
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ObjectType* dest = NULL;
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// CHECK: CudaCheck( hipMalloc(&dest,size*sizeof(ObjectType)) );
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CudaCheck( cudaMalloc(&dest,size*sizeof(ObjectType)) );
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// CHECK: CudaCheck( hipMemcpy(dest, src, size*sizeof(ObjectType), hipMemcpyHostToDevice ) );
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CudaCheck( cudaMemcpy(dest, src, size*sizeof(ObjectType), cudaMemcpyHostToDevice ) );
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return dest;
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}
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template <class ObjectType>
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ObjectType* alloc(const int size) {
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ObjectType* dest = NULL;
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// CHECK: CudaCheck( hipMalloc(&dest,size*sizeof(ObjectType)) );
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CudaCheck( cudaMalloc(&dest,size*sizeof(ObjectType)) );
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return dest;
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}
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template <class ObjectType>
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ObjectType* allocAndCopyPart(const ObjectType src[], const int size, const int allocSize) {
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ObjectType* dest = NULL;
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assert(size <= allocSize);
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// CHECK: CudaCheck( hipMalloc(&dest,allocSize*sizeof(ObjectType)) );
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// CHECK: CudaCheck( hipMemcpy(dest, src, size*sizeof(ObjectType), hipMemcpyHostToDevice ) );
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// CHECK: CudaCheck( hipMemset(&dest[size],0,(allocSize-size)*sizeof(ObjectType)) );
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CudaCheck( cudaMalloc(&dest,allocSize*sizeof(ObjectType)) );
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CudaCheck( cudaMemcpy(dest, src, size*sizeof(ObjectType), cudaMemcpyHostToDevice ) );
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CudaCheck( cudaMemset(&dest[size],0,(allocSize-size)*sizeof(ObjectType)) );
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return dest;
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}
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// COO part
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#include <algorithm>
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struct Ijv {
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int i, j;
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double v;
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};
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bool IjvComp(const Ijv& v1, const Ijv& v2) {
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return v1.i < v2.i || (v1.i == v2.i && v1.j < v2.j);
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}
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struct COOArrays {
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int m;
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int nnz;
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double *val;/*values(NNZ)*/
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int *rowind;/*i(NNZ)*/
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int *colind;/*j(NNZ)*/
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COOArrays() {
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val = NULL;
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rowind = NULL;
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colind = NULL;
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}
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~COOArrays() {
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delete[] val;
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delete[] rowind;
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delete[] colind;
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}
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void sortToRowMajor() {
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Ijv* ijvs = new Ijv[nnz];
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for(int idxCopy = 0 ; idxCopy < nnz ; ++idxCopy){
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ijvs[idxCopy].i = rowind[idxCopy];
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ijvs[idxCopy].j = colind[idxCopy];
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ijvs[idxCopy].v = val[idxCopy];
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}
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std::sort(ijvs, ijvs+nnz, IjvComp);
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for(int idxCopy = 0 ; idxCopy < nnz ; ++idxCopy){
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rowind[idxCopy] = ijvs[idxCopy].i;
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colind[idxCopy] = ijvs[idxCopy].j;
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val[idxCopy] = ijvs[idxCopy].v;
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}
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delete[] ijvs;
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}
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};
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void compute_COO(COOArrays& coo, double *x , double *y ) {
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for(int idxVal = 0 ; idxVal < coo.nnz ; ++idxVal){
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y[coo.rowind[idxVal]] += x[coo.colind[idxVal]] * coo.val[idxVal];
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}
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}
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// COO part
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struct CRSArrays {
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int m; //< the dim of the matrix
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int nnz;//< the number of nnz (== ia[m])
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double *cu_csrValA; //< the values (of size NNZ)
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int *cu_csrRowPtrA;//< the usual rowptr (of size m+1)
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int *cu_csrColIndA;//< the colidx of each NNZ (of size nnz)
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// CHECK: hipStream_t streamId;
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// CHECK: hipsparseHandle_t cusparseHandle;
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cudaStream_t streamId;
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cusparseHandle_t cusparseHandle;
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CRSArrays() {
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cu_csrValA = NULL;
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cu_csrRowPtrA = NULL;
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cu_csrColIndA = NULL;
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// Create sparse handle (needed to call sparse functions
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streamId = 0;
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// CHECK-NOT: hipsparseHandle = 0;
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cusparseHandle = 0;
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// CHECK: CudaSparseCheck(hipsparseCreate(&cusparseHandle));
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// CHECK: CudaSparseCheck(hipsparseSetStream(cusparseHandle, streamId));
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CudaSparseCheck(cusparseCreate(&cusparseHandle));
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CudaSparseCheck(cusparseSetStream(cusparseHandle, streamId));
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}
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~CRSArrays() {
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// CHECK: CudaCheck(hipFree(cu_csrValA));
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// CHECK: CudaCheck(hipFree(cu_csrRowPtrA));
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// CHECK: CudaCheck(hipFree(cu_csrColIndA));
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CudaCheck(cudaFree(cu_csrValA));
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CudaCheck(cudaFree(cu_csrRowPtrA));
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CudaCheck(cudaFree(cu_csrColIndA));
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// Destroy sparse handle
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// CHECK: CudaSparseCheck(hipsparseDestroy(cusparseHandle));
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CudaSparseCheck(cusparseDestroy(cusparseHandle));
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}
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};
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void COO_to_CRS(COOArrays& coo, CRSArrays* crs) {
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// We need COO to be sorted by row (and column)
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coo.sortToRowMajor();
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crs->m = coo.m;
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crs->nnz = coo.nnz;
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// Convert COO to CSR (it is just for the rows idx)
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crs->cu_csrRowPtrA = alloc<int>(coo.m+1);
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{
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int* cu_cooRowIndA = allocAndCopy(coo.rowind, coo.nnz);
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// CHECK: CudaSparseCheck(hipsparseXcoo2csr(crs->cusparseHandle, cu_cooRowIndA,
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// CHECK: coo.nnz, coo.m, crs->cu_csrRowPtrA, HIPSPARSE_INDEX_BASE_ZERO));
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CudaSparseCheck(cusparseXcoo2csr(crs->cusparseHandle, cu_cooRowIndA,
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coo.nnz, coo.m, crs->cu_csrRowPtrA, CUSPARSE_INDEX_BASE_ZERO));
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// CHECK: CudaCheck(hipFree(cu_cooRowIndA));
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CudaCheck(cudaFree(cu_cooRowIndA));
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}
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// Copy cols idx and values that are unchanged
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crs->cu_csrValA = allocAndCopy(coo.val, coo.nnz);
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crs->cu_csrColIndA = allocAndCopy(coo.colind, coo.nnz);
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}
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double compute_CRS( CRSArrays& crs, double *x , double *y) {
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// For blas 2 gemv y = alpha.x.A + Beta.y
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const double alpha = 1.0;
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const double beta = 0.0;
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// Copy input
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double* cu_x = allocAndCopy(x, crs.m);
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double* cu_y = allocAndCopy(y, crs.m);
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// Init matrix properties
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// CHECK: hipsparseMatDescr_t descr = 0;
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cusparseMatDescr_t descr = 0;
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// CHECK: CudaSparseCheck(hipsparseCreateMatDescr(&descr));
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CudaSparseCheck(cusparseCreateMatDescr(&descr));
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// CHECK: hipsparseSetMatType(descr,HIPSPARSE_MATRIX_TYPE_GENERAL);
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cusparseSetMatType(descr,CUSPARSE_MATRIX_TYPE_GENERAL);
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// CHECK: hipsparseSetMatIndexBase(descr,HIPSPARSE_INDEX_BASE_ZERO);
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cusparseSetMatIndexBase(descr,CUSPARSE_INDEX_BASE_ZERO);
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// Compute gemv
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float gemvComputeTume = 0;
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{
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// CHECK: hipEvent_t startTime, stopTime;
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// CHECK: hipEventCreate(&startTime);
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// CHECK: hipEventCreate(&stopTime);
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// CHECK: hipEventRecord(startTime, crs.streamId);
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cudaEvent_t startTime, stopTime;
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cudaEventCreate(&startTime);
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cudaEventCreate(&stopTime);
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cudaEventRecord(startTime, crs.streamId);
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// CHECK: CudaSparseCheck(hipsparseDcsrmv(crs.cusparseHandle, HIPSPARSE_OPERATION_NON_TRANSPOSE,
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CudaSparseCheck(cusparseDcsrmv(crs.cusparseHandle, CUSPARSE_OPERATION_NON_TRANSPOSE,
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crs.m, crs.m, crs.nnz, &alpha,
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descr, crs.cu_csrValA, crs.cu_csrRowPtrA,
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crs.cu_csrColIndA, cu_x, &beta, cu_y));
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// CHECK: hipEventRecord(stopTime, crs.streamId);
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// CHECK: hipEventSynchronize(stopTime);
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// CHECK: hipEventElapsedTime(&gemvComputeTume, startTime, stopTime);
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cudaEventRecord(stopTime, crs.streamId);
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cudaEventSynchronize(stopTime);
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cudaEventElapsedTime(&gemvComputeTume, startTime, stopTime);
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gemvComputeTume /=1000.0;
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}
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// Get back result
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// CHECK: CudaCheck( hipMemcpy(y, cu_y, crs.m*sizeof(double), hipMemcpyDeviceToHost ) );
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CudaCheck( cudaMemcpy(y, cu_y, crs.m*sizeof(double), cudaMemcpyDeviceToHost ) );
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// Dealloc vectors
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// CHECK: CudaCheck(hipFree(cu_x));
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// CHECK: CudaCheck(hipFree(cu_y));
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CudaCheck(cudaFree(cu_x));
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CudaCheck(cudaFree(cu_y));
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return gemvComputeTume;
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}
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// BCSR part
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struct BCRSArrays {
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int m;
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int nnz;
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int nbBlocks;
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int nbBlockRow;
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int blockSize;
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int* cu_bsrRowPtrC;
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int* cu_bsrColIndC;
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double* cu_bsrValC;
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// CHECK: hipStream_t streamId;
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cudaStream_t streamId;
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// CHECK: hipsparseHandle_t cusparseHandle;
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cusparseHandle_t cusparseHandle;
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BCRSArrays() {
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cu_bsrRowPtrC = NULL;
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cu_bsrColIndC = NULL;
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cu_bsrValC = NULL;
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// Create sparse handle (needed to call sparse functions
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streamId = 0;
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// CHECK: CudaSparseCheck(hipsparseCreate(&cusparseHandle));
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// CHECK: CudaSparseCheck(hipsparseSetStream(cusparseHandle, streamId));
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CudaSparseCheck(cusparseCreate(&cusparseHandle));
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CudaSparseCheck(cusparseSetStream(cusparseHandle, streamId));
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}
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~BCRSArrays() {
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// CHECK: CudaCheck(hipFree(cu_bsrRowPtrC));
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// CHECK: CudaCheck(hipFree(cu_bsrColIndC));
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// CHECK: CudaCheck(hipFree(cu_bsrValC));
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CudaCheck(cudaFree(cu_bsrRowPtrC));
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CudaCheck(cudaFree(cu_bsrColIndC));
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CudaCheck(cudaFree(cu_bsrValC));
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// Destroy sparse handle
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// CHECK: CudaSparseCheck(hipsparseDestroy(cusparseHandle));
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CudaSparseCheck(cusparseDestroy(cusparseHandle));
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}
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};
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void CRS_to_BCRS(CRSArrays& csr, BCRSArrays* bcrs, const int blockSize) {
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bcrs->m = csr.m;
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bcrs->nnz = csr.nnz;
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bcrs->blockSize = blockSize;
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bcrs->nbBlockRow = (csr.m + blockSize-1)/blockSize;
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// CHECK: hipMalloc((void**)&bcrs->cu_bsrRowPtrC, sizeof(int) *(bcrs->nbBlockRow+1));
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cudaMalloc((void**)&bcrs->cu_bsrRowPtrC, sizeof(int) *(bcrs->nbBlockRow+1));
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// CHECK: hipsparseMatDescr_t descr = 0;
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cusparseMatDescr_t descr = 0;
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// CHECK: CudaSparseCheck(hipsparseCreateMatDescr(&descr));
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// CHECK: hipsparseSetMatType(descr,HIPSPARSE_MATRIX_TYPE_GENERAL);
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// CHECK: hipsparseSetMatIndexBase(descr,HIPSPARSE_INDEX_BASE_ZERO);
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CudaSparseCheck(cusparseCreateMatDescr(&descr));
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cusparseSetMatType(descr,CUSPARSE_MATRIX_TYPE_GENERAL);
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cusparseSetMatIndexBase(descr,CUSPARSE_INDEX_BASE_ZERO);
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int nbNnzBlocks;
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// NOTE: cusparseXcsr2bsrNnz and CUSPARSE_DIRECTION_COLUMN (of type cusparseDirection_t) are yet unsupported by HIP
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// CHECK-NOT: hipsparseXcsr2bsrNnz(bcrs->cusparseHandle, HIPSPARSE_DIRECTION_COLUMN, csr.m, csr.m, descr, csr.cu_csrRowPtrA, csr.cu_csrColIndA,
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cusparseXcsr2bsrNnz(bcrs->cusparseHandle, CUSPARSE_DIRECTION_COLUMN, csr.m, csr.m, descr, csr.cu_csrRowPtrA, csr.cu_csrColIndA,
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blockSize, descr, bcrs->cu_bsrRowPtrC, &nbNnzBlocks);
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{
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int firstBlockIdx, lastBlockIdx;
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// CHECK: hipMemcpy(&lastBlockIdx, bcrs->cu_bsrRowPtrC+bcrs->nbBlockRow, sizeof(int), hipMemcpyDeviceToHost);
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// CHECK: hipMemcpy(&firstBlockIdx, bcrs->cu_bsrRowPtrC, sizeof(int), hipMemcpyDeviceToHost);
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cudaMemcpy(&lastBlockIdx, bcrs->cu_bsrRowPtrC+bcrs->nbBlockRow, sizeof(int), cudaMemcpyDeviceToHost);
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cudaMemcpy(&firstBlockIdx, bcrs->cu_bsrRowPtrC, sizeof(int), cudaMemcpyDeviceToHost);
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assert(firstBlockIdx == 0); // we are in base 0
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assert(nbNnzBlocks == lastBlockIdx - firstBlockIdx);
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}
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bcrs->nbBlocks = nbNnzBlocks;
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// CHECK: CudaCheck(hipMalloc((void**)&bcrs->cu_bsrColIndC, sizeof(int)*nbNnzBlocks));
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// CHECK: CudaCheck(hipMalloc((void**)&bcrs->cu_bsrValC, sizeof(double)*(blockSize*blockSize)*nbNnzBlocks));
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CudaCheck(cudaMalloc((void**)&bcrs->cu_bsrColIndC, sizeof(int)*nbNnzBlocks));
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CudaCheck(cudaMalloc((void**)&bcrs->cu_bsrValC, sizeof(double)*(blockSize*blockSize)*nbNnzBlocks));
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// NOTE: cusparseDcsr2bsr and CUSPARSE_DIRECTION_COLUMN (of type cusparseDirection_t) are yet unsupported by HIP
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// CHECK-NOT: hipsparseDcsr2bsr(bcrs->cusparseHandle, HIPSPARSE_DIRECTION_COLUMN,
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cusparseDcsr2bsr(bcrs->cusparseHandle, CUSPARSE_DIRECTION_COLUMN,
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csr.m, csr.m, descr, csr.cu_csrValA, csr.cu_csrRowPtrA, csr.cu_csrColIndA, blockSize, descr, bcrs->cu_bsrValC, bcrs->cu_bsrRowPtrC, bcrs->cu_bsrColIndC);
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}
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double compute_BSR(BCRSArrays& bcsr, double *x , double *y){
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// For blas 2 gemv y = alpha.x.A + Beta.y
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const double alpha = 1.0;
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const double beta = 0.0;
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// Copy input
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const int sizeMultipleBlockSize = ((bcsr.m+bcsr.blockSize-1)/bcsr.blockSize)*bcsr.blockSize;
|
||
double* cu_x = allocAndCopyPart(x, bcsr.m, sizeMultipleBlockSize);
|
||
double* cu_y = allocAndCopyPart(y, bcsr.m, sizeMultipleBlockSize);
|
||
// Init matrix properties
|
||
// CHECK: hipsparseMatDescr_t descr = 0;
|
||
// CHECK: CudaSparseCheck(hipsparseCreateMatDescr(&descr));
|
||
// CHECK: hipsparseSetMatType(descr,HIPSPARSE_MATRIX_TYPE_GENERAL);
|
||
// CHECK: hipsparseSetMatIndexBase(descr,HIPSPARSE_INDEX_BASE_ZERO);
|
||
cusparseMatDescr_t descr = 0;
|
||
CudaSparseCheck(cusparseCreateMatDescr(&descr));
|
||
cusparseSetMatType(descr,CUSPARSE_MATRIX_TYPE_GENERAL);
|
||
cusparseSetMatIndexBase(descr,CUSPARSE_INDEX_BASE_ZERO);
|
||
// Compute gemv
|
||
float gemvComputeTume = 0;
|
||
{
|
||
// CHECK: hipEvent_t startTime, stopTime;
|
||
// CHECK: hipEventCreate(&startTime);
|
||
// CHECK: hipEventCreate(&stopTime);
|
||
// CHECK: hipEventRecord(startTime, bcsr.streamId);
|
||
cudaEvent_t startTime, stopTime;
|
||
cudaEventCreate(&startTime);
|
||
cudaEventCreate(&stopTime);
|
||
cudaEventRecord(startTime, bcsr.streamId);
|
||
// CHECK: cusparseDbsrmv(bcsr.cusparseHandle, HIPSPARSE_DIRECTION_COLUMN, HIPSPARSE_OPERATION_NON_TRANSPOSE,
|
||
cusparseDbsrmv(bcsr.cusparseHandle, CUSPARSE_DIRECTION_COLUMN, CUSPARSE_OPERATION_NON_TRANSPOSE,
|
||
bcsr.nbBlockRow, bcsr.m, bcsr.nbBlocks, &alpha, descr,
|
||
bcsr.cu_bsrValC, bcsr.cu_bsrRowPtrC, bcsr.cu_bsrColIndC, bcsr.blockSize,
|
||
cu_x, &beta, cu_y);
|
||
// CHECK: hipEventRecord(stopTime, bcsr.streamId);
|
||
// CHECK: hipEventSynchronize(stopTime);
|
||
// CHECK: hipEventElapsedTime(&gemvComputeTume, startTime, stopTime);
|
||
cudaEventRecord(stopTime, bcsr.streamId);
|
||
cudaEventSynchronize(stopTime);
|
||
cudaEventElapsedTime(&gemvComputeTume, startTime, stopTime);
|
||
gemvComputeTume /=1000.0;
|
||
}
|
||
// Get back result
|
||
// CHECK: CudaCheck( hipMemcpy(y, cu_y, bcsr.m*sizeof(double), hipMemcpyDeviceToHost ) );
|
||
CudaCheck( cudaMemcpy(y, cu_y, bcsr.m*sizeof(double), cudaMemcpyDeviceToHost ) );
|
||
// Dealloc vectors
|
||
// CHECK: CudaCheck(hipFree(cu_x));
|
||
// CHECK: CudaCheck(hipFree(cu_y));
|
||
CudaCheck(cudaFree(cu_x));
|
||
CudaCheck(cudaFree(cu_y));
|
||
return gemvComputeTume;
|
||
}
|