derek.holloway
7502bf64a4
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649 lines
29 KiB
C++
649 lines
29 KiB
C++
/* ************************************************************************
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* Copyright (C) 2021-2026 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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#include "testing.hpp"
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#include <tuple>
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#include <vector>
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template <typename I, typename J, typename A, typename B, typename C, typename T>
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void testing_spmm_csr_bad_arg(const Arguments& arg)
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{
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static const size_t safe_size = 100;
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// Create rocsparse handle
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rocsparse_local_handle local_handle;
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rocsparse_handle handle = local_handle;
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J m = safe_size;
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J n = safe_size;
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J k = safe_size;
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I nnz = safe_size;
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const T* alpha = (const T*)0x4;
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const T* beta = (const T*)0x4;
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void* csr_val = (void*)0x4;
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void* csr_row_ptr = (void*)0x4;
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void* csr_col_ind = (void*)0x4;
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void* dB = (void*)0x4;
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void* dC = (void*)0x4;
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rocsparse_operation trans_A = rocsparse_operation_none;
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rocsparse_operation trans_B = rocsparse_operation_none;
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rocsparse_index_base base = rocsparse_index_base_zero;
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rocsparse_order order_B = rocsparse_order_column;
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rocsparse_order order_C = rocsparse_order_column;
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rocsparse_spmm_alg alg = rocsparse_spmm_alg_default;
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rocsparse_spmm_stage stage = rocsparse_spmm_stage_compute;
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rocsparse_indextype itype = get_indextype<I>();
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rocsparse_indextype jtype = get_indextype<J>();
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rocsparse_datatype atype = get_datatype<A>();
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rocsparse_datatype btype = get_datatype<B>();
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rocsparse_datatype ctype = get_datatype<C>();
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rocsparse_datatype compute_type = get_datatype<T>();
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// SpMM structures
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rocsparse_local_spmat local_mat_A(
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m, k, nnz, csr_row_ptr, csr_col_ind, csr_val, itype, jtype, base, atype);
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rocsparse_local_dnmat local_mat_B(k, n, k, dB, btype, order_B);
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rocsparse_local_dnmat local_mat_C(m, n, m, dC, ctype, order_C);
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rocsparse_spmat_descr mat_A = local_mat_A;
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rocsparse_dnmat_descr mat_B = local_mat_B;
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rocsparse_dnmat_descr mat_C = local_mat_C;
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int nargs_to_exclude = 2;
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const int args_to_exclude[2] = {11, 12};
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#define PARAMS \
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handle, trans_A, trans_B, alpha, mat_A, mat_B, beta, mat_C, compute_type, alg, stage, \
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buffer_size, temp_buffer
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{
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size_t* buffer_size = (size_t*)0x4;
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void* temp_buffer = (void*)0x4;
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select_bad_arg_analysis(rocsparse_spmm, nargs_to_exclude, args_to_exclude, PARAMS);
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}
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{
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size_t* buffer_size = (size_t*)0x4;
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void* temp_buffer = nullptr;
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select_bad_arg_analysis(rocsparse_spmm, nargs_to_exclude, args_to_exclude, PARAMS);
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}
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{
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size_t* buffer_size = nullptr;
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void* temp_buffer = (void*)0x4;
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select_bad_arg_analysis(rocsparse_spmm, nargs_to_exclude, args_to_exclude, PARAMS);
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}
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{
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size_t* buffer_size = nullptr;
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void* temp_buffer = nullptr;
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select_bad_arg_analysis(rocsparse_spmm, nargs_to_exclude, args_to_exclude, PARAMS);
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}
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#undef PARAMS
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}
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template <typename I, typename J, typename A, typename B, typename C, typename T>
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void testing_spmm_csr(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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J K = arg.K;
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rocsparse_operation trans_A = arg.transA;
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rocsparse_operation trans_B = arg.transB;
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rocsparse_index_base base = arg.baseA;
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rocsparse_spmm_alg alg = arg.spmm_alg;
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rocsparse_order order_B = arg.orderB;
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rocsparse_order order_C = arg.orderC;
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rocsparse_int ld_multiplier_B = arg.ld_multiplier_B;
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rocsparse_int ld_multiplier_C = arg.ld_multiplier_C;
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T halpha = arg.get_alpha<T>();
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T hbeta = arg.get_beta<T>();
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// Index and data type
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rocsparse_indextype itype = get_indextype<I>();
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rocsparse_indextype jtype = get_indextype<J>();
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rocsparse_datatype atype = get_datatype<A>();
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rocsparse_datatype btype = get_datatype<B>();
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rocsparse_datatype ctype = get_datatype<C>();
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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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// Allocate host memory for matrix
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host_vector<I> hcsr_row_ptr;
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host_vector<J> hcsr_col_ind;
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host_vector<A> hcsr_val;
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// Allocate host memory for matrix
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rocsparse_matrix_factory<A, I, J> matrix_factory(arg);
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I nnz_A;
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matrix_factory.init_csr(hcsr_row_ptr,
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hcsr_col_ind,
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hcsr_val,
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(trans_A == rocsparse_operation_none) ? M : K,
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(trans_A == rocsparse_operation_none) ? K : M,
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nnz_A,
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base);
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// Redefine values
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rocsparse_init_1d_array<A>(
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hcsr_val, nnz_A, arg.convert_to_int, arg.rand_gen_min, arg.rand_gen_max);
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// For low-precision types (f16/bf16), set values to 1.0f 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(hcsr_val.data(), nnz_A);
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}
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// Some matrix properties
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J A_m = (trans_A == rocsparse_operation_none) ? M : K;
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J A_n = (trans_A == rocsparse_operation_none) ? K : M;
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J B_m = (trans_B == rocsparse_operation_none) ? K : N;
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J B_n = (trans_B == rocsparse_operation_none) ? N : K;
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J C_m = M;
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J C_n = N;
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int64_t ldb = (order_B == rocsparse_order_column)
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? ((trans_B == rocsparse_operation_none) ? (int64_t(ld_multiplier_B) * K)
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: (int64_t(ld_multiplier_B) * N))
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: ((trans_B == rocsparse_operation_none) ? (int64_t(ld_multiplier_B) * N)
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: (int64_t(ld_multiplier_B) * K));
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int64_t ldc = (order_C == rocsparse_order_column) ? (int64_t(ld_multiplier_C) * M)
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: (int64_t(ld_multiplier_C) * N);
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int64_t nrowB = (order_B == rocsparse_order_column) ? ldb : B_m;
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int64_t ncolB = (order_B == rocsparse_order_column) ? B_n : ldb;
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int64_t nrowC = (order_C == rocsparse_order_column) ? ldc : C_m;
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int64_t ncolC = (order_C == rocsparse_order_column) ? C_n : ldc;
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int64_t nnz_B = nrowB * ncolB;
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int64_t nnz_C = nrowC * ncolC;
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// Allocate host memory for vectors
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host_vector<B> hB(nnz_B);
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host_vector<C> hC_1(nnz_C);
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host_vector<C> hC_2(nnz_C);
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host_vector<C> hC_gold(nnz_C);
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// Initialize data on CPU
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rocsparse_init_1d_array<B>(hB, nnz_B, arg.convert_to_int, arg.rand_gen_min, arg.rand_gen_max);
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rocsparse_init_1d_array<C>(hC_1, nnz_C, arg.convert_to_int, arg.rand_gen_min, arg.rand_gen_max);
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// For low-precision types (f16/bf16), set values to 1.0f for numerical stability
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if constexpr(is_low_precision_v<B>)
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{
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set_array_to_ones(hB.data(), nnz_B);
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}
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if constexpr(is_low_precision_v<C>)
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{
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set_array_to_ones(hC_1.data(), nnz_C);
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}
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hC_2 = hC_1;
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hC_gold = hC_1;
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// Allocate device memory
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device_vector<I> dcsr_row_ptr(A_m + 1);
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device_vector<J> dcsr_col_ind(nnz_A);
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device_vector<A> dcsr_val(nnz_A);
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device_vector<B> dB(nnz_B);
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device_vector<C> dC_1(nnz_C);
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device_vector<C> dC_2(nnz_C);
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device_vector<T> dalpha(1);
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device_vector<T> dbeta(1);
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// Copy data from CPU to device
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CHECK_HIP_ERROR(
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hipMemcpy(dcsr_row_ptr, hcsr_row_ptr.data(), sizeof(I) * (A_m + 1), hipMemcpyHostToDevice));
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CHECK_HIP_ERROR(
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hipMemcpy(dcsr_col_ind, hcsr_col_ind.data(), sizeof(J) * nnz_A, hipMemcpyHostToDevice));
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CHECK_HIP_ERROR(hipMemcpy(dcsr_val, hcsr_val.data(), sizeof(A) * nnz_A, hipMemcpyHostToDevice));
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CHECK_HIP_ERROR(hipMemcpy(dB, hB, sizeof(B) * nnz_B, hipMemcpyHostToDevice));
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CHECK_HIP_ERROR(hipMemcpy(dC_1, hC_1, sizeof(C) * nnz_C, hipMemcpyHostToDevice));
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CHECK_HIP_ERROR(hipMemcpy(dC_2, hC_2, sizeof(C) * nnz_C, hipMemcpyHostToDevice));
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CHECK_HIP_ERROR(hipMemcpy(dalpha, &halpha, sizeof(T), hipMemcpyHostToDevice));
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CHECK_HIP_ERROR(hipMemcpy(dbeta, &hbeta, sizeof(T), hipMemcpyHostToDevice));
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// Create descriptors
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rocsparse_local_spmat mat_A(
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A_m, A_n, nnz_A, dcsr_row_ptr, dcsr_col_ind, dcsr_val, itype, jtype, base, atype);
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ldb = std::max(int64_t(1), ldb);
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ldc = std::max(int64_t(1), ldc);
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rocsparse_local_dnmat mat_B(B_m, B_n, ldb, dB, btype, order_B);
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rocsparse_local_dnmat mat_C1(C_m, C_n, ldc, dC_1, ctype, order_C);
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rocsparse_local_dnmat mat_C2(C_m, C_n, ldc, dC_2, ctype, order_C);
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// Query SpMM buffer. Route through the graph-capture wrapper so the
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// graph_test cases capture the buffer_size stage as well. The default
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// algorithm selection runs a device reduction (kernel + D2H copy + stream
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// sync) only at buffer_size; that sequence is illegal under HIP stream
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// capture, so this exercises the capture guard (the call must still return
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// success and fall back to the capture-safe row-split default). For the
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// non-graph cases the wrapper is a plain passthrough.
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size_t buffer_size;
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CHECK_ROCSPARSE_ERROR(testing::rocsparse_spmm(handle,
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trans_A,
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trans_B,
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&halpha,
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mat_A,
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mat_B,
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&hbeta,
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mat_C1,
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ttype,
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alg,
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rocsparse_spmm_stage_buffer_size,
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&buffer_size,
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nullptr));
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// Allocate buffer
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void* dbuffer;
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CHECK_HIP_ERROR(rocsparse_hipMalloc(&dbuffer, buffer_size));
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CHECK_ROCSPARSE_ERROR(rocsparse_spmm(handle,
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trans_A,
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trans_B,
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&halpha,
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mat_A,
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mat_B,
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&hbeta,
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mat_C1,
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ttype,
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alg,
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rocsparse_spmm_stage_preprocess,
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&buffer_size,
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dbuffer));
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if(arg.unit_check)
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{
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// SpMM
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// Pointer mode host
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CHECK_ROCSPARSE_ERROR(rocsparse_set_pointer_mode(handle, rocsparse_pointer_mode_host));
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CHECK_ROCSPARSE_ERROR(testing::rocsparse_spmm(handle,
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trans_A,
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trans_B,
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&halpha,
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mat_A,
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mat_B,
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&hbeta,
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mat_C1,
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ttype,
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alg,
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rocsparse_spmm_stage_compute,
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&buffer_size,
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dbuffer));
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if(ROCSPARSE_REPRODUCIBILITY)
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{
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rocsparse_reproducibility::save("dC_1", dC_1);
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}
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// Pointer mode device
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CHECK_ROCSPARSE_ERROR(rocsparse_set_pointer_mode(handle, rocsparse_pointer_mode_device));
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CHECK_ROCSPARSE_ERROR(testing::rocsparse_spmm(handle,
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trans_A,
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trans_B,
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dalpha,
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mat_A,
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mat_B,
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dbeta,
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mat_C2,
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ttype,
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alg,
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rocsparse_spmm_stage_compute,
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&buffer_size,
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dbuffer));
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if(ROCSPARSE_REPRODUCIBILITY)
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{
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rocsparse_reproducibility::save("dC_2", dC_2);
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}
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// Copy output to host
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CHECK_HIP_ERROR(hipMemcpy(hC_1, dC_1, sizeof(C) * nnz_C, hipMemcpyDeviceToHost));
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CHECK_HIP_ERROR(hipMemcpy(hC_2, dC_2, sizeof(C) * nnz_C, hipMemcpyDeviceToHost));
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// CPU csrmm
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host_csrmm<T, I, J, A, B, C>(A_m,
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N,
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A_n,
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trans_A,
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trans_B,
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halpha,
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hcsr_row_ptr,
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hcsr_col_ind,
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hcsr_val,
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hB,
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ldb,
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order_B,
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hbeta,
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hC_gold,
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ldc,
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order_C,
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base,
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false);
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hC_gold.near_check(hC_1, get_near_check_tol<C>(arg));
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hC_gold.near_check(hC_2, get_near_check_tol<C>(arg));
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}
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if(arg.timing)
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{
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CHECK_ROCSPARSE_ERROR(rocsparse_set_pointer_mode(handle, rocsparse_pointer_mode_host));
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const double gpu_time_used = rocsparse_clients::run_benchmark(arg,
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rocsparse_spmm,
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handle,
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trans_A,
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trans_B,
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&halpha,
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mat_A,
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mat_B,
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&hbeta,
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mat_C1,
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ttype,
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alg,
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rocsparse_spmm_stage_compute,
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&buffer_size,
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dbuffer);
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double gflop_count
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= spmm_gflop_count(N, nnz_A, (I)C_m * (I)C_n, hbeta != static_cast<T>(0));
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double gpu_gflops = get_gpu_gflops(gpu_time_used, gflop_count);
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double gbyte_count = csrmm_gbyte_count<A, B, C>(
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A_m, nnz_A, (I)B_m * (I)B_n, (I)C_m * (I)C_n, hbeta != static_cast<T>(0));
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double gpu_gbyte = get_gpu_gbyte(gpu_time_used, gbyte_count);
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display_timing_info(display_key_t::M,
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M,
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display_key_t::N,
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N,
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display_key_t::K,
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K,
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display_key_t::nnz_A,
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nnz_A,
|
|
display_key_t::alpha,
|
|
halpha,
|
|
display_key_t::beta,
|
|
hbeta,
|
|
display_key_t::algorithm,
|
|
rocsparse_spmmalg2string(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));
|
|
}
|
|
|
|
#define INSTANTIATE(ITYPE, JTYPE, TTYPE) \
|
|
template void testing_spmm_csr_bad_arg<ITYPE, JTYPE, TTYPE, TTYPE, TTYPE, TTYPE>( \
|
|
const Arguments& arg); \
|
|
template void testing_spmm_csr<ITYPE, JTYPE, TTYPE, TTYPE, TTYPE, TTYPE>(const Arguments& arg)
|
|
#define INSTANTIATE_MIXED(ITYPE, JTYPE, ATYPE, XTYPE, YTYPE, TTYPE) \
|
|
template void testing_spmm_csr_bad_arg<ITYPE, JTYPE, ATYPE, XTYPE, YTYPE, TTYPE>( \
|
|
const Arguments& arg); \
|
|
template void testing_spmm_csr<ITYPE, JTYPE, ATYPE, XTYPE, YTYPE, TTYPE>(const Arguments& arg)
|
|
|
|
INSTANTIATE(int32_t, int32_t, float);
|
|
INSTANTIATE(int32_t, int32_t, double);
|
|
INSTANTIATE(int32_t, int32_t, rocsparse_float_complex);
|
|
INSTANTIATE(int32_t, int32_t, rocsparse_double_complex);
|
|
INSTANTIATE(int64_t, int32_t, float);
|
|
INSTANTIATE(int64_t, int32_t, double);
|
|
INSTANTIATE(int64_t, int32_t, rocsparse_float_complex);
|
|
INSTANTIATE(int64_t, int32_t, rocsparse_double_complex);
|
|
INSTANTIATE(int64_t, int64_t, float);
|
|
INSTANTIATE(int64_t, int64_t, double);
|
|
INSTANTIATE(int64_t, int64_t, rocsparse_float_complex);
|
|
INSTANTIATE(int64_t, int64_t, rocsparse_double_complex);
|
|
|
|
INSTANTIATE_MIXED(int32_t, int32_t, int8_t, int8_t, int32_t, int32_t);
|
|
INSTANTIATE_MIXED(int64_t, int32_t, int8_t, int8_t, int32_t, int32_t);
|
|
INSTANTIATE_MIXED(int64_t, int64_t, int8_t, int8_t, int32_t, int32_t);
|
|
INSTANTIATE_MIXED(int32_t, int32_t, int8_t, int8_t, float, float);
|
|
INSTANTIATE_MIXED(int64_t, int32_t, int8_t, int8_t, float, float);
|
|
INSTANTIATE_MIXED(int64_t, int64_t, int8_t, int8_t, float, float);
|
|
INSTANTIATE_MIXED(int32_t, int32_t, _Float16, _Float16, float, float);
|
|
INSTANTIATE_MIXED(int64_t, int32_t, _Float16, _Float16, float, float);
|
|
INSTANTIATE_MIXED(int64_t, int64_t, _Float16, _Float16, float, float);
|
|
INSTANTIATE_MIXED(int32_t, int32_t, rocsparse_bfloat16, rocsparse_bfloat16, float, float);
|
|
INSTANTIATE_MIXED(int64_t, int32_t, rocsparse_bfloat16, rocsparse_bfloat16, float, float);
|
|
INSTANTIATE_MIXED(int64_t, int64_t, rocsparse_bfloat16, rocsparse_bfloat16, float, float);
|
|
INSTANTIATE_MIXED(int32_t, int32_t, _Float16, _Float16, _Float16, float);
|
|
INSTANTIATE_MIXED(int64_t, int32_t, _Float16, _Float16, _Float16, float);
|
|
INSTANTIATE_MIXED(int64_t, int64_t, _Float16, _Float16, _Float16, float);
|
|
INSTANTIATE_MIXED(
|
|
int32_t, int32_t, rocsparse_bfloat16, rocsparse_bfloat16, rocsparse_bfloat16, float);
|
|
INSTANTIATE_MIXED(
|
|
int64_t, int32_t, rocsparse_bfloat16, rocsparse_bfloat16, rocsparse_bfloat16, float);
|
|
INSTANTIATE_MIXED(
|
|
int64_t, int64_t, rocsparse_bfloat16, rocsparse_bfloat16, rocsparse_bfloat16, float);
|
|
|
|
void testing_spmm_csr_extra(const Arguments& arg)
|
|
{
|
|
// Validate the CSR SpMM default-algorithm auto-selection end to end.
|
|
//
|
|
// The kernel the default resolves to is deliberately not observable through
|
|
// the public API: buffer_size is sized conservatively for the largest
|
|
// auto-selectable kernel, and every kernel computes the same product. So this
|
|
// test drives the full buffer_size -> preprocess -> compute pipeline - which
|
|
// includes the structural line-nnz profile reduction and the selection it
|
|
// feeds - and checks that the default reproduces the analytic product in both
|
|
// asymptotic skew regimes, and that it agrees with the explicit row-split and
|
|
// non-zero-split kernels.
|
|
//
|
|
// The two synthetic matrices below sit at the asymptotic ends of the
|
|
// dimensionless gate (longest-row share -> 1 vs -> 0), so the exercised
|
|
// decision is independent of the device compute-unit count, and therefore of
|
|
// the architecture.
|
|
|
|
rocsparse_local_handle local_handle;
|
|
rocsparse_handle handle = local_handle;
|
|
|
|
const rocsparse_datatype ttype = get_datatype<double>();
|
|
const rocsparse_indextype itype = get_indextype<int32_t>();
|
|
const rocsparse_indextype jtype = get_indextype<int32_t>();
|
|
const rocsparse_index_base base = rocsparse_index_base_zero;
|
|
const rocsparse_order order = rocsparse_order_column;
|
|
|
|
const double alpha = 1.0;
|
|
const double beta = 0.0;
|
|
const int32_t n = 2; // dense columns of B and C
|
|
|
|
// Run the full three-stage CSR SpMM for one structure and algorithm and copy
|
|
// the dense result C back to the host. Returns through an out-parameter
|
|
// because the CHECK_*_ERROR macros expand to GoogleTest ASSERT_*, which may
|
|
// only be used in a void-returning function. With every matrix and B entry
|
|
// equal to one (alpha = 1, beta = 0), C[i, j] is exactly the number of
|
|
// non-zeros in row i, an integer represented exactly in double.
|
|
auto run_spmm = [&](const host_vector<int32_t>& hrow_ptr,
|
|
const host_vector<int32_t>& hcol_ind,
|
|
int32_t k,
|
|
rocsparse_spmm_alg alg,
|
|
host_vector<double>& hC) {
|
|
const int32_t m = static_cast<int32_t>(hrow_ptr.size()) - 1;
|
|
const int64_t nnz = static_cast<int64_t>(hcol_ind.size());
|
|
|
|
const host_vector<double> hval(nnz, 1.0);
|
|
const host_vector<double> hB(int64_t(k) * n, 1.0);
|
|
|
|
device_vector<int32_t> drow_ptr(m + 1);
|
|
device_vector<int32_t> dcol_ind(nnz);
|
|
device_vector<double> dval(nnz);
|
|
device_vector<double> dB(int64_t(k) * n);
|
|
device_vector<double> dC(int64_t(m) * n);
|
|
|
|
CHECK_HIP_ERROR(
|
|
hipMemcpy(drow_ptr, hrow_ptr.data(), sizeof(int32_t) * (m + 1), hipMemcpyHostToDevice));
|
|
CHECK_HIP_ERROR(
|
|
hipMemcpy(dcol_ind, hcol_ind.data(), sizeof(int32_t) * nnz, hipMemcpyHostToDevice));
|
|
CHECK_HIP_ERROR(hipMemcpy(dval, hval.data(), sizeof(double) * nnz, hipMemcpyHostToDevice));
|
|
CHECK_HIP_ERROR(
|
|
hipMemcpy(dB, hB.data(), sizeof(double) * int64_t(k) * n, hipMemcpyHostToDevice));
|
|
|
|
rocsparse_local_spmat mat_A(m, k, nnz, drow_ptr, dcol_ind, dval, itype, jtype, base, ttype);
|
|
rocsparse_local_dnmat mat_B(k, n, k, dB, ttype, order);
|
|
rocsparse_local_dnmat mat_C(m, n, m, dC, ttype, order);
|
|
|
|
size_t buffer_size = 0;
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_spmm(handle,
|
|
rocsparse_operation_none,
|
|
rocsparse_operation_none,
|
|
&alpha,
|
|
mat_A,
|
|
mat_B,
|
|
&beta,
|
|
mat_C,
|
|
ttype,
|
|
alg,
|
|
rocsparse_spmm_stage_buffer_size,
|
|
&buffer_size,
|
|
nullptr));
|
|
|
|
void* dbuffer = nullptr;
|
|
CHECK_HIP_ERROR(rocsparse_hipMalloc(&dbuffer, buffer_size > 0 ? buffer_size : 1));
|
|
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_spmm(handle,
|
|
rocsparse_operation_none,
|
|
rocsparse_operation_none,
|
|
&alpha,
|
|
mat_A,
|
|
mat_B,
|
|
&beta,
|
|
mat_C,
|
|
ttype,
|
|
alg,
|
|
rocsparse_spmm_stage_preprocess,
|
|
&buffer_size,
|
|
dbuffer));
|
|
|
|
CHECK_ROCSPARSE_ERROR(rocsparse_spmm(handle,
|
|
rocsparse_operation_none,
|
|
rocsparse_operation_none,
|
|
&alpha,
|
|
mat_A,
|
|
mat_B,
|
|
&beta,
|
|
mat_C,
|
|
ttype,
|
|
alg,
|
|
rocsparse_spmm_stage_compute,
|
|
&buffer_size,
|
|
dbuffer));
|
|
|
|
hC.resize(int64_t(m) * n);
|
|
CHECK_HIP_ERROR(
|
|
hipMemcpy(hC.data(), dC, sizeof(double) * int64_t(m) * n, hipMemcpyDeviceToHost));
|
|
|
|
CHECK_HIP_ERROR(rocsparse_hipFree(dbuffer));
|
|
};
|
|
|
|
// For one structure, check that the default reproduces the analytic product
|
|
// and matches both explicit load-balanced kernels.
|
|
auto check_structure =
|
|
[&](const host_vector<int32_t>& hrow_ptr, const host_vector<int32_t>& hcol_ind, int32_t k) {
|
|
const int32_t m = static_cast<int32_t>(hrow_ptr.size()) - 1;
|
|
|
|
// Analytic reference C[i, j] = non-zeros in row i (column-major, ld = m).
|
|
host_vector<double> hC_ref(int64_t(m) * n);
|
|
for(int32_t j = 0; j < n; ++j)
|
|
{
|
|
for(int32_t i = 0; i < m; ++i)
|
|
{
|
|
hC_ref[int64_t(j) * m + i] = static_cast<double>(hrow_ptr[i + 1] - hrow_ptr[i]);
|
|
}
|
|
}
|
|
|
|
host_vector<double> hC_default, hC_row, hC_nnz;
|
|
run_spmm(hrow_ptr, hcol_ind, k, rocsparse_spmm_alg_default, hC_default);
|
|
run_spmm(hrow_ptr, hcol_ind, k, rocsparse_spmm_alg_csr_row_split, hC_row);
|
|
run_spmm(hrow_ptr, hcol_ind, k, rocsparse_spmm_alg_csr_nnz_split, hC_nnz);
|
|
|
|
unit_check_general<double>(m, n, hC_ref.data(), m, hC_default.data(), m);
|
|
unit_check_general<double>(m, n, hC_ref.data(), m, hC_row.data(), m);
|
|
unit_check_general<double>(m, n, hC_ref.data(), m, hC_nnz.data(), m);
|
|
};
|
|
|
|
// Extremely row-skewed matrix: one "hub" row holds almost all non-zeros, the
|
|
// rest a single entry. Longest-row share -> 1, so the gate is free to upgrade
|
|
// to the non-zero-split kernel; the default must still be correct.
|
|
{
|
|
const int32_t hub_nnz = 65536;
|
|
const int32_t m = 8;
|
|
const int32_t k = hub_nnz;
|
|
|
|
host_vector<int32_t> hrow_ptr(m + 1, 0);
|
|
host_vector<int32_t> hcol_ind;
|
|
hcol_ind.reserve(hub_nnz + (m - 1));
|
|
|
|
for(int32_t c = 0; c < hub_nnz; ++c)
|
|
{
|
|
hcol_ind.push_back(c);
|
|
}
|
|
hrow_ptr[1] = hub_nnz;
|
|
|
|
for(int32_t r = 1; r < m; ++r)
|
|
{
|
|
hcol_ind.push_back(0);
|
|
hrow_ptr[r + 1] = hrow_ptr[r] + 1;
|
|
}
|
|
|
|
check_structure(hrow_ptr, hcol_ind, k);
|
|
}
|
|
|
|
// Extremely uniform matrix: every row has the same small length. Longest-row
|
|
// share -> 0, so the gate keeps the row-split default; the default must stay
|
|
// correct.
|
|
{
|
|
const int32_t row_nnz = 4;
|
|
const int32_t m = 100000;
|
|
const int32_t k = row_nnz;
|
|
|
|
host_vector<int32_t> hrow_ptr(m + 1, 0);
|
|
host_vector<int32_t> hcol_ind;
|
|
hcol_ind.reserve(int64_t(m) * row_nnz);
|
|
|
|
for(int32_t r = 0; r < m; ++r)
|
|
{
|
|
for(int32_t c = 0; c < row_nnz; ++c)
|
|
{
|
|
hcol_ind.push_back(c);
|
|
}
|
|
hrow_ptr[r + 1] = hrow_ptr[r] + row_nnz;
|
|
}
|
|
|
|
check_structure(hrow_ptr, hcol_ind, k);
|
|
}
|
|
}
|