derek.holloway
7502bf64a4
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518 lines
20 KiB
C++
518 lines
20 KiB
C++
/* ************************************************************************
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* Copyright (C) 2020-2026 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 "rocsparse_traits.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_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_spmv_bad_arg(const Arguments& arg)
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{
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const T local_alpha = static_cast<T>(6);
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const T local_beta = static_cast<T>(2);
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rocsparse_local_handle local_handle;
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rocsparse_handle handle = local_handle;
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rocsparse_operation trans = rocsparse_operation_none;
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const void* alpha = (const void*)&local_alpha;
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const void* beta = (const void*)&local_beta;
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rocsparse_spmv_alg alg = rocsparse_spmv_alg_default;
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rocsparse_spmv_stage stage = rocsparse_spmv_stage_compute;
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size_t local_buffer_size;
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size_t* buffer_size = &local_buffer_size;
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void* temp_buffer = (void*)0x4;
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rocsparse_datatype compute_type = get_datatype<T>();
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#define PARAMS \
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handle, trans, alpha, mat, x, beta, y, compute_type, alg, stage, buffer_size, temp_buffer
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//
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// AUTOMATIC BAD ARGS.
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//
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{
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device_dense_matrix<X> dx;
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device_dense_matrix<Y> dy;
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device_sparse_matrix<A> dA;
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rocsparse_local_spmat local_mat(dA);
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rocsparse_local_dnvec local_x(dx);
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rocsparse_local_dnvec local_y(dy);
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rocsparse_spmat_descr mat = local_mat;
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rocsparse_dnvec_descr x = local_x;
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rocsparse_dnvec_descr y = local_y;
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//
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// WITH 2 ARGUMENTS BEING SKIPPED DURING THE CHECK.
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//
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static const int nex = 2;
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static const int ex[2] = {10, 11};
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select_bad_arg_analysis(rocsparse_spmv, nex, ex, PARAMS);
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buffer_size = nullptr;
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temp_buffer = nullptr;
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EXPECT_ROCSPARSE_STATUS(rocsparse_spmv(PARAMS), rocsparse_status_invalid_pointer);
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}
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#undef PARAMS
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}
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static void testing_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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const bool call_stage_analysis = arg.call_stage_analysis;
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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
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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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// For bf16/f16 precision, set all matrix values to 1.0 for numerical stability
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if constexpr(is_low_precision_v<A>)
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{
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set_array_to_ones(hA.val.data(), hA.val.size());
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}
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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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// For bf16/f16 precision, set all vector values to 1.0 for numerical stability
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if constexpr(is_low_precision_v<X>)
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{
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set_array_to_ones(hx.data(), static_cast<size_t>(hx.m * hx.n));
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}
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else
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{
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rocsparse_matrix_utils::init_exact(hx);
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}
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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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// For bf16/f16 precision, set all vector values to 1.0 for numerical stability
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if constexpr(is_low_precision_v<Y>)
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{
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set_array_to_ones(hy.data(), static_cast<size_t>(hy.m * hy.n));
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}
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else
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{
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rocsparse_matrix_utils::init_exact(hy);
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}
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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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void* dbuffer = nullptr;
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size_t buffer_size = 0;
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CHECK_ROCSPARSE_ERROR(
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rocsparse_spmv(PARAMS(h_alpha, matA, x, h_beta, y, rocsparse_spmv_stage_buffer_size)));
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CHECK_HIP_ERROR(rocsparse_hipMalloc(&dbuffer, buffer_size));
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if(call_stage_analysis)
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{
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// Run preprocess
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CHECK_ROCSPARSE_ERROR(rocsparse_spmv(
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PARAMS(h_alpha, matA, x, h_beta, y, rocsparse_spmv_stage_preprocess)));
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}
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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_spmv(
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PARAMS(h_alpha, matA, x, h_beta, y, rocsparse_spmv_stage_compute)));
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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_spmv(
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PARAMS(d_alpha, matA, x, d_beta, y, rocsparse_spmv_stage_compute)));
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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 = rocsparse_clients::run_benchmark(
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arg,
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rocsparse_spmv,
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PARAMS(h_alpha, matA, x, h_beta, y, rocsparse_spmv_stage_compute));
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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_HIP_ERROR(rocsparse_hipFree(dbuffer));
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}
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static void testing_spmv_analysis(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_ANALYSIS(alpha_, A_, x_, beta_, y_, stage) \
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handle, trans, alpha_, A_, x_, beta_, y_, ttype, alg, stage, &buffer_size, dbuffer
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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_stream);
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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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// For bf16/f16 precision, set all matrix values to 1.0 for numerical stability
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if constexpr(is_low_precision_v<A>)
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{
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set_array_to_ones(hA.val.data(), hA.val.size());
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}
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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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// For bf16/f16 precision, set all vector values to 1.0 for numerical stability
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if constexpr(is_low_precision_v<X>)
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{
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set_array_to_ones(hx.data(), static_cast<size_t>(hx.m * hx.n));
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}
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else
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{
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rocsparse_matrix_utils::init_exact(hx);
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}
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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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// For bf16/f16 precision, set all vector values to 1.0 for numerical stability
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if constexpr(is_low_precision_v<Y>)
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{
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set_array_to_ones(hy.data(), static_cast<size_t>(hy.m * hy.n));
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}
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else
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{
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rocsparse_matrix_utils::init_exact(hy);
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}
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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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|
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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)),
|
|
rocsparse_status_success);
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|
|
|
EXPECT_ROCSPARSE_STATUS(rocsparse_spmat_set_attribute(
|
|
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));
|
|
|
|
// Run buffer size
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|
void* dbuffer = nullptr;
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|
size_t buffer_size = 0;
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|
CHECK_ROCSPARSE_ERROR(rocsparse_spmv(
|
|
PARAMS_ANALYSIS(h_alpha, matA, x, h_beta, y, rocsparse_spmv_stage_buffer_size)));
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|
CHECK_HIP_ERROR(rocsparse_hipMalloc(&dbuffer, buffer_size));
|
|
|
|
// Run preprocess
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_spmv(
|
|
PARAMS_ANALYSIS(h_alpha, matA, x, h_beta, y, rocsparse_spmv_stage_preprocess)));
|
|
|
|
if(arg.timing)
|
|
{
|
|
const int number_cold_calls = 2;
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|
const int number_hot_calls = arg.iters;
|
|
|
|
// Warm up
|
|
for(int iter = 0; iter < number_cold_calls; ++iter)
|
|
{
|
|
void* dbuffer_iter;
|
|
size_t buffer_size;
|
|
|
|
dbuffer_iter = nullptr;
|
|
buffer_size = 0;
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_spmv(PARAMS_ANALYSIS(
|
|
h_alpha, matA, x, h_beta, y, rocsparse_spmv_stage_buffer_size)));
|
|
|
|
CHECK_HIP_ERROR(rocsparse_hipMalloc(&dbuffer_iter, buffer_size));
|
|
|
|
// Run preprocess
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_spmv(
|
|
PARAMS_ANALYSIS(h_alpha, matA, x, h_beta, y, rocsparse_spmv_stage_preprocess)));
|
|
|
|
CHECK_HIP_ERROR(rocsparse_hipFree(dbuffer_iter));
|
|
}
|
|
|
|
double gpu_time_used = get_time_us();
|
|
|
|
void* dbuffer_iter;
|
|
size_t buffer_size;
|
|
|
|
// Performance run
|
|
for(int iter = 0; iter < number_hot_calls; ++iter)
|
|
{
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_csr_set_pointers(matA, dA.ptr, dA.ind, dA.val));
|
|
|
|
dbuffer_iter = nullptr;
|
|
buffer_size = 0;
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_spmv(PARAMS_ANALYSIS(
|
|
h_alpha, matA, x, h_beta, y, rocsparse_spmv_stage_buffer_size)));
|
|
|
|
CHECK_HIP_ERROR(rocsparse_hipMalloc(&dbuffer_iter, buffer_size));
|
|
|
|
// Run preprocess
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_spmv(
|
|
PARAMS_ANALYSIS(h_alpha, matA, x, h_beta, y, rocsparse_spmv_stage_preprocess)));
|
|
|
|
CHECK_HIP_ERROR(rocsparse_hipFree(dbuffer_iter));
|
|
}
|
|
|
|
gpu_time_used = (get_time_us() - gpu_time_used) / number_hot_calls;
|
|
|
|
const double gpu_gflops = 0;
|
|
const double gpu_gbyte = 0;
|
|
|
|
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_HIP_ERROR(rocsparse_hipFree(dbuffer));
|
|
}
|
|
};
|