derek.holloway
7502bf64a4
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1230 lines
58 KiB
C++
1230 lines
58 KiB
C++
/* ************************************************************************
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* Copyright (C) 2025 Advanced Micro Devices, Inc. All rights Reserved.
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*
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* Permission is hereby granted, free of charge, to any person obtaining a copy
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* of this software and associated documentation files (the Software), to deal
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* in the Software without restriction, including without limitation the rights
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* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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* copies of the Software, and to permit persons to whom the Software is
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* furnished to do so, subject to the following conditions:
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*
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* The above copyright notice and this permission notice shall be included in
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* all copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED AS IS, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
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* THE SOFTWARE.
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*
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* ************************************************************************ */
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#pragma once
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#include "auto_testing_bad_arg.hpp"
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#include "rocsparse_matrix_statistics.hpp"
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#include "testing_spmv_dispatch_traits.hpp"
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template <rocsparse_format FORMAT,
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typename I,
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typename J,
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typename A,
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typename X,
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typename Y,
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typename T>
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struct testing_v2_spmv_dispatch
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{
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private:
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using traits = testing_spmv_dispatch_traits<FORMAT, I, J, A, X, Y, T>;
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template <typename U>
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using host_sparse_matrix = typename traits::template host_sparse_matrix<U>;
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template <typename U>
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using device_sparse_matrix = typename traits::template device_sparse_matrix<U>;
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public:
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static void testing_v2_spmv_bad_arg(const Arguments& arg)
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{
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rocsparse_local_handle local_handle;
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rocsparse_handle handle = local_handle;
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rocsparse_spmv_descr descr = (rocsparse_spmv_descr)0x4;
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rocsparse_spmat_descr mat = (rocsparse_spmat_descr)0x4;
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const void* alpha = (const void*)0x4;
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const void* beta = (const void*)0x4;
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rocsparse_v2_spmv_stage stage = rocsparse_v2_spmv_stage_analysis;
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void* buffer = (void*)0x4;
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rocsparse_dnvec_descr x = (rocsparse_dnvec_descr)0x4;
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rocsparse_dnvec_descr y = (rocsparse_dnvec_descr)0x4;
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rocsparse_error* p_error = nullptr;
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{
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size_t* buffer_size_in_bytes = (size_t*)0x4;
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#define PARAMS_BUFFER_SIZE handle, descr, mat, x, y, stage, buffer_size_in_bytes, p_error
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static constexpr int nex = 1;
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static const int ex[nex] = {7};
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select_bad_arg_analysis(rocsparse_v2_spmv_buffer_size, nex, ex, PARAMS_BUFFER_SIZE);
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#undef PARAMS_BUFFER_SIZE
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}
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{
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const size_t buffer_size_in_bytes = 10;
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#define PARAMS handle, descr, alpha, mat, x, beta, y, stage, buffer_size_in_bytes, buffer, p_error
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static constexpr int nex = 2;
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static const int ex[nex] = {8, 10};
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select_bad_arg_analysis(rocsparse_v2_spmv, nex, ex, PARAMS);
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#undef PARAMS
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}
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}
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static void testing_v2_spmv(const Arguments& arg)
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{
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J M = arg.M;
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J N = arg.N;
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rocsparse_operation trans = arg.transA;
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rocsparse_index_base base = arg.baseA;
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rocsparse_spmv_alg alg = arg.spmv_alg;
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rocsparse_matrix_type matrix_type = arg.matrix_type;
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rocsparse_fill_mode uplo = arg.uplo;
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rocsparse_storage_mode storage = arg.storage;
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rocsparse_datatype ttype = get_datatype<T>();
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// Create rocsparse handle
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rocsparse_local_handle handle(arg);
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host_scalar<T> h_alpha(arg.get_alpha<T>());
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host_scalar<T> h_beta(arg.get_beta<T>());
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device_scalar<T> d_alpha(h_alpha);
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device_scalar<T> d_beta(h_beta);
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#define PARAMS(alpha_, A_, x_, beta_, y_, stage) \
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handle, trans, alpha_, A_, x_, beta_, y_, ttype, alg, stage, &buffer_size, dbuffer, nullptr
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//
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// INITIALIZATE THE SPARSE MATRIX
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//
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host_sparse_matrix<A> hA;
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{
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int dev;
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CHECK_HIP_ERROR(hipGetDevice(&dev));
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hipDeviceProp_t prop;
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CHECK_HIP_ERROR(hipGetDeviceProperties(&prop, dev));
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const bool has_datafile = rocsparse_arguments_has_datafile(arg);
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bool to_int = false;
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to_int |= (prop.warpSize == 32);
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to_int |= (alg != rocsparse_spmv_alg_csr_rowsplit);
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to_int |= (trans != rocsparse_operation_none && has_datafile);
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to_int |= (matrix_type == rocsparse_matrix_type_symmetric && has_datafile);
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static constexpr bool full_rank = false;
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rocsparse_matrix_factory<A, I, J> matrix_factory(
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arg, arg.unit_check ? to_int : false, full_rank);
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traits::sparse_initialization(matrix_factory, hA, M, N, base);
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}
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if((matrix_type == rocsparse_matrix_type_symmetric && M != N)
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|| (matrix_type == rocsparse_matrix_type_triangular && M != N))
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{
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return;
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}
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device_sparse_matrix<A> dA(hA);
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host_dense_matrix<X> hx((trans == rocsparse_operation_none) ? N : M, 1);
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rocsparse_matrix_utils::init_exact(hx);
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device_dense_matrix<X> dx(hx);
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host_dense_matrix<Y> hy((trans == rocsparse_operation_none) ? M : N, 1);
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rocsparse_matrix_utils::init_exact(hy);
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device_dense_matrix<Y> dy(hy);
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rocsparse_local_spmat matA(dA);
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rocsparse_local_dnvec x(dx);
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rocsparse_local_dnvec y(dy);
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EXPECT_ROCSPARSE_STATUS(
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rocsparse_spmat_set_attribute(
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matA, rocsparse_spmat_matrix_type, &matrix_type, sizeof(matrix_type)),
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rocsparse_status_success);
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EXPECT_ROCSPARSE_STATUS(
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rocsparse_spmat_set_attribute(matA, rocsparse_spmat_fill_mode, &uplo, sizeof(uplo)),
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rocsparse_status_success);
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EXPECT_ROCSPARSE_STATUS(rocsparse_spmat_set_attribute(
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matA, rocsparse_spmat_storage_mode, &storage, sizeof(storage)),
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rocsparse_status_success);
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CHECK_ROCSPARSE_ERROR(rocsparse_set_pointer_mode(handle, rocsparse_pointer_mode_host));
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// Run buffer size
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rocsparse_spmv_descr spmv_descr;
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CHECK_ROCSPARSE_ERROR(rocsparse_create_spmv_descr(&spmv_descr));
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CHECK_ROCSPARSE_ERROR(rocsparse_spmv_set_input(
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handle, spmv_descr, rocsparse_spmv_input_alg, &alg, sizeof(alg), nullptr));
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CHECK_ROCSPARSE_ERROR(rocsparse_spmv_set_input(
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handle, spmv_descr, rocsparse_spmv_input_operation, &trans, sizeof(trans), nullptr));
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CHECK_ROCSPARSE_ERROR(rocsparse_spmv_set_input(handle,
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spmv_descr,
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rocsparse_spmv_input_compute_datatype,
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&ttype,
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sizeof(ttype),
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nullptr));
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CHECK_ROCSPARSE_ERROR(rocsparse_spmv_set_input(handle,
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spmv_descr,
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rocsparse_spmv_input_scalar_datatype,
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&ttype,
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sizeof(ttype),
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nullptr));
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size_t buffer_size = 0;
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CHECK_ROCSPARSE_ERROR(rocsparse_v2_spmv_buffer_size(handle,
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spmv_descr,
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matA,
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x,
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y,
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rocsparse_v2_spmv_stage_analysis,
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&buffer_size,
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nullptr));
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void* dbuffer = nullptr;
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CHECK_HIP_ERROR(rocsparse_hipMalloc(&dbuffer, buffer_size));
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// Run analysis
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CHECK_ROCSPARSE_ERROR(rocsparse_v2_spmv(handle,
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spmv_descr,
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h_alpha,
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matA,
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x,
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h_beta,
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y,
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rocsparse_v2_spmv_stage_analysis,
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buffer_size,
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dbuffer,
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nullptr));
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CHECK_HIP_ERROR(rocsparse_hipFree(dbuffer));
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dbuffer = nullptr;
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CHECK_ROCSPARSE_ERROR(rocsparse_v2_spmv_buffer_size(handle,
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spmv_descr,
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matA,
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x,
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y,
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rocsparse_v2_spmv_stage_compute,
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&buffer_size,
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nullptr));
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CHECK_HIP_ERROR(rocsparse_hipMalloc(&dbuffer, buffer_size));
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if(arg.unit_check)
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{
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// Run solve
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CHECK_ROCSPARSE_ERROR(testing::rocsparse_v2_spmv(handle,
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spmv_descr,
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h_alpha,
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matA,
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x,
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h_beta,
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y,
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rocsparse_v2_spmv_stage_compute,
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buffer_size,
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dbuffer,
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nullptr));
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host_dense_matrix<Y> hy_copy(hy);
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traits::host_calculation(trans, h_alpha, hA, hx, h_beta, hy, alg, matrix_type);
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hy.near_check(dy);
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if(ROCSPARSE_REPRODUCIBILITY)
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{
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rocsparse_reproducibility::save("Y_pointer_mode_host", dy);
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}
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dy.transfer_from(hy_copy);
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CHECK_ROCSPARSE_ERROR(
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rocsparse_set_pointer_mode(handle, rocsparse_pointer_mode_device));
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CHECK_ROCSPARSE_ERROR(testing::rocsparse_v2_spmv(handle,
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spmv_descr,
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d_alpha,
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matA,
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x,
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d_beta,
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y,
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rocsparse_v2_spmv_stage_compute,
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buffer_size,
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dbuffer,
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nullptr));
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CHECK_ROCSPARSE_ERROR(rocsparse_set_pointer_mode(handle, rocsparse_pointer_mode_host));
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hy.near_check(dy);
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if(ROCSPARSE_REPRODUCIBILITY)
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{
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rocsparse_reproducibility::save("Y_pointer_mode_device", dy);
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}
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}
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if(arg.timing)
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{
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const double gpu_time_used
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= rocsparse_clients::run_benchmark(arg,
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rocsparse_v2_spmv,
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handle,
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spmv_descr,
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h_alpha,
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matA,
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x,
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h_beta,
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y,
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rocsparse_v2_spmv_stage_compute,
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buffer_size,
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dbuffer,
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nullptr);
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const double gflop_count = traits::gflop_count(hA, *h_beta != static_cast<T>(0));
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const double gbyte_count = traits::byte_count(hA, *h_beta != static_cast<T>(0));
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const double gpu_gflops = get_gpu_gflops(gpu_time_used, gflop_count);
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const double gpu_gbyte = get_gpu_gbyte(gpu_time_used, gbyte_count);
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if(arg.sparsity_pattern_statistics)
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{
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int64_t min_nnz_row;
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int64_t median_nnz_row;
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int64_t max_nnz_row;
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rocsparse_matrix_statistics::get_nnz_per_row(
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dA, min_nnz_row, median_nnz_row, max_nnz_row);
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int64_t min_nnz_col;
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int64_t median_nnz_col;
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int64_t max_nnz_col;
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rocsparse_matrix_statistics::get_nnz_per_column(
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dA, min_nnz_col, median_nnz_col, max_nnz_col);
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traits::display_info(arg,
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display_key_t::trans_A,
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rocsparse_operation2string(trans),
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dA,
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display_key_t::min_nnz_per_row,
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min_nnz_row,
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display_key_t::max_nnz_per_row,
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max_nnz_row,
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display_key_t::median_nnz_per_row,
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median_nnz_row,
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display_key_t::min_nnz_per_col,
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min_nnz_col,
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display_key_t::max_nnz_per_col,
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max_nnz_col,
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display_key_t::median_nnz_per_col,
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median_nnz_col,
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display_key_t::alpha,
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*h_alpha,
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display_key_t::beta,
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*h_beta,
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display_key_t::algorithm,
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rocsparse_spmvalg2string(alg),
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display_key_t::gflops,
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gpu_gflops,
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display_key_t::bandwidth,
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gpu_gbyte,
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display_key_t::time_ms,
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get_gpu_time_msec(gpu_time_used));
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}
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else
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{
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traits::display_info(arg,
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display_key_t::trans_A,
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rocsparse_operation2string(trans),
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dA,
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display_key_t::alpha,
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*h_alpha,
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display_key_t::beta,
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*h_beta,
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display_key_t::algorithm,
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rocsparse_spmvalg2string(alg),
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display_key_t::gflops,
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gpu_gflops,
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display_key_t::bandwidth,
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gpu_gbyte,
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display_key_t::time_ms,
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get_gpu_time_msec(gpu_time_used));
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}
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}
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CHECK_ROCSPARSE_ERROR(rocsparse_destroy_spmv_descr(spmv_descr));
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CHECK_HIP_ERROR(rocsparse_hipFree(dbuffer));
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}
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static void testing_v2_spmv_extra_bad_arg(const Arguments& arg)
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{
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rocsparse_spmv_descr descr = (rocsparse_spmv_descr)0x4;
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// Test bad arguments for rocsparse_spmv_clear_extra
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static constexpr int nex_clear = 3;
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static const int ex_clear[nex_clear] = {0, 1, 2}; // handle, descr, p_error
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select_bad_arg_analysis(rocsparse_spmv_clear_extra,
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nex_clear,
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ex_clear,
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(rocsparse_handle)0x4,
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descr,
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(rocsparse_error*)0x4);
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}
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static void testing_v2_spmv_extra(const Arguments& arg)
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{
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J M = arg.M;
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J N = arg.N;
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rocsparse_operation trans = arg.transA;
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rocsparse_index_base base = arg.baseA;
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rocsparse_spmv_alg alg = arg.spmv_alg;
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rocsparse_matrix_type matrix_type = arg.matrix_type;
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rocsparse_fill_mode uplo = arg.uplo;
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rocsparse_storage_mode storage = arg.storage;
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rocsparse_datatype ttype = get_datatype<T>();
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// Create rocsparse handle
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rocsparse_local_handle handle(arg);
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T gamma_val = static_cast<T>(0.5);
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host_scalar<T> h_alpha(arg.get_alpha<T>());
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host_scalar<T> h_beta(arg.get_beta<T>());
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host_scalar<T> h_gamma(static_cast<T>(gamma_val));
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device_scalar<T> d_alpha(h_alpha);
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device_scalar<T> d_beta(h_beta);
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device_scalar<T> d_gamma(h_gamma);
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//
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// INITIALIZATE THE SPARSE MATRIX
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//
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host_sparse_matrix<A> hA;
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{
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int dev;
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CHECK_HIP_ERROR(hipGetDevice(&dev));
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hipDeviceProp_t prop;
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CHECK_HIP_ERROR(hipGetDeviceProperties(&prop, dev));
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const bool has_datafile = rocsparse_arguments_has_datafile(arg);
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bool to_int = false;
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to_int |= (prop.warpSize == 32);
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to_int |= (alg != rocsparse_spmv_alg_csr_rowsplit);
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to_int |= (trans != rocsparse_operation_none && has_datafile);
|
|
to_int |= (matrix_type == rocsparse_matrix_type_symmetric && has_datafile);
|
|
static constexpr bool full_rank = false;
|
|
rocsparse_matrix_factory<A, I, J> matrix_factory(
|
|
arg, arg.unit_check ? to_int : false, full_rank);
|
|
traits::sparse_initialization(matrix_factory, hA, M, N, base);
|
|
}
|
|
|
|
if((matrix_type == rocsparse_matrix_type_symmetric && M != N)
|
|
|| (matrix_type == rocsparse_matrix_type_triangular && M != N))
|
|
{
|
|
return;
|
|
}
|
|
|
|
if(M == 0 || N == 0)
|
|
{
|
|
return;
|
|
}
|
|
|
|
device_sparse_matrix<A> dA(hA);
|
|
|
|
host_dense_matrix<X> hx((trans == rocsparse_operation_none) ? N : M, 1);
|
|
rocsparse_matrix_utils::init_exact(hx);
|
|
device_dense_matrix<X> dx(hx);
|
|
|
|
host_dense_matrix<Y> hy((trans == rocsparse_operation_none) ? M : N, 1);
|
|
rocsparse_matrix_utils::init_exact(hy);
|
|
device_dense_matrix<Y> dy(hy);
|
|
|
|
// Create extra vector
|
|
host_dense_matrix<X> h_extra((trans == rocsparse_operation_none) ? M : N, 1);
|
|
rocsparse_matrix_utils::init_exact(h_extra);
|
|
device_dense_matrix<X> d_extra(h_extra);
|
|
|
|
rocsparse_local_spmat matA(dA);
|
|
rocsparse_local_dnvec x(dx);
|
|
rocsparse_local_dnvec y(dy);
|
|
rocsparse_local_dnvec extra(d_extra);
|
|
|
|
EXPECT_ROCSPARSE_STATUS(
|
|
rocsparse_spmat_set_attribute(
|
|
matA, rocsparse_spmat_matrix_type, &matrix_type, sizeof(matrix_type)),
|
|
rocsparse_status_success);
|
|
|
|
EXPECT_ROCSPARSE_STATUS(
|
|
rocsparse_spmat_set_attribute(matA, rocsparse_spmat_fill_mode, &uplo, sizeof(uplo)),
|
|
rocsparse_status_success);
|
|
|
|
EXPECT_ROCSPARSE_STATUS(rocsparse_spmat_set_attribute(
|
|
matA, rocsparse_spmat_storage_mode, &storage, sizeof(storage)),
|
|
rocsparse_status_success);
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_set_pointer_mode(handle, rocsparse_pointer_mode_host));
|
|
|
|
// Run buffer size
|
|
rocsparse_spmv_descr spmv_descr;
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_create_spmv_descr(&spmv_descr));
|
|
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_spmv_set_input(
|
|
handle, spmv_descr, rocsparse_spmv_input_alg, &alg, sizeof(alg), nullptr));
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_spmv_set_input(
|
|
handle, spmv_descr, rocsparse_spmv_input_operation, &trans, sizeof(trans), nullptr));
|
|
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_spmv_set_input(handle,
|
|
spmv_descr,
|
|
rocsparse_spmv_input_compute_datatype,
|
|
&ttype,
|
|
sizeof(ttype),
|
|
nullptr));
|
|
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_spmv_set_input(handle,
|
|
spmv_descr,
|
|
rocsparse_spmv_input_scalar_datatype,
|
|
&ttype,
|
|
sizeof(ttype),
|
|
nullptr));
|
|
|
|
// Create gamma dnvec with host values
|
|
rocsparse_dnvec_descr gamma_vec;
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_create_dnvec_descr(&gamma_vec, 1, h_gamma, ttype));
|
|
|
|
rocsparse_const_dnvec_descr z_vecs[1] = {extra};
|
|
|
|
CHECK_ROCSPARSE_ERROR(
|
|
rocsparse_spmv_set_extra(handle, spmv_descr, 1, gamma_vec, z_vecs, nullptr));
|
|
|
|
size_t buffer_size = 0;
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_v2_spmv_buffer_size(handle,
|
|
spmv_descr,
|
|
matA,
|
|
x,
|
|
y,
|
|
rocsparse_v2_spmv_stage_analysis,
|
|
&buffer_size,
|
|
nullptr));
|
|
|
|
void* dbuffer = nullptr;
|
|
CHECK_HIP_ERROR(rocsparse_hipMalloc(&dbuffer, buffer_size));
|
|
|
|
// Run analysis
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_v2_spmv(handle,
|
|
spmv_descr,
|
|
h_alpha,
|
|
matA,
|
|
x,
|
|
h_beta,
|
|
y,
|
|
rocsparse_v2_spmv_stage_analysis,
|
|
buffer_size,
|
|
dbuffer,
|
|
nullptr));
|
|
|
|
CHECK_HIP_ERROR(rocsparse_hipFree(dbuffer));
|
|
dbuffer = nullptr;
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_v2_spmv_buffer_size(handle,
|
|
spmv_descr,
|
|
matA,
|
|
x,
|
|
y,
|
|
rocsparse_v2_spmv_stage_compute,
|
|
&buffer_size,
|
|
nullptr));
|
|
CHECK_HIP_ERROR(rocsparse_hipMalloc(&dbuffer, buffer_size));
|
|
|
|
if(arg.unit_check)
|
|
{
|
|
// Run solve
|
|
CHECK_ROCSPARSE_ERROR(testing::rocsparse_v2_spmv(handle,
|
|
spmv_descr,
|
|
h_alpha,
|
|
matA,
|
|
x,
|
|
h_beta,
|
|
y,
|
|
rocsparse_v2_spmv_stage_compute,
|
|
buffer_size,
|
|
dbuffer,
|
|
nullptr));
|
|
|
|
host_dense_matrix<Y> hy_copy(hy);
|
|
traits::host_calculation(trans, h_alpha, hA, hx, h_beta, hy, alg, matrix_type);
|
|
|
|
const size_t hy_size = (trans == rocsparse_operation_none) ? M : N;
|
|
|
|
for(size_t i = 0; i < hy_size; ++i)
|
|
{
|
|
hy[i] += gamma_val * h_extra[i];
|
|
}
|
|
|
|
hy.near_check(dy);
|
|
|
|
if(ROCSPARSE_REPRODUCIBILITY)
|
|
{
|
|
rocsparse_reproducibility::save("Y_pointer_mode_host_extra", dy);
|
|
}
|
|
|
|
dy.transfer_from(hy_copy);
|
|
}
|
|
|
|
// Clear extra vector after computation
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_spmv_clear_extra(handle, spmv_descr, nullptr));
|
|
|
|
if(arg.timing)
|
|
{
|
|
const double gpu_time_used
|
|
= rocsparse_clients::run_benchmark(arg,
|
|
rocsparse_v2_spmv,
|
|
handle,
|
|
spmv_descr,
|
|
h_alpha,
|
|
matA,
|
|
x,
|
|
h_beta,
|
|
y,
|
|
rocsparse_v2_spmv_stage_compute,
|
|
buffer_size,
|
|
dbuffer,
|
|
nullptr);
|
|
|
|
const double gflop_count = traits::gflop_count(hA, *h_beta != static_cast<T>(0));
|
|
const double gbyte_count = traits::byte_count(hA, *h_beta != static_cast<T>(0));
|
|
|
|
const double gpu_gflops = get_gpu_gflops(gpu_time_used, gflop_count);
|
|
const double gpu_gbyte = get_gpu_gbyte(gpu_time_used, gbyte_count);
|
|
|
|
if(arg.sparsity_pattern_statistics)
|
|
{
|
|
int64_t min_nnz_row;
|
|
int64_t median_nnz_row;
|
|
int64_t max_nnz_row;
|
|
rocsparse_matrix_statistics::get_nnz_per_row(
|
|
dA, min_nnz_row, median_nnz_row, max_nnz_row);
|
|
|
|
int64_t min_nnz_col;
|
|
int64_t median_nnz_col;
|
|
int64_t max_nnz_col;
|
|
rocsparse_matrix_statistics::get_nnz_per_column(
|
|
dA, min_nnz_col, median_nnz_col, max_nnz_col);
|
|
traits::display_info(arg,
|
|
display_key_t::trans_A,
|
|
rocsparse_operation2string(trans),
|
|
dA,
|
|
display_key_t::min_nnz_per_row,
|
|
min_nnz_row,
|
|
display_key_t::max_nnz_per_row,
|
|
max_nnz_row,
|
|
display_key_t::median_nnz_per_row,
|
|
median_nnz_row,
|
|
display_key_t::min_nnz_per_col,
|
|
min_nnz_col,
|
|
display_key_t::max_nnz_per_col,
|
|
max_nnz_col,
|
|
display_key_t::median_nnz_per_col,
|
|
median_nnz_col,
|
|
display_key_t::alpha,
|
|
*h_alpha,
|
|
display_key_t::beta,
|
|
*h_beta,
|
|
display_key_t::algorithm,
|
|
rocsparse_spmvalg2string(alg),
|
|
display_key_t::gflops,
|
|
gpu_gflops,
|
|
display_key_t::bandwidth,
|
|
gpu_gbyte,
|
|
display_key_t::time_ms,
|
|
get_gpu_time_msec(gpu_time_used));
|
|
}
|
|
else
|
|
{
|
|
traits::display_info(arg,
|
|
display_key_t::trans_A,
|
|
rocsparse_operation2string(trans),
|
|
dA,
|
|
display_key_t::alpha,
|
|
*h_alpha,
|
|
display_key_t::beta,
|
|
*h_beta,
|
|
display_key_t::algorithm,
|
|
rocsparse_spmvalg2string(alg),
|
|
display_key_t::gflops,
|
|
gpu_gflops,
|
|
display_key_t::bandwidth,
|
|
gpu_gbyte,
|
|
display_key_t::time_ms,
|
|
get_gpu_time_msec(gpu_time_used));
|
|
}
|
|
}
|
|
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_destroy_dnvec_descr(gamma_vec));
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_destroy_spmv_descr(spmv_descr));
|
|
CHECK_HIP_ERROR(rocsparse_hipFree(dbuffer));
|
|
|
|
// Test enable/disable extra functionality
|
|
if(matrix_type == rocsparse_matrix_type_general && arg.unit_check)
|
|
{
|
|
// Create a new spmv descriptor for enable/disable testing
|
|
rocsparse_spmv_descr spmv_descr;
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_create_spmv_descr(&spmv_descr));
|
|
|
|
// Set mandatory inputs
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_spmv_set_input(
|
|
handle, spmv_descr, rocsparse_spmv_input_alg, &alg, sizeof(alg), nullptr));
|
|
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_spmv_set_input(handle,
|
|
spmv_descr,
|
|
rocsparse_spmv_input_operation,
|
|
&trans,
|
|
sizeof(trans),
|
|
nullptr));
|
|
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_spmv_set_input(handle,
|
|
spmv_descr,
|
|
rocsparse_spmv_input_scalar_datatype,
|
|
&ttype,
|
|
sizeof(ttype),
|
|
nullptr));
|
|
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_spmv_set_input(handle,
|
|
spmv_descr,
|
|
rocsparse_spmv_input_compute_datatype,
|
|
&ttype,
|
|
sizeof(ttype),
|
|
nullptr));
|
|
|
|
// Set extra vectors
|
|
T gamma_val = static_cast<T>(1.0);
|
|
rocsparse_dnvec_descr gamma_vec;
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_create_dnvec_descr(&gamma_vec, 1, &gamma_val, ttype));
|
|
rocsparse_const_dnvec_descr z_vecs[1] = {extra};
|
|
|
|
CHECK_ROCSPARSE_ERROR(
|
|
rocsparse_spmv_set_extra(handle, spmv_descr, 1, gamma_vec, z_vecs, nullptr));
|
|
|
|
// Run analysis
|
|
size_t buffer_size = 0;
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_v2_spmv_buffer_size(handle,
|
|
spmv_descr,
|
|
matA,
|
|
x,
|
|
y,
|
|
rocsparse_v2_spmv_stage_analysis,
|
|
&buffer_size,
|
|
nullptr));
|
|
|
|
void* dbuffer = nullptr;
|
|
CHECK_HIP_ERROR(rocsparse_hipMalloc(&dbuffer, buffer_size));
|
|
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_v2_spmv(handle,
|
|
spmv_descr,
|
|
h_alpha,
|
|
matA,
|
|
x,
|
|
h_beta,
|
|
y,
|
|
rocsparse_v2_spmv_stage_analysis,
|
|
buffer_size,
|
|
dbuffer,
|
|
nullptr));
|
|
|
|
CHECK_HIP_ERROR(rocsparse_hipFree(dbuffer));
|
|
|
|
// Test compute stage with extras enabled (default state)
|
|
buffer_size = 0;
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_v2_spmv_buffer_size(handle,
|
|
spmv_descr,
|
|
matA,
|
|
x,
|
|
y,
|
|
rocsparse_v2_spmv_stage_compute,
|
|
&buffer_size,
|
|
nullptr));
|
|
CHECK_HIP_ERROR(rocsparse_hipMalloc(&dbuffer, buffer_size));
|
|
|
|
// Store original y values for comparison
|
|
host_dense_matrix<Y> hy_enabled(hy);
|
|
hy_enabled.transfer_from(dy);
|
|
|
|
// Run with extras enabled
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_v2_spmv(handle,
|
|
spmv_descr,
|
|
h_alpha,
|
|
matA,
|
|
x,
|
|
h_beta,
|
|
y,
|
|
rocsparse_v2_spmv_stage_compute,
|
|
buffer_size,
|
|
dbuffer,
|
|
nullptr));
|
|
|
|
host_dense_matrix<Y> hy_with_extra(hy);
|
|
hy_with_extra.transfer_from(dy);
|
|
|
|
// Reset y values
|
|
dy.transfer_from(hy_enabled);
|
|
|
|
// Disable extras and run again
|
|
int32_t disable_extra = 0;
|
|
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_spmv_set_input(handle,
|
|
spmv_descr,
|
|
rocsparse_spmv_input_enable_extra,
|
|
&disable_extra,
|
|
sizeof(disable_extra),
|
|
nullptr));
|
|
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_v2_spmv(handle,
|
|
spmv_descr,
|
|
h_alpha,
|
|
matA,
|
|
x,
|
|
h_beta,
|
|
y,
|
|
rocsparse_v2_spmv_stage_compute,
|
|
buffer_size,
|
|
dbuffer,
|
|
nullptr));
|
|
|
|
host_dense_matrix<Y> hy_without_extra(hy);
|
|
hy_without_extra.transfer_from(dy);
|
|
|
|
// Verify results are different (extras disabled should not include z vector)
|
|
const size_t hy_size = (trans == rocsparse_operation_none) ? M : N;
|
|
int results_different = 0;
|
|
for(size_t i = 0; i < hy_size; ++i)
|
|
{
|
|
if(hy_with_extra[i] != hy_without_extra[i])
|
|
{
|
|
results_different = 1;
|
|
break;
|
|
}
|
|
}
|
|
unit_check_scalar(results_different, (int)1);
|
|
|
|
// Re-enable extras and verify we get the same result as before
|
|
dy.transfer_from(hy_enabled);
|
|
|
|
int32_t enable_extra = 1;
|
|
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_spmv_set_input(handle,
|
|
spmv_descr,
|
|
rocsparse_spmv_input_enable_extra,
|
|
&enable_extra,
|
|
sizeof(enable_extra),
|
|
nullptr));
|
|
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_v2_spmv(handle,
|
|
spmv_descr,
|
|
h_alpha,
|
|
matA,
|
|
x,
|
|
h_beta,
|
|
y,
|
|
rocsparse_v2_spmv_stage_compute,
|
|
buffer_size,
|
|
dbuffer,
|
|
nullptr));
|
|
|
|
host_dense_matrix<Y> hy_re_enabled(hy);
|
|
hy_re_enabled.transfer_from(dy);
|
|
|
|
// Verify re-enabled results match original enabled results
|
|
for(size_t i = 0; i < hy_size; ++i)
|
|
{
|
|
unit_check_scalar(hy_with_extra[i], hy_re_enabled[i]);
|
|
}
|
|
|
|
// Test error cases: enable/disable when no extras are set
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_spmv_clear_extra(handle, spmv_descr, nullptr));
|
|
|
|
// These should return errors since no extras are set
|
|
rocsparse_status status;
|
|
int32_t enable_extra_test = 1;
|
|
|
|
status = rocsparse_spmv_set_input(handle,
|
|
spmv_descr,
|
|
rocsparse_spmv_input_enable_extra,
|
|
&enable_extra_test,
|
|
sizeof(enable_extra_test),
|
|
nullptr);
|
|
unit_check_enum(status, rocsparse_status_invalid_value);
|
|
|
|
int32_t disable_extra_test = 0;
|
|
|
|
status = rocsparse_spmv_set_input(handle,
|
|
spmv_descr,
|
|
rocsparse_spmv_input_enable_extra,
|
|
&disable_extra_test,
|
|
sizeof(disable_extra_test),
|
|
nullptr);
|
|
unit_check_enum(status, rocsparse_status_invalid_value);
|
|
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_destroy_dnvec_descr(gamma_vec));
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_destroy_spmv_descr(spmv_descr));
|
|
CHECK_HIP_ERROR(rocsparse_hipFree(dbuffer));
|
|
}
|
|
}
|
|
|
|
static void testing_v2_spmv_multiple_extra(const Arguments& arg)
|
|
{
|
|
J M = arg.M;
|
|
J N = arg.N;
|
|
rocsparse_operation trans = arg.transA;
|
|
rocsparse_index_base base = arg.baseA;
|
|
rocsparse_spmv_alg alg = arg.spmv_alg;
|
|
rocsparse_matrix_type matrix_type = arg.matrix_type;
|
|
rocsparse_fill_mode uplo = arg.uplo;
|
|
rocsparse_storage_mode storage = arg.storage;
|
|
rocsparse_datatype ttype = get_datatype<T>();
|
|
|
|
// Create rocsparse handle
|
|
rocsparse_local_handle handle(arg);
|
|
|
|
// Number of extra vectors to test
|
|
static constexpr int64_t num_extra = 3;
|
|
T gamma_vals[num_extra] = {static_cast<T>(0.5), static_cast<T>(0.3), static_cast<T>(0.7)};
|
|
|
|
host_scalar<T> h_alpha(arg.get_alpha<T>());
|
|
host_scalar<T> h_beta(arg.get_beta<T>());
|
|
host_scalar<T> h_gamma[num_extra] = {host_scalar<T>(gamma_vals[0]),
|
|
host_scalar<T>(gamma_vals[1]),
|
|
host_scalar<T>(gamma_vals[2])};
|
|
|
|
device_scalar<T> d_alpha(h_alpha);
|
|
device_scalar<T> d_beta(h_beta);
|
|
device_scalar<T> d_gamma[num_extra] = {device_scalar<T>(h_gamma[0]),
|
|
device_scalar<T>(h_gamma[1]),
|
|
device_scalar<T>(h_gamma[2])};
|
|
|
|
//
|
|
// INITIALIZATE THE SPARSE MATRIX
|
|
//
|
|
host_sparse_matrix<A> hA;
|
|
{
|
|
int dev;
|
|
CHECK_HIP_ERROR(hipGetDevice(&dev));
|
|
|
|
hipDeviceProp_t prop;
|
|
CHECK_HIP_ERROR(hipGetDeviceProperties(&prop, dev));
|
|
|
|
const bool has_datafile = rocsparse_arguments_has_datafile(arg);
|
|
bool to_int = false;
|
|
to_int |= (prop.warpSize == 32);
|
|
to_int |= (alg != rocsparse_spmv_alg_csr_rowsplit);
|
|
to_int |= (trans != rocsparse_operation_none && has_datafile);
|
|
to_int |= (matrix_type == rocsparse_matrix_type_symmetric && has_datafile);
|
|
static constexpr bool full_rank = false;
|
|
rocsparse_matrix_factory<A, I, J> matrix_factory(
|
|
arg, arg.unit_check ? to_int : false, full_rank);
|
|
traits::sparse_initialization(matrix_factory, hA, M, N, base);
|
|
}
|
|
|
|
if((matrix_type == rocsparse_matrix_type_symmetric && M != N)
|
|
|| (matrix_type == rocsparse_matrix_type_triangular && M != N))
|
|
{
|
|
return;
|
|
}
|
|
|
|
if(M == 0 || N == 0)
|
|
{
|
|
return;
|
|
}
|
|
|
|
device_sparse_matrix<A> dA(hA);
|
|
|
|
host_dense_matrix<X> hx((trans == rocsparse_operation_none) ? N : M, 1);
|
|
rocsparse_matrix_utils::init_exact(hx);
|
|
device_dense_matrix<X> dx(hx);
|
|
|
|
host_dense_matrix<Y> hy((trans == rocsparse_operation_none) ? M : N, 1);
|
|
rocsparse_matrix_utils::init_exact(hy);
|
|
device_dense_matrix<Y> dy(hy);
|
|
|
|
// Create multiple extra vectors
|
|
host_dense_matrix<X> h_extra[num_extra] = {host_dense_matrix<X>(hy.m, 1),
|
|
host_dense_matrix<X>(hy.m, 1),
|
|
host_dense_matrix<X>(hy.m, 1)};
|
|
for(int64_t i = 0; i < num_extra; ++i)
|
|
{
|
|
rocsparse_matrix_utils::init_exact(h_extra[i]);
|
|
}
|
|
|
|
device_dense_matrix<X> d_extra[num_extra] = {device_dense_matrix<X>(h_extra[0]),
|
|
device_dense_matrix<X>(h_extra[1]),
|
|
device_dense_matrix<X>(h_extra[2])};
|
|
|
|
// Create the dnvec descriptors directly without assignment to avoid destructor issues
|
|
rocsparse_local_dnvec extra0(d_extra[0]);
|
|
rocsparse_local_dnvec extra1(d_extra[1]);
|
|
rocsparse_local_dnvec extra2(d_extra[2]);
|
|
|
|
rocsparse_local_spmat matA(dA);
|
|
rocsparse_local_dnvec x(dx);
|
|
rocsparse_local_dnvec y(dy);
|
|
|
|
EXPECT_ROCSPARSE_STATUS(
|
|
rocsparse_spmat_set_attribute(
|
|
matA, rocsparse_spmat_matrix_type, &matrix_type, sizeof(matrix_type)),
|
|
rocsparse_status_success);
|
|
|
|
EXPECT_ROCSPARSE_STATUS(
|
|
rocsparse_spmat_set_attribute(matA, rocsparse_spmat_fill_mode, &uplo, sizeof(uplo)),
|
|
rocsparse_status_success);
|
|
|
|
EXPECT_ROCSPARSE_STATUS(rocsparse_spmat_set_attribute(
|
|
matA, rocsparse_spmat_storage_mode, &storage, sizeof(storage)),
|
|
rocsparse_status_success);
|
|
|
|
// Test both pointer modes for alpha/beta/gamma
|
|
for(int pointer_mode = 0; pointer_mode < 1; ++pointer_mode)
|
|
{
|
|
if(pointer_mode == 0)
|
|
{
|
|
CHECK_ROCSPARSE_ERROR(
|
|
rocsparse_set_pointer_mode(handle, rocsparse_pointer_mode_host));
|
|
}
|
|
else
|
|
{
|
|
CHECK_ROCSPARSE_ERROR(
|
|
rocsparse_set_pointer_mode(handle, rocsparse_pointer_mode_device));
|
|
}
|
|
|
|
// Run buffer size
|
|
rocsparse_spmv_descr spmv_descr;
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_create_spmv_descr(&spmv_descr));
|
|
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_spmv_set_input(
|
|
handle, spmv_descr, rocsparse_spmv_input_alg, &alg, sizeof(alg), nullptr));
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_spmv_set_input(handle,
|
|
spmv_descr,
|
|
rocsparse_spmv_input_operation,
|
|
&trans,
|
|
sizeof(trans),
|
|
nullptr));
|
|
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_spmv_set_input(handle,
|
|
spmv_descr,
|
|
rocsparse_spmv_input_compute_datatype,
|
|
&ttype,
|
|
sizeof(ttype),
|
|
nullptr));
|
|
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_spmv_set_input(handle,
|
|
spmv_descr,
|
|
rocsparse_spmv_input_scalar_datatype,
|
|
&ttype,
|
|
sizeof(ttype),
|
|
nullptr));
|
|
|
|
// Create gamma dnvec with multiple gamma values
|
|
rocsparse_dnvec_descr gamma_vec;
|
|
CHECK_ROCSPARSE_ERROR(
|
|
rocsparse_create_dnvec_descr(&gamma_vec, num_extra, gamma_vals, ttype));
|
|
|
|
rocsparse_const_dnvec_descr z_vecs[num_extra];
|
|
// Get the descriptor directly from each rocsparse_local_dnvec
|
|
rocsparse_local_dnvec* extra_ptrs[num_extra] = {&extra0, &extra1, &extra2};
|
|
for(int64_t i = 0; i < num_extra; ++i)
|
|
{
|
|
rocsparse_dnvec_descr& desc_ref = *extra_ptrs[i];
|
|
z_vecs[i]
|
|
= desc_ref; // Implicit conversion from rocsparse_dnvec_descr to rocsparse_const_dnvec_descr
|
|
}
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_spmv_set_extra(
|
|
handle, spmv_descr, num_extra, gamma_vec, z_vecs, nullptr));
|
|
|
|
size_t buffer_size = 0;
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_v2_spmv_buffer_size(handle,
|
|
spmv_descr,
|
|
matA,
|
|
x,
|
|
y,
|
|
rocsparse_v2_spmv_stage_analysis,
|
|
&buffer_size,
|
|
nullptr));
|
|
|
|
void* dbuffer = nullptr;
|
|
CHECK_HIP_ERROR(rocsparse_hipMalloc(&dbuffer, buffer_size));
|
|
|
|
// Run analysis
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_v2_spmv(handle,
|
|
spmv_descr,
|
|
pointer_mode == 0 ? h_alpha : d_alpha,
|
|
matA,
|
|
x,
|
|
pointer_mode == 0 ? h_beta : d_beta,
|
|
y,
|
|
rocsparse_v2_spmv_stage_analysis,
|
|
buffer_size,
|
|
dbuffer,
|
|
nullptr));
|
|
|
|
CHECK_HIP_ERROR(rocsparse_hipFree(dbuffer));
|
|
dbuffer = nullptr;
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_v2_spmv_buffer_size(handle,
|
|
spmv_descr,
|
|
matA,
|
|
x,
|
|
y,
|
|
rocsparse_v2_spmv_stage_compute,
|
|
&buffer_size,
|
|
nullptr));
|
|
CHECK_HIP_ERROR(rocsparse_hipMalloc(&dbuffer, buffer_size));
|
|
|
|
if(arg.unit_check)
|
|
{
|
|
// Run solve
|
|
CHECK_ROCSPARSE_ERROR(
|
|
testing::rocsparse_v2_spmv(handle,
|
|
spmv_descr,
|
|
pointer_mode == 0 ? h_alpha : d_alpha,
|
|
matA,
|
|
x,
|
|
pointer_mode == 0 ? h_beta : d_beta,
|
|
y,
|
|
rocsparse_v2_spmv_stage_compute,
|
|
buffer_size,
|
|
dbuffer,
|
|
nullptr));
|
|
|
|
host_dense_matrix<Y> hy_copy(hy);
|
|
traits::host_calculation(trans,
|
|
pointer_mode == 0 ? h_alpha : d_alpha,
|
|
hA,
|
|
hx,
|
|
pointer_mode == 0 ? h_beta : d_beta,
|
|
hy,
|
|
alg,
|
|
matrix_type);
|
|
|
|
const size_t hy_size = (trans == rocsparse_operation_none) ? M : N;
|
|
|
|
// Add contribution from all extra vectors: y += gamma[i] * z[i]
|
|
for(int64_t i = 0; i < num_extra; ++i)
|
|
{
|
|
for(size_t j = 0; j < hy_size; ++j)
|
|
{
|
|
hy[j] += gamma_vals[i] * h_extra[i][j];
|
|
}
|
|
}
|
|
|
|
hy.near_check(dy);
|
|
|
|
if(ROCSPARSE_REPRODUCIBILITY)
|
|
{
|
|
rocsparse_reproducibility::save(pointer_mode == 0
|
|
? "Y_pointer_mode_host_multiple_extra"
|
|
: "Y_pointer_mode_device_multiple_extra",
|
|
dy);
|
|
}
|
|
|
|
dy.transfer_from(hy_copy);
|
|
}
|
|
|
|
// Clear extra vectors after computation
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_spmv_clear_extra(handle, spmv_descr, nullptr));
|
|
|
|
if(arg.timing)
|
|
{
|
|
const double gpu_time_used
|
|
= rocsparse_clients::run_benchmark(arg,
|
|
rocsparse_v2_spmv,
|
|
handle,
|
|
spmv_descr,
|
|
pointer_mode == 0 ? h_alpha : d_alpha,
|
|
matA,
|
|
x,
|
|
pointer_mode == 0 ? h_beta : d_beta,
|
|
y,
|
|
rocsparse_v2_spmv_stage_compute,
|
|
buffer_size,
|
|
dbuffer,
|
|
nullptr);
|
|
|
|
const double gflop_count = traits::gflop_count(hA, *h_beta != static_cast<T>(0));
|
|
const double gbyte_count = traits::byte_count(hA, *h_beta != static_cast<T>(0));
|
|
|
|
const double gpu_gflops = get_gpu_gflops(gpu_time_used, gflop_count);
|
|
const double gpu_gbyte = get_gpu_gbyte(gpu_time_used, gbyte_count);
|
|
|
|
if(arg.sparsity_pattern_statistics)
|
|
{
|
|
int64_t min_nnz_row;
|
|
int64_t median_nnz_row;
|
|
int64_t max_nnz_row;
|
|
rocsparse_matrix_statistics::get_nnz_per_row(
|
|
dA, min_nnz_row, median_nnz_row, max_nnz_row);
|
|
|
|
int64_t min_nnz_col;
|
|
int64_t median_nnz_col;
|
|
int64_t max_nnz_col;
|
|
rocsparse_matrix_statistics::get_nnz_per_column(
|
|
dA, min_nnz_col, median_nnz_col, max_nnz_col);
|
|
traits::display_info(arg,
|
|
display_key_t::trans_A,
|
|
rocsparse_operation2string(trans),
|
|
dA,
|
|
display_key_t::min_nnz_per_row,
|
|
min_nnz_row,
|
|
display_key_t::max_nnz_per_row,
|
|
max_nnz_row,
|
|
display_key_t::median_nnz_per_row,
|
|
median_nnz_row,
|
|
display_key_t::min_nnz_per_col,
|
|
min_nnz_col,
|
|
display_key_t::max_nnz_per_col,
|
|
max_nnz_col,
|
|
display_key_t::median_nnz_per_col,
|
|
median_nnz_col,
|
|
display_key_t::alpha,
|
|
*h_alpha,
|
|
display_key_t::beta,
|
|
*h_beta,
|
|
display_key_t::algorithm,
|
|
rocsparse_spmvalg2string(alg),
|
|
display_key_t::gflops,
|
|
gpu_gflops,
|
|
display_key_t::bandwidth,
|
|
gpu_gbyte,
|
|
display_key_t::time_ms,
|
|
get_gpu_time_msec(gpu_time_used));
|
|
}
|
|
else
|
|
{
|
|
traits::display_info(arg,
|
|
display_key_t::trans_A,
|
|
rocsparse_operation2string(trans),
|
|
dA,
|
|
display_key_t::alpha,
|
|
*h_alpha,
|
|
display_key_t::beta,
|
|
*h_beta,
|
|
display_key_t::algorithm,
|
|
rocsparse_spmvalg2string(alg),
|
|
display_key_t::gflops,
|
|
gpu_gflops,
|
|
display_key_t::bandwidth,
|
|
gpu_gbyte,
|
|
display_key_t::time_ms,
|
|
get_gpu_time_msec(gpu_time_used));
|
|
}
|
|
}
|
|
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_destroy_dnvec_descr(gamma_vec));
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_destroy_spmv_descr(spmv_descr));
|
|
CHECK_HIP_ERROR(rocsparse_hipFree(dbuffer));
|
|
}
|
|
}
|
|
};
|