derek.holloway
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609 lines
25 KiB
C++
609 lines
25 KiB
C++
/* ************************************************************************
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* Copyright (C) 2023 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 cop-
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* ies of the Software, and to permit persons to whom the Software is furnished
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* 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 all
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* 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 IM-
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* PLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS
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* FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
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* COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER
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* IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNE-
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* CTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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*
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*
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* ************************************************************************ */
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#pragma once
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#include "clientcommon.hpp"
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template <typename T>
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void csrrf_refactlu_checkBadArgs(hipsolverRfHandle_t handle,
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const int n,
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const int nnzA,
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int* ptrA,
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int* indA,
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T valA,
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const int nnzT,
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int* ptrT,
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int* indT,
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T valT,
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int* pivP,
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int* pivQ)
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{
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// handle
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EXPECT_ROCBLAS_STATUS(hipsolverRfRefactor(nullptr), HIPSOLVER_STATUS_NOT_INITIALIZED);
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}
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template <typename T>
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void testing_csrrf_refactlu_bad_arg()
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{
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// safe arguments
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hipsolverRf_local_handle handle;
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int n = 1;
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int nnzA = 1;
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int nnzT = 1;
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// memory allocations
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device_strided_batch_vector<int> ptrA(1, 1, 1, 1);
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device_strided_batch_vector<int> indA(1, 1, 1, 1);
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device_strided_batch_vector<T> valA(1, 1, 1, 1);
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device_strided_batch_vector<int> ptrT(1, 1, 1, 1);
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device_strided_batch_vector<int> indT(1, 1, 1, 1);
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device_strided_batch_vector<T> valT(1, 1, 1, 1);
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device_strided_batch_vector<int> pivP(1, 1, 1, 1);
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device_strided_batch_vector<int> pivQ(1, 1, 1, 1);
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CHECK_HIP_ERROR(ptrA.memcheck());
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CHECK_HIP_ERROR(indA.memcheck());
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CHECK_HIP_ERROR(valA.memcheck());
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CHECK_HIP_ERROR(ptrT.memcheck());
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CHECK_HIP_ERROR(indT.memcheck());
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CHECK_HIP_ERROR(valT.memcheck());
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CHECK_HIP_ERROR(pivP.memcheck());
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CHECK_HIP_ERROR(pivQ.memcheck());
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// check bad arguments
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csrrf_refactlu_checkBadArgs(handle,
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n,
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nnzA,
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ptrA.data(),
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indA.data(),
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valA.data(),
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nnzT,
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ptrT.data(),
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indT.data(),
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valT.data(),
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pivP.data(),
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pivQ.data());
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}
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template <bool CPU, bool GPU, typename T, typename Td, typename Ud, typename Th, typename Uh>
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void csrrf_refactlu_initData(hipsolverRfHandle_t handle,
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const int n,
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const int nnzA,
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Ud& dptrA,
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Ud& dindA,
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Td& dvalA,
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const int nnzL,
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Ud& dptrL,
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Ud& dindL,
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Td& dvalL,
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const int nnzU,
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Ud& dptrU,
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Ud& dindU,
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Td& dvalU,
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Ud& dpivP,
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Ud& dpivQ,
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Uh& hptrA,
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Uh& hindA,
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Th& hvalA,
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Uh& hptrL,
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Uh& hindL,
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Th& hvalL,
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Uh& hptrU,
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Uh& hindU,
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Th& hvalU,
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Th& hvalT,
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Uh& hpivP,
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Uh& hpivQ,
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const fs::path testcase)
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{
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int nnzT = nnzL - n + nnzU;
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if(CPU)
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{
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fs::path file;
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// read-in A
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file = testcase / "ptrA";
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read_matrix(file.string(), 1, n + 1, hptrA.data(), 1);
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file = testcase / "indA";
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read_matrix(file.string(), 1, nnzA, hindA.data(), 1);
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file = testcase / "valA";
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read_matrix(file.string(), 1, nnzA, hvalA.data(), 1);
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// read-in L
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file = testcase / "ptrL";
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read_matrix(file.string(), 1, n + 1, hptrL.data(), 1);
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file = testcase / "indL";
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read_matrix(file.string(), 1, nnzL, hindL.data(), 1);
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file = testcase / "valL";
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read_matrix(file.string(), 1, nnzL, hvalL.data(), 1);
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// read-in U
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file = testcase / "ptrU";
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read_matrix(file.string(), 1, n + 1, hptrU.data(), 1);
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file = testcase / "indU";
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read_matrix(file.string(), 1, nnzU, hindU.data(), 1);
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file = testcase / "valU";
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read_matrix(file.string(), 1, nnzU, hvalU.data(), 1);
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// read-in T
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file = testcase / "valT";
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read_matrix(file.string(), 1, nnzT, hvalT.data(), 1);
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// read-in P
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file = testcase / "P";
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read_matrix(file.string(), 1, n, hpivP.data(), 1);
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// read-in Q
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file = testcase / "Q";
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read_matrix(file.string(), 1, n, hpivQ.data(), 1);
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}
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if(GPU)
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{
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CHECK_HIP_ERROR(dptrA.transfer_from(hptrA));
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CHECK_HIP_ERROR(dindA.transfer_from(hindA));
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CHECK_HIP_ERROR(dvalA.transfer_from(hvalA));
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CHECK_HIP_ERROR(dptrL.transfer_from(hptrL));
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CHECK_HIP_ERROR(dindL.transfer_from(hindL));
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CHECK_HIP_ERROR(dvalL.transfer_from(hvalL));
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CHECK_HIP_ERROR(dptrU.transfer_from(hptrU));
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CHECK_HIP_ERROR(dindU.transfer_from(hindU));
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CHECK_HIP_ERROR(dvalU.transfer_from(hvalU));
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CHECK_HIP_ERROR(dpivP.transfer_from(hpivP));
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CHECK_HIP_ERROR(dpivQ.transfer_from(hpivQ));
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}
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}
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template <typename T, typename Td, typename Ud, typename Th, typename Uh>
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void csrrf_refactlu_getError(hipsolverRfHandle_t handle,
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const int n,
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const int nnzA,
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Ud& dptrA,
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Ud& dindA,
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Td& dvalA,
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const int nnzL,
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Ud& dptrL,
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Ud& dindL,
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Td& dvalL,
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const int nnzU,
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Ud& dptrU,
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Ud& dindU,
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Td& dvalU,
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Ud& dpivP,
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Ud& dpivQ,
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Uh& hptrA,
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Uh& hindA,
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Th& hvalA,
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Uh& hptrL,
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Uh& hindL,
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Th& hvalL,
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Uh& hptrU,
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Uh& hindU,
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Th& hvalU,
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Th& hvalT,
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Uh& hpivP,
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Uh& hpivQ,
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double* max_err,
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const fs::path testcase)
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{
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int nnzLRes;
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int* hptrLRes;
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int* hindLRes;
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T* hvalLRes;
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int nnzURes;
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int* hptrURes;
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int* hindURes;
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T* hvalURes;
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int nnzTRes;
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int* hptrTRes;
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int* hindTRes;
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T* hvalTRes;
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// input data initialization
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csrrf_refactlu_initData<true, true, T>(handle,
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n,
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nnzA,
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dptrA,
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dindA,
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dvalA,
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nnzL,
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dptrL,
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dindL,
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dvalL,
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nnzU,
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dptrU,
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dindU,
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dvalU,
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dpivP,
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dpivQ,
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hptrA,
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hindA,
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hvalA,
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hptrL,
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hindL,
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hvalL,
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hptrU,
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hindU,
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hvalU,
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hvalT,
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hpivP,
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hpivQ,
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testcase);
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// execute computations
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// GPU lapack
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CHECK_ROCBLAS_ERROR(hipsolverRfSetupDevice(n,
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nnzA,
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dptrA.data(),
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dindA.data(),
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dvalA.data(),
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nnzL,
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dptrL.data(),
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dindL.data(),
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dvalL.data(),
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nnzU,
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dptrU.data(),
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dindU.data(),
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dvalU.data(),
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dpivP.data(),
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dpivQ.data(),
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handle));
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CHECK_ROCBLAS_ERROR(hipsolverRfAnalyze(handle));
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CHECK_ROCBLAS_ERROR(hipsolverRfResetValues(
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n, nnzA, dptrA.data(), dindA.data(), dvalA.data(), dpivP.data(), dpivQ.data(), handle));
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CHECK_ROCBLAS_ERROR(hipsolverRfRefactor(handle));
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// compare computed bundled factors with original result
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CHECK_ROCBLAS_ERROR(
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hipsolverRfExtractBundledFactorsHost(handle, &nnzTRes, &hptrTRes, &hindTRes, &hvalTRes));
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EXPECT_EQ(nnzTRes, nnzL - n + nnzU) << "where b = " << 0;
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if(nnzTRes == nnzL - n + nnzU)
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*max_err = norm_error('F', 1, nnzTRes, 1, hvalT[0], hvalTRes);
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else
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*max_err = 1;
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#if defined(__HIP_PLATFORM_HCC__) || defined(__HIP_PLATFORM_AMD__)
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// compare computed split factors with original result
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CHECK_ROCBLAS_ERROR(hipsolverRfExtractSplitFactorsHost(handle,
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&nnzLRes,
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&hptrLRes,
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&hindLRes,
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&hvalLRes,
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&nnzURes,
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&hptrURes,
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&hindURes,
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&hvalURes));
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EXPECT_EQ(nnzLRes, nnzL) << "where b = " << 0;
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EXPECT_EQ(nnzURes, nnzU) << "where b = " << 0;
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if(nnzLRes == nnzL && nnzURes == nnzU)
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{
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double errorL, errorU;
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errorL = norm_error('F', 1, nnzLRes, 1, hvalL[0], hvalLRes);
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errorU = norm_error('F', 1, nnzURes, 1, hvalU[0], hvalURes);
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*max_err = max({*max_err, errorL, errorU});
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}
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else
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*max_err = 1;
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#endif
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}
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template <typename T, typename Td, typename Ud, typename Th, typename Uh>
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void csrrf_refactlu_getPerfData(hipsolverRfHandle_t handle,
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const int n,
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const int nnzA,
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Ud& dptrA,
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Ud& dindA,
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Td& dvalA,
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const int nnzL,
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Ud& dptrL,
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Ud& dindL,
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Td& dvalL,
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const int nnzU,
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Ud& dptrU,
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Ud& dindU,
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Td& dvalU,
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Ud& dpivP,
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Ud& dpivQ,
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Uh& hptrA,
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Uh& hindA,
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Th& hvalA,
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Uh& hptrL,
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Uh& hindL,
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Th& hvalL,
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Uh& hptrU,
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Uh& hindU,
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Th& hvalU,
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Th& hvalT,
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Uh& hpivP,
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Uh& hpivQ,
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double* gpu_time_used,
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double* cpu_time_used,
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const int hot_calls,
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const bool perf,
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const fs::path testcase)
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{
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*cpu_time_used = nan(""); // no timing on cpu-lapack execution
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*gpu_time_used = nan(""); // no timing on gpu-lapack execution
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}
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template <typename T>
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void testing_csrrf_refactlu(Arguments& argus)
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{
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// get arguments
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hipsolverRf_local_handle handle;
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int n = argus.get<int>("n");
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int nnzA = argus.get<int>("nnzA");
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int hot_calls = argus.iters;
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// check non-supported values
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// N/A
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// check invalid sizes
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bool invalid_size = (n < 0 || nnzA < 0);
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if(invalid_size)
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{
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// EXPECT_ROCBLAS_STATUS(rocsolver_csrrf_refactlu(
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// handle, n, nnzA, (int*)nullptr, (int*)nullptr,
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// (T*)nullptr, nnzT, (int*)nullptr, (int*)nullptr,
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// (T*)nullptr, (int*)nullptr, (int*)nullptr, rfinfo),
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// rocblas_status_invalid_size);
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if(argus.timing)
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rocsolver_bench_inform(inform_invalid_size);
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return;
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}
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// determine existing test case
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if(n > 0)
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{
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if(n <= 35)
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n = 20;
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else if(n <= 75)
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n = 50;
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else if(n <= 175)
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n = 100;
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else
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n = 250;
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}
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if(n <= 50) // small case
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{
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if(nnzA <= 80)
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nnzA = 60;
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else if(nnzA <= 120)
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nnzA = 100;
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else
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nnzA = 140;
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}
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else // large case
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{
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if(nnzA <= 400)
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nnzA = 300;
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else if(nnzA <= 600)
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nnzA = 500;
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else
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nnzA = 700;
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}
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// read/set corresponding nnzL and nnzU
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int nnzL, nnzU;
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fs::path testcase;
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if(n > 0)
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{
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fs::path file;
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std::string folder = std::string("mat_") + std::to_string(n) + "_" + std::to_string(nnzA);
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testcase = get_sparse_data_dir() / folder;
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file = testcase / "ptrA";
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read_last(file.string(), &nnzA);
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file = testcase / "ptrL";
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read_last(file.string(), &nnzL);
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file = testcase / "ptrU";
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read_last(file.string(), &nnzU);
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}
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// determine sizes
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size_t size_ptrA = size_t(n) + 1;
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size_t size_indA = size_t(nnzA);
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size_t size_valA = size_t(nnzA);
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size_t size_ptrL = size_t(n) + 1;
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size_t size_indL = size_t(nnzL);
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size_t size_valL = size_t(nnzL);
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size_t size_ptrU = size_t(n) + 1;
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size_t size_indU = size_t(nnzU);
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size_t size_valU = size_t(nnzU);
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size_t size_valT = size_t(nnzL) - n + nnzU;
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size_t size_pivP = size_t(n);
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size_t size_pivQ = size_t(n);
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double max_error = 0, gpu_time_used = 0, cpu_time_used = 0;
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// memory allocations
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host_strided_batch_vector<int> hptrA(size_ptrA, 1, size_ptrA, 1);
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host_strided_batch_vector<int> hindA(size_indA, 1, size_indA, 1);
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host_strided_batch_vector<T> hvalA(size_valA, 1, size_valA, 1);
|
|
host_strided_batch_vector<int> hptrL(size_ptrL, 1, size_ptrL, 1);
|
|
host_strided_batch_vector<int> hindL(size_indL, 1, size_indL, 1);
|
|
host_strided_batch_vector<T> hvalL(size_valL, 1, size_valL, 1);
|
|
host_strided_batch_vector<int> hptrU(size_ptrU, 1, size_ptrU, 1);
|
|
host_strided_batch_vector<int> hindU(size_indU, 1, size_indU, 1);
|
|
host_strided_batch_vector<T> hvalU(size_valU, 1, size_valU, 1);
|
|
host_strided_batch_vector<T> hvalT(size_valT, 1, size_valT, 1);
|
|
host_strided_batch_vector<int> hpivP(size_pivP, 1, size_pivP, 1);
|
|
host_strided_batch_vector<int> hpivQ(size_pivQ, 1, size_pivQ, 1);
|
|
|
|
device_strided_batch_vector<int> dptrA(size_ptrA, 1, size_ptrA, 1);
|
|
device_strided_batch_vector<int> dindA(size_indA, 1, size_indA, 1);
|
|
device_strided_batch_vector<T> dvalA(size_valA, 1, size_valA, 1);
|
|
device_strided_batch_vector<int> dptrL(size_ptrL, 1, size_ptrL, 1);
|
|
device_strided_batch_vector<int> dindL(size_indL, 1, size_indL, 1);
|
|
device_strided_batch_vector<T> dvalL(size_valL, 1, size_valL, 1);
|
|
device_strided_batch_vector<int> dptrU(size_ptrU, 1, size_ptrU, 1);
|
|
device_strided_batch_vector<int> dindU(size_indU, 1, size_indU, 1);
|
|
device_strided_batch_vector<T> dvalU(size_valU, 1, size_valU, 1);
|
|
device_strided_batch_vector<int> dpivP(size_pivP, 1, size_pivP, 1);
|
|
device_strided_batch_vector<int> dpivQ(size_pivQ, 1, size_pivQ, 1);
|
|
CHECK_HIP_ERROR(dptrA.memcheck());
|
|
CHECK_HIP_ERROR(dptrL.memcheck());
|
|
CHECK_HIP_ERROR(dptrU.memcheck());
|
|
if(size_indA)
|
|
CHECK_HIP_ERROR(dindA.memcheck());
|
|
if(size_valA)
|
|
CHECK_HIP_ERROR(dvalA.memcheck());
|
|
if(size_indL)
|
|
CHECK_HIP_ERROR(dindL.memcheck());
|
|
if(size_valL)
|
|
CHECK_HIP_ERROR(dvalL.memcheck());
|
|
if(size_indU)
|
|
CHECK_HIP_ERROR(dindU.memcheck());
|
|
if(size_valU)
|
|
CHECK_HIP_ERROR(dvalU.memcheck());
|
|
if(size_pivP)
|
|
CHECK_HIP_ERROR(dpivP.memcheck());
|
|
if(size_pivQ)
|
|
CHECK_HIP_ERROR(dpivQ.memcheck());
|
|
|
|
// check computations
|
|
if(argus.unit_check || argus.norm_check)
|
|
csrrf_refactlu_getError<T>(handle,
|
|
n,
|
|
nnzA,
|
|
dptrA,
|
|
dindA,
|
|
dvalA,
|
|
nnzL,
|
|
dptrL,
|
|
dindL,
|
|
dvalL,
|
|
nnzU,
|
|
dptrU,
|
|
dindU,
|
|
dvalU,
|
|
dpivP,
|
|
dpivQ,
|
|
hptrA,
|
|
hindA,
|
|
hvalA,
|
|
hptrL,
|
|
hindL,
|
|
hvalL,
|
|
hptrU,
|
|
hindU,
|
|
hvalU,
|
|
hvalT,
|
|
hpivP,
|
|
hpivQ,
|
|
&max_error,
|
|
testcase);
|
|
|
|
// collect performance data
|
|
if(argus.timing)
|
|
csrrf_refactlu_getPerfData<T>(handle,
|
|
n,
|
|
nnzA,
|
|
dptrA,
|
|
dindA,
|
|
dvalA,
|
|
nnzL,
|
|
dptrL,
|
|
dindL,
|
|
dvalL,
|
|
nnzU,
|
|
dptrU,
|
|
dindU,
|
|
dvalU,
|
|
dpivP,
|
|
dpivQ,
|
|
hptrA,
|
|
hindA,
|
|
hvalA,
|
|
hptrL,
|
|
hindL,
|
|
hvalL,
|
|
hptrU,
|
|
hindU,
|
|
hvalU,
|
|
hvalT,
|
|
hpivP,
|
|
hpivQ,
|
|
&gpu_time_used,
|
|
&cpu_time_used,
|
|
hot_calls,
|
|
argus.perf,
|
|
testcase);
|
|
|
|
// validate results for rocsolver-test
|
|
// using n * machine precision for tolerance
|
|
if(argus.unit_check)
|
|
ROCSOLVER_TEST_CHECK(T, max_error, n);
|
|
|
|
// output results for rocsolver-bench
|
|
if(argus.timing)
|
|
{
|
|
if(!argus.perf)
|
|
{
|
|
std::cerr << "\n============================================\n";
|
|
std::cerr << "Arguments:\n";
|
|
std::cerr << "============================================\n";
|
|
rocsolver_bench_output("n", "nnzA");
|
|
rocsolver_bench_output(n, nnzA);
|
|
|
|
std::cerr << "\n============================================\n";
|
|
std::cerr << "Results:\n";
|
|
std::cerr << "============================================\n";
|
|
if(argus.norm_check)
|
|
{
|
|
rocsolver_bench_output("cpu_time_us", "gpu_time_us", "error");
|
|
rocsolver_bench_output(cpu_time_used, gpu_time_used, max_error);
|
|
}
|
|
else
|
|
{
|
|
rocsolver_bench_output("cpu_time_us", "gpu_time_us");
|
|
rocsolver_bench_output(cpu_time_used, gpu_time_used);
|
|
}
|
|
std::cerr << std::endl;
|
|
}
|
|
else
|
|
{
|
|
if(argus.norm_check)
|
|
rocsolver_bench_output(gpu_time_used, max_error);
|
|
else
|
|
rocsolver_bench_output(gpu_time_used);
|
|
}
|
|
}
|
|
|
|
// ensure all arguments were consumed
|
|
argus.validate_consumed();
|
|
}
|