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529 lines
21 KiB
C++
529 lines
21 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 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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#include "../include/hipsolver_dispatcher.hpp"
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#include "../rocblascommon/program_options.hpp"
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using rocblas_int = int;
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using rocblas_stride = ptrdiff_t;
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using namespace roc;
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// clang-format off
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const char* help_str = R"HELP_STR(
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hipSOLVER benchmark client help.
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Usage: ./hipsolver-bench <options>
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In addition to some common general options, the following list of options corresponds to all the parameters
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that might be needed to test a given hipSOLVER function. The parameters are named as in the API user guide.
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The arrays are initialized internally by the program with random values.
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Note: When a required parameter/option is not provided, it will take the default value as listed below.
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If no default value is defined, the program will try to calculate a suitable value depending on the context
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of the problem and the tested function; if this is not possible, the program will abort with an error.
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Functions that accept multiple size parameters can generally be provided a single size parameter (typically,
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m) and a square-size matrix will be assumed.
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Example: ./hipsolver-bench -f getrf -m 30 --lda 75
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This will test getrf with a random 30x30 matrix.
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Options:
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)HELP_STR";
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// clang-format on
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int main(int argc, char* argv[])
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try
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{
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Arguments argus;
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// disable unit_check in client benchmark, it is only
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// used in gtest unit test
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argus.unit_check = 0;
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// enable timing check,otherwise no performance data collected
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argus.timing = 1;
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std::string function;
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char precision;
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rocblas_int device_id;
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// take arguments and set default values
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// clang-format off
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options_description desc("rocsolver client command line options");
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desc.add_options()("help,h", "Produces this help message.")
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// test options
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("batch_count",
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value<rocblas_int>(&argus.batch_count)->default_value(1),
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"Number of matrices or problem instances in the batch.\n"
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" Only applicable to batch routines.\n"
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" ")
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("device",
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value<rocblas_int>(&device_id)->default_value(0),
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"Set the default device to be used for subsequent program runs.\n"
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" ")
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("function,f",
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value<std::string>(&function)->default_value("getrf"),
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"The LAPACK function to test.\n"
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" Options are: getrf, getrs, potrf, potrf_batched, etc.\n"
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" ")
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("iters,i",
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value<rocblas_int>(&argus.iters)->default_value(10),
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"Iterations to run inside the GPU timing loop.\n"
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" Reported time will be the average.\n"
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" ")
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("mem_query",
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value<rocblas_int>(&argus.mem_query)->default_value(0),
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"Calculate the required amount of device workspace memory? 0 = No, 1 = Yes.\n"
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" This forces the client to print only the amount of device memory required by\n"
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" the function, in bytes.\n"
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" ")
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("perf",
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value<rocblas_int>(&argus.perf)->default_value(0),
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"Ignore CPU timing results? 0 = No, 1 = Yes.\n"
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" This forces the client to print only the GPU time and the error if requested.\n"
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" ")
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("precision,r",
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value<char>(&precision)->default_value('s'),
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"Precision to be used in the tests.\n"
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" Options are: s, d, c, z.\n"
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" ")
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// ("singular",
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// value<rocblas_int>(&argus.singular)->default_value(0),
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// "Test with degenerate matrices? 0 = No, 1 = Yes\n"
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// " This will produce matrices that are singular, non positive-definite, etc.\n"
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// " ")
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("verify,v",
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value<rocblas_int>(&argus.norm_check)->default_value(0),
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"Validate GPU results with CPU? 0 = No, 1 = Yes.\n"
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" This will additionally print the relative error of the computations.\n"
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" ")
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// size options
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("k",
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value<rocblas_int>(),
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"Matrix/vector size parameter.\n"
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" Represents a sub-dimension of a problem.\n"
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" For example, the number of Householder reflections in a transformation.\n"
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" ")
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("m",
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value<rocblas_int>(),
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"Matrix/vector size parameter.\n"
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" Typically, the number of rows of a matrix.\n"
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" ")
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("n",
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value<rocblas_int>(),
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"Matrix/vector size parameter.\n"
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" Typically, the number of columns of a matrix,\n"
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" or the order of a system or transformation.\n"
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" ")
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("nrhs",
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value<rocblas_int>(),
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"Matrix/vector size parameter.\n"
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" Typically, the number of columns of a matrix on the right-hand side of a problem.\n"
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" ")
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// leading dimension options
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("lda",
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value<rocblas_int>(),
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"Matrix size parameter.\n"
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" Leading dimension of matrices A.\n"
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" ")
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("ldb",
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value<rocblas_int>(),
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"Matrix size parameter.\n"
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" Leading dimension of matrices B.\n"
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" ")
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("ldc",
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value<rocblas_int>(),
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"Matrix size parameter.\n"
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" Leading dimension of matrices C.\n"
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" ")
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// ("ldt",
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// value<rocblas_int>(),
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// "Matrix size parameter.\n"
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// " Leading dimension of matrices T.\n"
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// " ")
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("ldu",
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value<rocblas_int>(),
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"Matrix size parameter.\n"
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" Leading dimension of matrices U.\n"
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" ")
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("ldv",
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value<rocblas_int>(),
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"Matrix size parameter.\n"
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" Leading dimension of matrices V.\n"
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" ")
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("ldvl",
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value<rocblas_int>(),
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"Matrix size parameter.\n"
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" Leading dimension of matrices VL.\n"
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" ")
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("ldvr",
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value<rocblas_int>(),
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"Matrix size parameter.\n"
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" Leading dimension of matrices VR.\n"
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" ")
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// ("ldw",
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// value<rocblas_int>(),
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// "Matrix size parameter.\n"
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// " Leading dimension of matrices W.\n"
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// " ")
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("ldx",
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value<rocblas_int>(),
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"Matrix size parameter.\n"
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" Leading dimension of matrices X.\n"
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" ")
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// ("ldy",
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// value<rocblas_int>(),
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// "Matrix size parameter.\n"
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// " Leading dimension of matrices Y.\n"
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// " ")
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// stride options
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("strideA",
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value<rocblas_stride>(),
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"Matrix/vector stride parameter.\n"
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" Stride for matrices/vectors A.\n"
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" ")
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// ("strideB",
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// value<rocblas_stride>(),
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// "Matrix/vector stride parameter.\n"
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// " Stride for matrices/vectors B.\n"
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// " ")
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// ("strideD",
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// value<rocblas_stride>(),
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// "Matrix/vector stride parameter.\n"
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// " Stride for matrices/vectors D.\n"
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// " ")
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// ("strideE",
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// value<rocblas_stride>(),
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// "Matrix/vector stride parameter.\n"
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// " Stride for matrices/vectors E.\n"
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// " ")
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// ("strideQ",
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// value<rocblas_stride>(),
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// "Matrix/vector stride parameter.\n"
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// " Stride for vectors tauq.\n"
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// " ")
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// ("strideP",
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// value<rocblas_stride>(),
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// "Matrix/vector stride parameter.\n"
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// " Stride for vectors tau, taup, and ipiv.\n"
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// " ")
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("strideS",
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value<rocblas_stride>(),
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"Matrix/vector stride parameter.\n"
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" Stride for matrices/vectors S.\n"
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" ")
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("strideU",
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value<rocblas_stride>(),
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"Matrix/vector stride parameter.\n"
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" Stride for matrices/vectors U.\n"
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" ")
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("strideV",
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value<rocblas_stride>(),
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"Matrix/vector stride parameter.\n"
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" Stride for matrices/vectors V.\n"
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" ")
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// bdsqr options
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// ("nc",
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// value<rocblas_int>()->default_value(0),
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// "The number of columns of matrix C.\n"
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// " Only applicable to bdsqr.\n"
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// " ")
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// ("nu",
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// value<rocblas_int>(),
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// "The number of columns of matrix U.\n"
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// " Only applicable to bdsqr.\n"
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// " ")
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// ("nv",
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// value<rocblas_int>()->default_value(0),
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// "The number of columns of matrix V.\n"
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// " Only applicable to bdsqr.\n"
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// " ")
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// laswp options
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// ("k1",
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// value<rocblas_int>(),
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// "First index for row interchange.\n"
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// " Only applicable to laswp.\n"
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// " ")
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// ("k2",
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// value<rocblas_int>(),
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// "Last index for row interchange.\n"
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// " Only applicable to laswp.\n"
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// " ")
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// geev options
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("jobvl",
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value<char>()->default_value('N'),
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"N = none, V = compute eigenvectors/singular vectors of the matrix,\n"
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" Indicates how the eigenvectors/singular vectors are to be calculated and stored.\n"
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" ")
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("jobvr",
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value<char>()->default_value('N'),
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"N = none, V = compute eigenvectors/singular vectors of the matrix,\n"
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" Indicates how the eigenvectors/singular vectors are to be calculated and stored.\n"
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" ")
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// gesvd options
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("jobu",
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value<char>()->default_value('N'),
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"N = none, A = the entire orthogonal matrix is computed,\n"
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" S = the singular vectors are computed,\n"
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" O = the singular vectors overwrite the original matrix.\n"
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" Indicates how the left singular vectors are to be calculated and stored.\n"
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" ")
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("jobv",
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value<char>()->default_value('N'),
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"N = none, A = the entire orthogonal matrix is computed,\n"
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" S = the singular vectors are computed,\n"
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" O = the singular vectors overwrite the original matrix.\n"
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" Indicates how the right singular vectors are to be calculated and stored.\n"
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" ")
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// partial eigenvalue/singular value decomposition options
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("il",
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value<rocblas_int>(),
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"Lower index in ordered subset of eigenvalues.\n"
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" Used in partial eigenvalue decomposition functions.\n"
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" ")
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("iu",
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value<rocblas_int>(),
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"Upper index in ordered subset of eigenvalues.\n"
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" Used in partial eigenvalue decomposition functions.\n"
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" ")
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("range",
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value<char>()->default_value('A'),
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"A = all eigenvalues, V = in (vl, vu], I = from the il-th to the iu-th.\n"
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" For partial eigenvalue decompositions, it indicates the type of interval in which\n"
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" the eigenvalues will be found.\n"
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" ")
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("rank",
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value<rocblas_int>(),
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"The number of singular values to be computed.\n"
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" Used in partial SVD functions.\n"
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" ")
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("vl",
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value<double>(),
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"Lower bound of half-open interval (vl, vu].\n"
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" Used in partial eigenvalue decomposition functions.\n"
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" Note: the used random input matrices have all eigenvalues in [-20, 20].\n"
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" ")
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("vu",
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value<double>(),
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"Upper bound of half-open interval (vl, vu].\n"
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" Used in partial eigenvalue decomposition functions.\n"
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" Note: the used random input matrices have all eigenvalues in [-20, 20].\n"
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" ")
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// iterative Jacobi options
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("econ",
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value<rocblas_int>()->default_value(0),
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"Enable economy size for singular vector matrices? 0 = No, 1 = Yes.\n"
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" Only applicable to gesvdj.\n"
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" ")
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("max_sweeps",
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value<rocblas_int>()->default_value(100),
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"Maximum number of sweeps/iterations.\n"
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" Used in iterative Jacobi functions.\n"
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" ")
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("tolerance",
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value<double>(),
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"Absolute tolerance at which convergence is accepted.\n"
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" Used in iterative Jacobi functions.\n"
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" ")
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("sort_eig",
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value<rocblas_int>()->default_value(1),
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"0 = no sorting, 1 = ascending order.\n"
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" Indicates whether the computed eigenvalues are sorted in ascending order.\n"
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" Used in iterative Jacobi functions.\n"
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" ")
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// sparse routine options
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("base1",
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value<rocblas_int>(),
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"0 = use base zero indices, 1 = use base one indices.\n"
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" ")
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("nnzA",
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value<rocblas_int>(),
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"Matrix size parameter.\n"
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" Maximum number of non-zero entries of matrices A.\n"
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" ")
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("reorder",
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value<rocblas_int>(),
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"0 = no reordering, 1 = RCM reordering,\n"
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" 2 = AMD reordering, 3 = METIS reordering.\n"
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" ")
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// other options
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// ("direct",
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// value<char>()->default_value('F'),
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// "F = forward, B = backward.\n"
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// " The order in which a series of transformations are applied.\n"
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// " ")
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// ("fast_alg",
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// value<char>()->default_value('O'),
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// "O = out-of-place, I = in-place.\n"
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// " Enables out-of-place computations.\n"
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// " ")
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// ("incx",
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// value<rocblas_int>()->default_value(1),
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// "Increment between values in vector x.\n"
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// " ")
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("itype",
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value<char>()->default_value('1'),
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"1 = Ax, 2 = ABx, 3 = BAx.\n"
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" Problem type for generalized eigenproblems.\n"
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" ")
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("jobz",
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value<char>()->default_value('N'),
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"N = none, V = compute eigenvectors/singular vectors of the matrix,\n"
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" Indicates how the eigenvectors/singular vectors are to be calculated and stored.\n"
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" ")
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("side",
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value<char>(),
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"L = left, R = right.\n"
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" The side from which a matrix should be multiplied.\n"
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" ")
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// ("storev",
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// value<char>(),
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// "C = column-wise, R = row-wise.\n"
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// " Indicates whether data is stored column-wise or row-wise.\n"
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// " ")
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("trans",
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value<char>()->default_value('N'),
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"N = no transpose, T = transpose, C = conjugate transpose.\n"
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" Indicates if a matrix should be transposed.\n"
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" ")
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("uplo",
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value<char>()->default_value('U'),
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"U = upper, L = lower.\n"
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" Indicates where the data for a triangular or symmetric/hermitian matrix is stored.\n"
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" ");
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// clang-format on
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variables_map vm;
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store(parse_command_line(argc, argv, desc), vm);
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notify(vm);
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// print help message
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if(vm.count("help"))
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{
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std::cout << help_str << desc << std::endl;
|
|
return 0;
|
|
}
|
|
|
|
argus.populate(vm);
|
|
|
|
// set device ID
|
|
if(!argus.perf)
|
|
{
|
|
rocblas_int device_count = query_device_property();
|
|
if(device_count <= device_id)
|
|
throw std::invalid_argument("Invalid Device ID");
|
|
}
|
|
set_device(device_id);
|
|
|
|
// catch invalid arguments
|
|
argus.validate_precision("precision");
|
|
argus.validate_operation("trans");
|
|
argus.validate_side("side");
|
|
argus.validate_fill("uplo");
|
|
// argus.validate_direct("direct");
|
|
// argus.validate_storev("storev");
|
|
argus.validate_svect("jobu");
|
|
argus.validate_svect("jobv");
|
|
// argus.validate_workmode("fast_alg");
|
|
argus.validate_itype("itype");
|
|
argus.validate_evect("jobz");
|
|
argus.validate_evect("jobvl");
|
|
argus.validate_evect("jobvr");
|
|
argus.validate_erange("range");
|
|
|
|
// select and dispatch function test/benchmark
|
|
hipsolver_dispatcher::invoke(function, precision, argus);
|
|
|
|
return 0;
|
|
}
|
|
|
|
catch(const std::invalid_argument& exp)
|
|
{
|
|
std::cerr << exp.what() << std::endl;
|
|
return -1;
|
|
}
|