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/* **************************************************************************
* Copyright (C) 2016-2024 Advanced Micro Devices, Inc. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
*
* 1. Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
*
* 2. Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
*
* THIS SOFTWARE IS PROVIDED BY THE AUTHOR AND CONTRIBUTORS ``AS IS'' AND
* ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
* ARE DISCLAIMED. IN NO EVENT SHALL THE AUTHOR OR CONTRIBUTORS BE LIABLE
* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
* DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS
* OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
* HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY
* OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
* SUCH DAMAGE.
* *************************************************************************/
#include <fmt/core.h>
#include <fmt/ostream.h>
#include "common/misc/program_options.hpp"
#include "common/misc/rocsolver_dispatcher.hpp"
using namespace roc;
// clang-format off
const char* help_str = R"HELP_STR(
rocSOLVER benchmark client help.
Usage: ./rocsolver-bench <options>
In addition to some common general options, the following list of options corresponds to all the parameters
that might be needed to test a given rocSOLVER function. The parameters are named as in the API user guide.
The arrays are initialized internally by the program with random values.
Note: When a required parameter/option is not provided, it will take the default value as listed below.
If no default value is defined, the program will try to calculate a suitable value depending on the context
of the problem and the tested function; if this is not possible, the program will abort with an error.
Functions that accept multiple size parameters can generally be provided a single size parameter (typically,
m) and a square-size matrix will be assumed.
Example: ./rocsolver-bench -f getf2_batched -m 30 --lda 75 --batch_count 350
This will test getf2_batched with a set of 350 random 30x30 matrices. strideP will be set to be equal to 30.
Options:
)HELP_STR";
// clang-format on
static std::string rocblas_version()
{
size_t size;
rocblas_get_version_string_size(&size);
std::string str(size - 1, '\0');
rocblas_get_version_string(str.data(), size);
return str;
}
static std::string rocsolver_version()
{
size_t size;
rocsolver_get_version_string_size(&size);
std::string str(size - 1, '\0');
rocsolver_get_version_string(str.data(), size);
return str;
}
static void print_version_info()
{
fmt::print("rocSOLVER version {} (with rocBLAS {})\n", rocsolver_version(), rocblas_version());
std::fflush(stdout);
}
int main(int argc, char* argv[])
try
{
Arguments argus;
// disable unit_check in client benchmark, it is only
// used in gtest unit test
argus.unit_check = 0;
// enable timing check,otherwise no performance data collected
argus.timing = 1;
std::string function;
char precision = 's';
rocblas_int device_id = 0;
// take arguments and set default values
// clang-format off
options_description desc("rocsolver client command line options");
desc.add_options()("help,h", "Produces this help message.")
// test options
("batch_count",
value<rocblas_int>(&argus.batch_count)->default_value(1),
"Number of matrices or problem instances in the batch.\n"
" Only applicable to batch routines.\n"
" ")
("device",
value<rocblas_int>(&device_id)->default_value(0),
"Set the default device to be used for subsequent program runs.\n"
" ")
("function,f",
value<std::string>(&function)->default_value("potf2"),
"The LAPACK function to test.\n"
" Options are: getf2, getrf, gesvd_batched, etc.\n"
" ")
("iters,i",
value<rocblas_int>(&argus.iters)->default_value(10),
"Iterations to run inside the GPU timing loop.\n"
" Reported time will be the average.\n"
" ")
("alg_mode",
value<rocblas_int>(&argus.alg_mode)->default_value(0),
"0 = GPU-only, 1 = Hybrid\n"
" This will change how the algorithm operates.\n"
" Only applicable to functions with hybrid support.\n"
" ")
("mem_query",
value<rocblas_int>(&argus.mem_query)->default_value(0),
"Calculate the required amount of device workspace memory? 0 = No, 1 = Yes.\n"
" This forces the client to print only the amount of device memory required by\n"
" the function, in bytes.\n"
" ")
("perf",
value<rocblas_int>(&argus.perf)->default_value(0),
"Ignore CPU timing results? 0 = No, 1 = Yes.\n"
" This forces the client to print only the GPU time and the error if requested.\n"
" ")
("precision,r",
value<char>(&precision)->default_value('s'),
"Precision to be used in the tests.\n"
" Options are: s, d, c, z.\n"
" ")
("profile",
value<rocblas_int>(&argus.profile)->default_value(0),
"Print profile logging results for the tested function.\n"
" The argument specifies the max depth of the nested output.\n"
" If the argument is unset or <= 0, profile logging is disabled.\n"
" ")
("profile_kernels",
value<rocblas_int>(&argus.profile_kernels)->default_value(0),
"Include kernels in profile logging results? 0 = No, 1 = Yes.\n"
" Used in conjunction with --profile to include kernels in the profile log.\n"
" ")
("singular",
value<rocblas_int>(&argus.singular)->default_value(0),
"Test with degenerate matrices? 0 = No, 1 = Yes\n"
" This will produce matrices that are singular, non positive-definite, etc.\n"
" ")
("verify,v",
value<rocblas_int>(&argus.norm_check)->default_value(0),
"Validate GPU results with CPU? 0 = No, 1 = Yes.\n"
" This will additionally print the relative error of the computations.\n"
" ")
("hash",
value<rocblas_int>(&argus.hash_check)->default_value(0),
"Print hash of GPU results? 0 = No, 1 = Yes.\n"
" Meant for checking reproducibility of computations.\n"
" ")
// size options
("k",
value<rocblas_int>(),
"Matrix/vector size parameter.\n"
" Represents a sub-dimension of a problem.\n"
" For example, the number of Householder reflections in a transformation.\n"
" ")
("m",
value<rocblas_int>(),
"Matrix/vector size parameter.\n"
" Typically, the number of rows of a matrix.\n"
" ")
("n",
value<rocblas_int>(),
"Matrix/vector size parameter.\n"
" Typically, the number of columns of a matrix,\n"
" or the order of a system or transformation.\n"
" ")
("nrhs",
value<rocblas_int>(),
"Matrix/vector size parameter.\n"
" Typically, the number of columns of a matrix on the right-hand side of a problem.\n"
" ")
// increment options
("inca",
value<rocblas_int>()->default_value(1),
"Matrix/vector increment parameter.\n"
" Increment between values in matrices A.\n"
" ")
("incb",
value<rocblas_int>()->default_value(1),
"Matrix/vector increment parameter.\n"
" Increment between values in matrices B.\n"
" ")
("incc",
value<rocblas_int>()->default_value(1),
"Matrix/vector increment parameter.\n"
" Increment between values in matrices C.\n"
" ")
("incx",
value<rocblas_int>()->default_value(1),
"Matrix/vector increment parameter.\n"
" Increment between values in matrices/vectors X.\n"
" ")
// leading dimension options
("lda",
value<rocblas_int>(),
"Matrix size parameter.\n"
" Leading dimension of matrices A.\n"
" ")
("ldb",
value<rocblas_int>(),
"Matrix size parameter.\n"
" Leading dimension of matrices B.\n"
" ")
("ldc",
value<rocblas_int>(),
"Matrix size parameter.\n"
" Leading dimension of matrices C.\n"
" ")
("ldt",
value<rocblas_int>(),
"Matrix size parameter.\n"
" Leading dimension of matrices T.\n"
" ")
("ldu",
value<rocblas_int>(),
"Matrix size parameter.\n"
" Leading dimension of matrices U.\n"
" ")
("ldv",
value<rocblas_int>(),
"Matrix size parameter.\n"
" Leading dimension of matrices V.\n"
" ")
("ldw",
value<rocblas_int>(),
"Matrix size parameter.\n"
" Leading dimension of matrices W.\n"
" ")
("ldx",
value<rocblas_int>(),
"Matrix size parameter.\n"
" Leading dimension of matrices X.\n"
" ")
("ldy",
value<rocblas_int>(),
"Matrix size parameter.\n"
" Leading dimension of matrices Y.\n"
" ")
("ldz",
value<rocblas_int>(),
"Matrix size parameter.\n"
" Leading dimension of matrices Z.\n"
" ")
// stride options
("strideA",
value<rocblas_stride>(),
"Matrix/vector stride parameter.\n"
" Stride for matrices/vectors A.\n"
" ")
("strideB",
value<rocblas_stride>(),
"Matrix/vector stride parameter.\n"
" Stride for matrices/vectors B.\n"
" ")
("strideD",
value<rocblas_stride>(),
"Matrix/vector stride parameter.\n"
" Stride for matrices/vectors D.\n"
" ")
("strideE",
value<rocblas_stride>(),
"Matrix/vector stride parameter.\n"
" Stride for matrices/vectors E.\n"
" ")
("strideF",
value<rocblas_stride>(),
"Matrix/vector stride parameter.\n"
" Stride for vectors ifail.\n"
" ")
("strideQ",
value<rocblas_stride>(),
"Matrix/vector stride parameter.\n"
" Stride for vectors tauq.\n"
" ")
("strideP",
value<rocblas_stride>(),
"Matrix/vector stride parameter.\n"
" Stride for vectors tau, taup, and ipiv.\n"
" ")
("strideS",
value<rocblas_stride>(),
"Matrix/vector stride parameter.\n"
" Stride for matrices/vectors S.\n"
" ")
("strideU",
value<rocblas_stride>(),
"Matrix/vector stride parameter.\n"
" Stride for matrices/vectors U.\n"
" ")
("strideV",
value<rocblas_stride>(),
"Matrix/vector stride parameter.\n"
" Stride for matrices/vectors V.\n"
" ")
("strideW",
value<rocblas_stride>(),
"Matrix/vector stride parameter.\n"
" Stride for matrices/vectors W.\n"
" ")
("strideX",
value<rocblas_stride>(),
"Matrix/vector stride parameter.\n"
" Stride for matrices/vectors X.\n"
" ")
("strideZ",
value<rocblas_stride>(),
"Matrix/vector stride parameter.\n"
" Stride for matrices/vectors Z.\n"
" ")
// refactorization options
("nnzM",
value<rocblas_int>(),
"The number of non-zero elements in sparse matrix M.\n"
" Currently only a few test cases can be generated.\n"
" The benchmark client will use the available case closest to the input value.\n"
" ")
("nnzA",
value<rocblas_int>(),
"The number of non-zero elements in sparse matrix A.\n"
" Currently only a few test cases can be generated.\n"
" The benchmark client will use the available case closest to the input value.\n"
" ")
("nnzL",
value<rocblas_int>(),
"The number of non-zero elements in sparse matrix L.\n"
" Currently only a few test cases can be generated.\n"
" The benchmark client will use the available case closest to the input value.\n"
" ")
("nnzU",
value<rocblas_int>(),
"The number of non-zero elements in sparse matrix U.\n"
" Currently only a few test cases can be generated.\n"
" The benchmark client will use the available case closest to the input value.\n"
" ")
("nnzT",
value<rocblas_int>(),
"The number of non-zero elements in sparse matrix T.\n"
" Currently only a few test cases can be generated.\n"
" The benchmark client will use the available case closest to the input value.\n"
" ")
("rfinfo_mode",
value<char>(),
"Specifies the desired re-factorization algorithm.\n"
" 1 = LU, 2 = Cholesky.\n"
" ")
// bdsqr options
("nc",
value<rocblas_int>()->default_value(0),
"The number of columns of matrix C.\n"
" Only applicable to bdsqr.\n"
" ")
("nu",
value<rocblas_int>(),
"The number of columns of matrix U.\n"
" Only applicable to bdsqr.\n"
" ")
("nv",
value<rocblas_int>()->default_value(0),
"The number of columns of matrix V.\n"
" Only applicable to bdsqr.\n"
" ")
// bdsvdx options
("svect",
value<char>()->default_value('N'),
"N = none, S or V = the singular vectors are computed.\n"
" Indicates how the left singular vectors are to be calculated and stored.\n"
" Only applicable to bdsvdx.\n"
" ")
// laswp options
("k1",
value<rocblas_int>(),
"First index for row interchange.\n"
" Only applicable to laswp.\n"
" ")
("k2",
value<rocblas_int>(),
"Last index for row interchange.\n"
" Only applicable to laswp.\n"
" ")
// gesvd options
("left_svect",
value<char>()->default_value('N'),
"N = none, A = the entire orthogonal matrix is computed,\n"
" S or V = the singular vectors are computed,\n"
" O = the singular vectors overwrite the original matrix.\n"
" Indicates how the left singular vectors are to be calculated and stored.\n"
" ")
("right_svect",
value<char>()->default_value('N'),
"N = none, A = the entire orthogonal matrix is computed,\n"
" S or V = the singular vectors are computed,\n"
" O = the singular vectors overwrite the original matrix.\n"
" Indicates how the right singular vectors are to be calculated and stored.\n"
" ")
// stein options
("nev",
value<rocblas_int>(),
"Number of eigenvectors to compute in a partial decomposition.\n"
" Only applicable to stein.\n"
" ")
// trtri options
("diag",
value<char>()->default_value('N'),
"N = non-unit triangular, U = unit triangular.\n"
" Indicates whether the diagonal elements of a triangular matrix are assumed to be one.\n"
" Only applicable to trtri.\n"
" ")
// stebz options
("eorder",
value<char>()->default_value('E'),
"E = entire matrix, B = by blocks.\n"
" Indicates whether the computed eigenvalues are ordered by blocks or for the entire matrix.\n"
" Only applicable to stebz.\n"
" ")
// geblttrf/geblttrs options
("nb",
value<rocblas_int>(),
"Number of rows and columns in each block.\n"
" Only applicable to block tridiagonal matrix APIs.\n"
" ")
("nblocks",
value<rocblas_int>(),
"Number of blocks along the diagonal.\n"
" Only applicable to block tridiagonal matrix APIs.\n"
" ")
// partial eigenvalue/singular value decomposition options
("il",
value<rocblas_int>(),
"Lower index in ordered subset of eigenvalues.\n"
" Used in partial eigenvalue decomposition functions.\n"
" ")
("iu",
value<rocblas_int>(),
"Upper index in ordered subset of eigenvalues.\n"
" Used in partial eigenvalue decomposition functions.\n"
" ")
("erange",
value<char>()->default_value('A'),
"A = all eigenvalues, V = in (vl, vu], I = from the il-th to the iu-th.\n"
" For partial eigenvalue decompositions, it indicates the type of interval in which\n"
" the eigenvalues will be found.\n"
" ")
("srange",
value<char>()->default_value('A'),
"A = all singular values, V = in (vl, vu], I = from the il-th to the iu-th.\n"
" For partial singular value decompositions, it indicates the type of interval in which\n"
" the singular values will be found.\n"
" ")
("vl",
value<double>(),
"Lower bound of half-open interval (vl, vu].\n"
" Used in partial eigenvalue decomposition functions.\n"
" Note: the used random input matrices have all eigenvalues in [-20, 20].\n"
" ")
("vu",
value<double>(),
"Upper bound of half-open interval (vl, vu].\n"
" Used in partial eigenvalue decomposition functions.\n"
" Note: the used random input matrices have all eigenvalues in [-20, 20].\n"
" ")
// iterative Jacobi options
("max_sweeps",
value<rocblas_int>()->default_value(100),
"Maximum number of sweeps/iterations.\n"
" Used in iterative Jacobi functions.\n"
" ")
("esort",
value<char>()->default_value('A'),
"N = no sorting, A = ascending order.\n"
" Indicates whether the computed eigenvalues are sorted in ascending order.\n"
" Used in iterative Jacobi functions.\n"
" ")
// other options
("abstol",
value<double>()->default_value(0),
"Absolute tolerance at which convergence is accepted.\n"
" Used in iterative Jacobi and partial eigenvalue decomposition functions.\n"
" ")
("direct",
value<char>()->default_value('F'),
"F = forward, B = backward.\n"
" The order in which a series of transformations are applied.\n"
" ")
("pivot",
value<char>()->default_value('V'),
"V = variable, T = top, B = bottom.\n"
" Defines the planes on which a sequence of rotations is applied.\n"
" ")
("evect",
value<char>()->default_value('N'),
"N = none, V = compute eigenvectors of the matrix,\n"
" I = compute eigenvectors of the tridiagonal matrix.\n"
" Indicates how the eigenvectors are to be calculated and stored.\n"
" ")
("fast_alg",
value<char>()->default_value('O'),
"O = out-of-place, I = in-place.\n"
" Enables out-of-place computations.\n"
" ")
("itype",
value<char>()->default_value('1'),
"1 = Ax, 2 = ABx, 3 = BAx.\n"
" Problem type for generalized eigenproblems.\n"
" ")
("side",
value<char>(),
"L = left, R = right.\n"
" The side from which a matrix should be multiplied.\n"
" ")
("storev",
value<char>(),
"C = column-wise, R = row-wise.\n"
" Indicates whether data is stored column-wise or row-wise.\n"
" ")
("trans",
value<char>()->default_value('N'),
"N = no transpose, T = transpose, C = conjugate transpose.\n"
" Indicates if a matrix should be transposed.\n"
" ")
("uplo",
value<char>()->default_value('U'),
"U = upper, L = lower.\n"
" Indicates where the data for a triangular or symmetric/hermitian matrix is stored.\n"
" ");
// clang-format on
variables_map vm;
store(parse_command_line(argc, argv, desc), vm);
notify(vm);
// print help message
if(vm.count("help"))
{
std::stringstream desc_ss{};
desc_ss << desc;
fmt::print("{}{}\n", help_str, desc_ss.str());
return 0;
}
argus.populate(vm);
if(!argus.perf)
{
print_version_info();
rocblas_int device_count = query_device_property();
if(device_count <= 0)
throw std::runtime_error("No devices found");
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_diag("diag");
argus.validate_direct("direct");
argus.validate_pivot("pivot");
argus.validate_storev("storev");
argus.validate_svect("svect");
argus.validate_svect("left_svect");
argus.validate_svect("right_svect");
argus.validate_erange("srange");
argus.validate_workmode("fast_alg");
argus.validate_evect("evect");
argus.validate_erange("erange");
argus.validate_eorder("eorder");
argus.validate_esort("esort");
argus.validate_itype("itype");
argus.validate_rfinfo_mode("rfinfo_mode");
// prepare logging infrastructure and ignore environment variables
rocsolver_log_begin();
rocsolver_log_set_layer_mode(rocblas_layer_mode_none);
// select and dispatch function test/benchmark
rocsolver_dispatcher::invoke(function, precision, argus);
// terminate logging
rocsolver_log_end();
return 0;
}
catch(const std::exception& exp)
{
fmt::print(stderr, "{}\n", exp.what());
return -1;
}
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