derek.holloway
7502bf64a4
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1177 lines
51 KiB
C++
1177 lines
51 KiB
C++
/* **************************************************************************
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* Copyright (C) 2024-2025 Advanced Micro Devices, Inc. All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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*
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* 1. Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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*
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* 2. Redistributions in binary form must reproduce the above copyright
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* notice, this list of conditions and the following disclaimer in the
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* documentation and/or other materials provided with the distribution.
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*
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* THIS SOFTWARE IS PROVIDED BY THE AUTHOR AND CONTRIBUTORS ``AS IS'' AND
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* ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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* ARE DISCLAIMED. IN NO EVENT SHALL THE AUTHOR OR CONTRIBUTORS BE LIABLE
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* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
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* DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS
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* OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
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* HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
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* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY
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* OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
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* SUCH DAMAGE.
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* *************************************************************************/
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#pragma once
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#include "common/matrix_utils/matrix_utils.hpp"
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#include "common/misc/client_util.hpp"
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#include "common/misc/clientcommon.hpp"
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#include "common/misc/clss.hpp"
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#include "common/misc/lapack_host_reference.hpp"
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#include "common/misc/norm.hpp"
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#include "common/misc/rocsolver.hpp"
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#include "common/misc/rocsolver_arguments.hpp"
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#include "common/misc/rocsolver_test.hpp"
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#include "common/misc/rocsolver_timer.hpp"
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template <bool STRIDED, typename T, typename S, typename U>
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void sygvdx_hegvdx_checkBadArgs(const rocblas_handle handle,
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const rocblas_eform itype,
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const rocblas_evect evect,
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const rocblas_erange erange,
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const rocblas_fill uplo,
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const rocblas_int n,
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T dA,
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const rocblas_int lda,
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const rocblas_stride stA,
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T dB,
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const rocblas_int ldb,
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const rocblas_stride stB,
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const S vl,
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const S vu,
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const rocblas_int il,
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const rocblas_int iu,
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rocblas_int* dNev,
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U dW,
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const rocblas_stride stW,
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T dZ,
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const rocblas_int ldz,
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const rocblas_stride stZ,
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rocblas_int* dInfo,
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const rocblas_int bc)
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{
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// handle
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EXPECT_ROCBLAS_STATUS(rocsolver_sygvdx_hegvdx(STRIDED, nullptr, itype, evect, erange, uplo, n,
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dA, lda, stA, dB, ldb, stB, vl, vu, il, iu, dNev,
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dW, stW, dZ, ldz, stZ, dInfo, bc),
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rocblas_status_invalid_handle);
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// values
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EXPECT_ROCBLAS_STATUS(rocsolver_sygvdx_hegvdx(STRIDED, handle, rocblas_eform(0), evect, erange,
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uplo, n, dA, lda, stA, dB, ldb, stB, vl, vu, il,
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iu, dNev, dW, stW, dZ, ldz, stZ, dInfo, bc),
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rocblas_status_invalid_value);
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EXPECT_ROCBLAS_STATUS(rocsolver_sygvdx_hegvdx(STRIDED, handle, itype, rocblas_evect_tridiagonal,
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erange, uplo, n, dA, lda, stA, dB, ldb, stB, vl,
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vu, il, iu, dNev, dW, stW, dZ, ldz, stZ, dInfo, bc),
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rocblas_status_invalid_value);
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EXPECT_ROCBLAS_STATUS(rocsolver_sygvdx_hegvdx(STRIDED, handle, itype, evect, rocblas_erange(0),
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uplo, n, dA, lda, stA, dB, ldb, stB, vl, vu, il,
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iu, dNev, dW, stW, dZ, ldz, stZ, dInfo, bc),
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rocblas_status_invalid_value);
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EXPECT_ROCBLAS_STATUS(rocsolver_sygvdx_hegvdx(STRIDED, handle, itype, evect, erange,
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rocblas_fill_full, n, dA, lda, stA, dB, ldb, stB,
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vl, vu, il, iu, dNev, dW, stW, dZ, ldz, stZ,
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dInfo, bc),
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rocblas_status_invalid_value);
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// sizes (only check batch_count if applicable)
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if(STRIDED)
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EXPECT_ROCBLAS_STATUS(rocsolver_sygvdx_hegvdx(STRIDED, handle, itype, evect, erange, uplo,
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n, dA, lda, stA, dB, ldb, stB, vl, vu, il, iu,
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dNev, dW, stW, dZ, ldz, stZ, dInfo, -1),
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rocblas_status_invalid_size);
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// pointers
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EXPECT_ROCBLAS_STATUS(rocsolver_sygvdx_hegvdx(STRIDED, handle, itype, evect, erange, uplo, n,
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(T) nullptr, lda, stA, dB, ldb, stB, vl, vu, il,
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iu, dNev, dW, stW, dZ, ldz, stZ, dInfo, bc),
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rocblas_status_invalid_pointer);
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EXPECT_ROCBLAS_STATUS(rocsolver_sygvdx_hegvdx(STRIDED, handle, itype, evect, erange, uplo, n,
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dA, lda, stA, (T) nullptr, ldb, stB, vl, vu, il,
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iu, dNev, dW, stW, dZ, ldz, stZ, dInfo, bc),
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rocblas_status_invalid_pointer);
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EXPECT_ROCBLAS_STATUS(rocsolver_sygvdx_hegvdx(STRIDED, handle, itype, evect, erange, uplo, n,
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dA, lda, stA, dB, ldb, stB, vl, vu, il, iu,
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(rocblas_int*)nullptr, dW, stW, dZ, ldz, stZ,
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dInfo, bc),
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rocblas_status_invalid_pointer);
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EXPECT_ROCBLAS_STATUS(rocsolver_sygvdx_hegvdx(STRIDED, handle, itype, evect, erange, uplo, n,
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dA, lda, stA, dB, ldb, stB, vl, vu, il, iu, dNev,
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(U) nullptr, stW, dZ, ldz, stZ, dInfo, bc),
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rocblas_status_invalid_pointer);
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EXPECT_ROCBLAS_STATUS(rocsolver_sygvdx_hegvdx(STRIDED, handle, itype, evect, erange, uplo, n,
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dA, lda, stA, dB, ldb, stB, vl, vu, il, iu, dNev,
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dW, stW, (T) nullptr, ldz, stZ, dInfo, bc),
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rocblas_status_invalid_pointer);
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EXPECT_ROCBLAS_STATUS(rocsolver_sygvdx_hegvdx(STRIDED, handle, itype, evect, erange, uplo, n,
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dA, lda, stA, dB, ldb, stB, vl, vu, il, iu, dNev,
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dW, stW, dZ, ldz, stZ, (rocblas_int*)nullptr, bc),
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rocblas_status_invalid_pointer);
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// quick return with invalid pointers
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EXPECT_ROCBLAS_STATUS(rocsolver_sygvdx_hegvdx(STRIDED, handle, itype, evect, erange, uplo, 0,
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(T) nullptr, lda, stA, (T) nullptr, ldb, stB, vl,
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vu, il, iu, dNev, (U) nullptr, stW, (T) nullptr,
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ldz, stZ, dInfo, bc),
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rocblas_status_success);
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// quick return with zero batch_count if applicable
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if(STRIDED)
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EXPECT_ROCBLAS_STATUS(rocsolver_sygvdx_hegvdx(STRIDED, handle, itype, evect, erange, uplo,
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n, dA, lda, stA, dB, ldb, stB, vl, vu, il, iu,
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(rocblas_int*)nullptr, dW, stW, dZ, ldz, stZ,
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(rocblas_int*)nullptr, 0),
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rocblas_status_success);
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}
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template <bool BATCHED, bool STRIDED, typename T>
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void testing_sygvdx_hegvdx_bad_arg()
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{
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using S = decltype(std::real(T{}));
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// safe arguments
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rocblas_local_handle handle;
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rocblas_int n = 1;
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rocblas_int lda = 1;
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rocblas_int ldb = 1;
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rocblas_int ldz = 1;
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rocblas_stride stA = 1;
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rocblas_stride stB = 1;
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rocblas_stride stW = 1;
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rocblas_stride stZ = 1;
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rocblas_int bc = 1;
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rocblas_eform itype = rocblas_eform_ax;
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rocblas_evect evect = rocblas_evect_original;
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rocblas_erange erange = rocblas_erange_value;
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rocblas_fill uplo = rocblas_fill_upper;
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S vl = 0.0;
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S vu = 1.0;
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rocblas_int il = 0;
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rocblas_int iu = 0;
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if(BATCHED)
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{
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// memory allocations
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device_batch_vector<T> dA(1, 1, 1);
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device_batch_vector<T> dB(1, 1, 1);
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device_batch_vector<T> dZ(1, 1, 1);
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device_strided_batch_vector<S> dW(1, 1, 1, 1);
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device_strided_batch_vector<rocblas_int> dNev(1, 1, 1, 1);
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device_strided_batch_vector<rocblas_int> dInfo(1, 1, 1, 1);
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CHECK_HIP_ERROR(dA.memcheck());
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CHECK_HIP_ERROR(dB.memcheck());
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CHECK_HIP_ERROR(dZ.memcheck());
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CHECK_HIP_ERROR(dW.memcheck());
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CHECK_HIP_ERROR(dNev.memcheck());
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CHECK_HIP_ERROR(dInfo.memcheck());
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// check bad arguments
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sygvdx_hegvdx_checkBadArgs<STRIDED>(handle, itype, evect, erange, uplo, n, dA.data(), lda,
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stA, dB.data(), ldb, stB, vl, vu, il, iu, dNev.data(),
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dW.data(), stW, dZ.data(), ldz, stZ, dInfo.data(), bc);
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}
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else
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{
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// memory allocations
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device_strided_batch_vector<T> dA(1, 1, 1, 1);
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device_strided_batch_vector<T> dB(1, 1, 1, 1);
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device_strided_batch_vector<T> dZ(1, 1, 1, 1);
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device_strided_batch_vector<S> dW(1, 1, 1, 1);
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device_strided_batch_vector<rocblas_int> dNev(1, 1, 1, 1);
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device_strided_batch_vector<rocblas_int> dInfo(1, 1, 1, 1);
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CHECK_HIP_ERROR(dA.memcheck());
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CHECK_HIP_ERROR(dB.memcheck());
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CHECK_HIP_ERROR(dZ.memcheck());
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CHECK_HIP_ERROR(dW.memcheck());
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CHECK_HIP_ERROR(dNev.memcheck());
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CHECK_HIP_ERROR(dInfo.memcheck());
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// check bad arguments
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sygvdx_hegvdx_checkBadArgs<STRIDED>(handle, itype, evect, erange, uplo, n, dA.data(), lda,
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stA, dB.data(), ldb, stB, vl, vu, il, iu, dNev.data(),
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dW.data(), stW, dZ.data(), ldz, stZ, dInfo.data(), bc);
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}
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}
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//
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// If the environment variable:
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//
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// ROCSOLVER_SYGVDX_HEGVDX_USE_LEGACY_TESTS
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//
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// is defined, `sygvdx_hegvdx_getError` will compute errors using the
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// legacy error bounds (for debugging purposes).
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//
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// Otherwise the new error bounds are always used.
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//
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static bool sygvdx_hegvdx_use_legacy_tests()
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{
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bool status = false;
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if(std::getenv("ROCSOLVER_SYGVDX_HEGVDX_USE_LEGACY_TESTS") != nullptr)
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{
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status = true;
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}
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return status;
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}
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//
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// The default behaviour of `sygvdx_hegvdx_getError()` is to check if the
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// number of computed eigenvalues match the number of reference eigenvalues,
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// and then to check all computed eigenvalues for their accuracy, but this
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// behaviour can be relaxed. This leads to two modes of operation: a relaxed
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// check and a full (default) check. Those are controlled by function
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// `test_for_equality_of_number_of_computed_eigenvalues()`, below, in the
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// following manner:
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//
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// a) If `ROCSOLVER_LAX_EIGENSOLVERS_TESTS` is defined, then the test suite
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// will only use the subset of computed eigenvalues that match reference
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// eigenvalues (up to the given tolerance); except
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//
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// b) If `ROCSOLVER_FULL_EIGENSOLVERS_TESTS` is defined, then the test suite
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// will unconditionally check all eigenvalues for their accuracy.
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//
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// The relaxed tests are intended as a means to decouple the computation of
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// error bounds of eigenvalues and eigenvectors, allowing tests to pass in the
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// case that not all eigenvalues could be accurately computed, but all accurate
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// eigenvalues have accurate eigenvectors. If eigenvectors are not accurate,
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// the corresponding tests will fail both in full mode and in relaxed mode.
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//
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// Note: the relaxed version of the tests is only supported when using the new
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// error bounds, see also function `sygvdx_hegvdx_use_legacy_tests()`.
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//
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static bool test_for_equality_of_number_of_computed_eigenvalues()
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{
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bool status = true;
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#if defined(ROCSOLVER_LAX_EIGENSOLVERS_TESTS)
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status = false;
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#else
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if(std::getenv("ROCSOLVER_LAX_EIGENSOLVERS_TESTS") != nullptr)
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{
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status = false;
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}
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#endif
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if(std::getenv("ROCSOLVER_FULL_EIGENSOLVERS_TESTS") != nullptr)
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{
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status = true;
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}
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return status;
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}
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template <bool CPU, bool GPU, typename T, typename Td, typename Th>
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void sygvdx_hegvdx_initData(const rocblas_handle handle,
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const rocblas_eform itype,
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const rocblas_evect evect,
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const rocblas_int n,
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Td& dA,
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const rocblas_int lda,
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const rocblas_stride stA,
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Td& dB,
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const rocblas_int ldb,
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const rocblas_stride stB,
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const rocblas_int bc,
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Th& hA,
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Th& hB,
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host_strided_batch_vector<T>& A,
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host_strided_batch_vector<T>& B,
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const bool test,
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const bool singular)
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{
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if(CPU)
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{
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rocblas_int info;
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rocblas_int ldu = n;
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host_strided_batch_vector<T> U(n * n, 1, n * n, bc);
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rocblas_init<T>(hA, true);
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rocblas_init<T>(U, true);
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bool use_legacy_tests = sygvdx_hegvdx_use_legacy_tests();
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for(rocblas_int b = 0; b < bc; ++b)
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{
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// for testing purposes, we start with a reduced matrix M for the standard equivalent problem
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// with spectrum in a desired range (-20, 20). Then we construct the generalized pair
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// (A, B) from there.
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memset(hB[b], 0,
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sizeof(T) * n * ldb); // since ldb >= n, make sure all entries of B are initialized
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for(rocblas_int i = 0; i < n; i++)
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{
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// scale matrices and set hA = M (symmetric/hermitian), hB = U (upper triangular)
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for(rocblas_int j = i; j < n; j++)
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{
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if(i == j)
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{
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hA[b][i + j * lda] = std::real(hA[b][i + j * lda]) + 10;
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U[b][i + j * ldu] = std::real(U[b][i + j * ldu]) / 100 + 1;
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hB[b][i + j * ldb] = U[b][i + j * ldu];
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}
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else
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{
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if(j == i + 1)
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{
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hA[b][i + j * lda] = (hA[b][i + j * lda] - 5) / 10;
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hA[b][j + i * lda] = sconj(hA[b][i + j * lda]);
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}
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else
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hA[b][j + i * lda] = hA[b][i + j * lda] = 0;
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U[b][i + j * ldu] = (U[b][i + j * ldu] - 5) / 100;
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hB[b][i + j * ldb] = U[b][i + j * ldu];
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hB[b][j + i * ldb] = 0;
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U[b][j + i * ldu] = 0;
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}
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}
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if(i == n / 4 || i == n / 2 || i == n - 1 || i == n / 7 || i == n / 5 || i == n / 3)
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hA[b][i + i * lda] *= -1;
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}
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// form B = U' U
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T one = T(1);
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cpu_trmm(rocblas_side_left, rocblas_fill_upper, rocblas_operation_conjugate_transpose,
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rocblas_diagonal_non_unit, n, n, one, U[b], ldu, hB[b], ldb);
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if(singular && (b == bc / 4 || b == bc / 2 || b == bc - 1))
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{
|
|
// make some matrices B not positive definite
|
|
// always the same elements for debugging purposes
|
|
// the algorithm must detect the lower order of the principal minors <= 0
|
|
// in those matrices in the batch that are non positive definite
|
|
rocblas_int i = n / 4 + b;
|
|
i -= (i / n) * n;
|
|
hB[b][i + i * ldb] = 0;
|
|
i = n / 2 + b;
|
|
i -= (i / n) * n;
|
|
hB[b][i + i * ldb] = 0;
|
|
i = n - 1 + b;
|
|
i -= (i / n) * n;
|
|
hB[b][i + i * ldb] = 0;
|
|
}
|
|
|
|
if(itype == rocblas_eform_ax)
|
|
{
|
|
// form A = U' M U
|
|
cpu_trmm(rocblas_side_left, rocblas_fill_upper, rocblas_operation_conjugate_transpose,
|
|
rocblas_diagonal_non_unit, n, n, one, U[b], ldu, hA[b], lda);
|
|
cpu_trmm(rocblas_side_right, rocblas_fill_upper, rocblas_operation_none,
|
|
rocblas_diagonal_non_unit, n, n, one, U[b], ldu, hA[b], lda);
|
|
}
|
|
else
|
|
{
|
|
// form A = inv(U) M inv(U')
|
|
cpu_trsm(rocblas_side_left, rocblas_fill_upper, rocblas_operation_none,
|
|
rocblas_diagonal_non_unit, n, n, one, U[b], ldu, hA[b], lda);
|
|
cpu_trsm(rocblas_side_right, rocblas_fill_upper,
|
|
rocblas_operation_conjugate_transpose, rocblas_diagonal_non_unit, n, n,
|
|
one, U[b], ldu, hA[b], lda);
|
|
}
|
|
|
|
// store A and B for testing purposes
|
|
if(test && evect != rocblas_evect_none)
|
|
{
|
|
for(rocblas_int i = 0; i < n; i++)
|
|
{
|
|
for(rocblas_int j = 0; j < n; j++)
|
|
{
|
|
if(use_legacy_tests)
|
|
{
|
|
if(itype != rocblas_eform_bax)
|
|
{
|
|
A[b][i + j * lda] = hA[b][i + j * lda];
|
|
B[b][i + j * ldb] = hB[b][i + j * ldb];
|
|
}
|
|
else
|
|
{
|
|
A[b][i + j * lda] = hB[b][i + j * ldb];
|
|
B[b][i + j * ldb] = hA[b][i + j * lda];
|
|
}
|
|
}
|
|
else
|
|
{
|
|
A[b][i + j * lda] = hA[b][i + j * lda];
|
|
B[b][i + j * ldb] = hB[b][i + j * ldb];
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
if(GPU)
|
|
{
|
|
// now copy data to the GPU
|
|
CHECK_HIP_ERROR(dA.transfer_from(hA));
|
|
CHECK_HIP_ERROR(dB.transfer_from(hB));
|
|
}
|
|
}
|
|
|
|
template <bool STRIDED, typename T, typename S, typename Td, typename Ud, typename Vd, typename Th, typename Uh, typename Vh>
|
|
void sygvdx_hegvdx_getError(const rocblas_handle handle,
|
|
const rocblas_eform itype,
|
|
const rocblas_evect evect,
|
|
const rocblas_erange erange,
|
|
const rocblas_fill uplo,
|
|
const rocblas_int n,
|
|
Td& dA,
|
|
const rocblas_int lda,
|
|
const rocblas_stride stA,
|
|
Td& dB,
|
|
const rocblas_int ldb,
|
|
const rocblas_stride stB,
|
|
const S vl,
|
|
const S vu,
|
|
const rocblas_int il,
|
|
const rocblas_int iu,
|
|
Vd& dNev,
|
|
Ud& dW,
|
|
const rocblas_stride stW,
|
|
Td& dZ,
|
|
const rocblas_int ldz,
|
|
const rocblas_stride stZ,
|
|
Vd& dInfo,
|
|
const rocblas_int bc,
|
|
Th& hA,
|
|
Th& hB,
|
|
Vh& hNev,
|
|
Vh& hNevRes,
|
|
Uh& hW,
|
|
Uh& hWRes,
|
|
Th& hZ,
|
|
Th& hZRes,
|
|
Vh& hInfo,
|
|
Vh& hInfoRes,
|
|
double* max_err,
|
|
const bool singular,
|
|
size_t& hashA,
|
|
size_t& hashB,
|
|
size_t& hashW,
|
|
size_t& hashZ)
|
|
{
|
|
using HMat = HostMatrix<T, rocblas_int>;
|
|
using BDesc = typename HMat::BlockDescriptor;
|
|
constexpr bool COMPLEX = rocblas_is_complex<T>;
|
|
|
|
int lwork = (COMPLEX ? 2 * n : 8 * n);
|
|
int lrwork = (COMPLEX ? 7 * n : 0);
|
|
int liwork = 5 * n;
|
|
|
|
std::vector<T> work(lwork);
|
|
std::vector<S> rwork(lrwork);
|
|
std::vector<int> iwork(liwork);
|
|
std::vector<int> hIfail(n);
|
|
host_strided_batch_vector<T> A(lda * n, 1, lda * n, bc);
|
|
host_strided_batch_vector<T> B(ldb * n, 1, ldb * n, bc);
|
|
std::vector<closest_largest_subsequences<S>> clss(bc);
|
|
std::vector<bool> skip_test(bc, false);
|
|
|
|
bool use_legacy_tests = sygvdx_hegvdx_use_legacy_tests();
|
|
bool test_for_equality = test_for_equality_of_number_of_computed_eigenvalues();
|
|
|
|
// input data initialization
|
|
sygvdx_hegvdx_initData<true, true, T>(handle, itype, evect, n, dA, lda, stA, dB, ldb, stB, bc,
|
|
hA, hB, A, B, true, singular);
|
|
|
|
// hash inputs
|
|
hashA = deterministic_hash(hA, bc);
|
|
hashB = deterministic_hash(hB, bc);
|
|
|
|
// CPU lapack
|
|
// abstol = 0 ensures max accuracy in rocsolver; for lapack we should use 2*safemin
|
|
S atol = 2 * get_safemin<S>();
|
|
for(rocblas_int b = 0; b < bc; ++b)
|
|
{
|
|
cpu_sygvx_hegvx(itype, evect, erange, uplo, n, hA[b], lda, hB[b], ldb, vl, vu, il, iu, atol,
|
|
hNev[b], hW[b], hZ[b], ldz, work.data(), lwork, rwork.data(), iwork.data(),
|
|
hIfail.data(), hInfo[b]);
|
|
|
|
// Capture failures where B is not positive definite (hInfo[b][0] > n),
|
|
// or where the i-argument has an illegal value (hInfo[b][0] < 0). All other LAPACK
|
|
// failures skip the test.
|
|
if((hInfo[b][0] > 0) && (hInfo[b][0] <= n))
|
|
{
|
|
skip_test[b] = true;
|
|
}
|
|
}
|
|
|
|
//
|
|
// Given an eigenvalue l_i of the symmetric matrix A and a computed
|
|
// eigenvalue l_i^* (obtained with a backward stable method), Weyl's
|
|
// theorem yields |l_i - l_i^*| <= K*ulp*||A||_2, where K depends on n.
|
|
// For the sake of this test, we will set K = C * n, with C ~ 1.
|
|
//
|
|
// Thus, if the range to look for eigenvalues is the interval (vl, vu],
|
|
// calls to the solver should look for computed eigenvalues in the range
|
|
// (vl - tol, vu + tol], where `tol = C * n * ulp * ||A||`.
|
|
//
|
|
S C = 10;
|
|
std::vector<S> tols(bc, 0);
|
|
std::vector<S> norms(bc, 0);
|
|
S tol = 0;
|
|
for(rocblas_int b = 0; b < bc; ++b)
|
|
{
|
|
if(hNev[b][0] > 0)
|
|
{
|
|
// Get lapack eigenvalues (reference to which rocSOLVER's sygvdx will be compared to)
|
|
auto eigsLapack = *HMat::Convert(hW[b], hNev[b][0], 1);
|
|
norms[b] = eigsLapack.max_coeff_norm();
|
|
}
|
|
else
|
|
{
|
|
norms[b] = S(0);
|
|
}
|
|
|
|
tols[b] = C * n * std::numeric_limits<S>::epsilon() * norms[b];
|
|
if(std::isfinite(tols[b]) && (tols[b] > tol))
|
|
{
|
|
tol = tols[b];
|
|
}
|
|
}
|
|
|
|
// execute computations
|
|
// GPU lapack
|
|
CHECK_ROCBLAS_ERROR(rocsolver_sygvdx_hegvdx(
|
|
STRIDED, handle, itype, evect, erange, uplo, n, dA.data(), lda, stA, dB.data(), ldb, stB,
|
|
vl, vu, il, iu, dNev.data(), dW.data(), stW, dZ.data(), ldz, stZ, dInfo.data(), bc));
|
|
|
|
CHECK_HIP_ERROR(hNevRes.transfer_from(dNev));
|
|
CHECK_HIP_ERROR(hWRes.transfer_from(dW));
|
|
CHECK_HIP_ERROR(hInfoRes.transfer_from(dInfo));
|
|
if(evect != rocblas_evect_none)
|
|
CHECK_HIP_ERROR(hZRes.transfer_from(dZ));
|
|
|
|
// hash outputs
|
|
hashW = deterministic_hash(hWRes, bc);
|
|
if(evect != rocblas_evect_none)
|
|
hashZ = deterministic_hash(hZRes, bc);
|
|
|
|
// Except for the cases in which B is indefinite, we expect the eigensolver
|
|
// to converge for all input matrices.
|
|
|
|
// check info for illegal values and/or positive-definiteness
|
|
*max_err = 0;
|
|
for(rocblas_int b = 0; b < bc; ++b)
|
|
{
|
|
// Capture failures where B is not positive definite (hInfo[b][0] > n),
|
|
// or where the i-argument has an illegal value (hInfo[b][0] < 0). All other LAPACK
|
|
// failures skip the test.
|
|
if(skip_test[b])
|
|
continue;
|
|
|
|
EXPECT_EQ(hInfo[b][0], hInfoRes[b][0]) << "where b = " << b;
|
|
if(hInfo[b][0] != hInfoRes[b][0])
|
|
*max_err += 1;
|
|
|
|
auto numMatchingEigs = clss[b](hW[b], hNev[b][0], hWRes[b], hNevRes[b][0], tols[b]);
|
|
if(test_for_equality)
|
|
{
|
|
EXPECT_EQ(hNev[b][0], numMatchingEigs) << "where b = " << b;
|
|
if(hNev[b][0] != numMatchingEigs)
|
|
*max_err += 1;
|
|
}
|
|
}
|
|
|
|
//
|
|
// Compute errors
|
|
//
|
|
double err;
|
|
|
|
for(rocblas_int b = 0; b < bc; ++b)
|
|
{
|
|
auto [lapackEigs, rocsolverEigs] = clss[b].subseqs();
|
|
auto [_, rocsolverEigsIds] = clss[b].subseqs_ids();
|
|
auto numMatchingEigs = rocsolverEigs.size();
|
|
|
|
// Number of eigenvalues computed by rocSOLVER
|
|
auto numRocsolverEigs = hNevRes[b][0];
|
|
|
|
// Only check accuracy for tests in which both computed and reference values exist and are well defined.
|
|
if(skip_test[b] || (numMatchingEigs == 0) || (hInfo[b][0] != 0))
|
|
continue;
|
|
|
|
if(evect == rocblas_evect_none)
|
|
{
|
|
//
|
|
// Only eigenvalues
|
|
//
|
|
|
|
if(use_legacy_tests)
|
|
{
|
|
err = norm_error('F', 1, numMatchingEigs, 1, lapackEigs.data(), rocsolverEigs.data());
|
|
*max_err = err > *max_err ? err : *max_err;
|
|
}
|
|
else
|
|
{
|
|
// Get computed eigenvalues
|
|
auto eigs
|
|
= *HMat::Convert(rocsolverEigs.data(), rocsolverEigs.size(),
|
|
1); // convert eigenvalues from type S to type T, if required
|
|
|
|
// Get lapack (reference) eigenvalues
|
|
auto eigsRef
|
|
= *HMat::Convert(lapackEigs.data(), lapackEigs.size(),
|
|
1); // convert eigenvalues from type S to type T, if required
|
|
err = (eigs - eigsRef).norm() / eigsRef.norm();
|
|
*max_err = err > *max_err ? err : *max_err;
|
|
}
|
|
}
|
|
else
|
|
{
|
|
//
|
|
// Both eigenvalues and eigenvectors
|
|
//
|
|
|
|
if(use_legacy_tests)
|
|
{
|
|
T alpha = 1;
|
|
T beta = 0;
|
|
|
|
// hZRes contains eigenvectors x
|
|
// compute B*x (or A*x) and store in hB
|
|
cpu_symm_hemm(rocblas_side_left, uplo, n, numRocsolverEigs, alpha, B[b], ldb,
|
|
hZRes[b], ldz, beta, hB[b], ldb);
|
|
|
|
auto [_, hWResIds] = clss[b].subseqs_ids();
|
|
if(itype == rocblas_eform_ax)
|
|
{
|
|
// problem is A*x = (lambda)*B*x
|
|
|
|
// compute (1/lambda)*A*x and store in hA
|
|
for(int j = 0; j < numMatchingEigs; j++)
|
|
{
|
|
int jj = hWResIds[j]; // Id of rocSOLVER eigen-pair associated to j-th LAPACK eigen-pair
|
|
alpha = T(1) / hWRes[b][jj];
|
|
cpu_symv_hemv(uplo, n, alpha, A[b], lda, hZRes[b] + jj * ldz, 1, beta,
|
|
hA[b] + j * lda, 1);
|
|
}
|
|
|
|
// move B*x into hZRes
|
|
for(rocblas_int i = 0; i < n; i++)
|
|
{
|
|
for(rocblas_int j = 0; j < numMatchingEigs; j++)
|
|
{
|
|
int jj = hWResIds[j]; // Id of rocSOLVER eigen-pair associated to j-th LAPACK eigen-pair
|
|
hZRes[b][i + j * ldz] = hB[b][i + jj * ldb];
|
|
}
|
|
}
|
|
}
|
|
else
|
|
{
|
|
// problem is A*B*x = (lambda)*x or B*A*x = (lambda)*x
|
|
|
|
// compute (1/lambda)*A*B*x or (1/lambda)*B*A*x and store in hA
|
|
for(int j = 0; j < numMatchingEigs; j++)
|
|
{
|
|
int jj = hWResIds[j]; // Id of rocSOLVER eigen-pair associated to j-th LAPACK eigen-pair
|
|
alpha = T(1) / hWRes[b][jj];
|
|
cpu_symv_hemv(uplo, n, alpha, A[b], lda, hB[b] + jj * ldb, 1, beta,
|
|
hA[b] + j * lda, 1);
|
|
}
|
|
// move hZRes
|
|
for(rocblas_int i = 0; i < n; i++)
|
|
{
|
|
for(rocblas_int j = 0; j < numMatchingEigs; j++)
|
|
{
|
|
int jj = hWResIds[j]; // Id of rocSOLVER eigen-pair associated to j-th LAPACK eigen-pair
|
|
if(j != jj)
|
|
hZRes[b][i + j * ldz] = hZRes[b][i + jj * ldz];
|
|
}
|
|
}
|
|
}
|
|
|
|
// error is ||hA - hZRes|| / ||hA||
|
|
// using frobenius norm
|
|
err = norm_error('F', n, numMatchingEigs, lda, hA[b], hZRes[b], ldz);
|
|
*max_err = err > *max_err ? err : *max_err;
|
|
}
|
|
else // if(!use_legacy_tests)
|
|
{
|
|
//
|
|
// Prepare input
|
|
//
|
|
|
|
// Get computed eigenvalues
|
|
auto eigs
|
|
= *HMat::Convert(rocsolverEigs.data(), rocsolverEigs.size(),
|
|
1); // convert eigenvalues from type S to type T, if required
|
|
|
|
// Get lapack (reference) eigenvalues
|
|
auto eigsRef
|
|
= *HMat::Convert(lapackEigs.data(), lapackEigs.size(),
|
|
1); // convert eigenvalues from type S to type T, if required
|
|
|
|
// Create thin wrappers of input matrices A and B
|
|
auto AWrap = HMat::Wrap(A.data() + b * lda * n, lda, n);
|
|
auto BWrap = HMat::Wrap(B.data() + b * ldb * n, ldb, n);
|
|
|
|
// We want the sub-blocks starting from row 0, col 0 and with size n x n of A and B
|
|
auto A_b = (*AWrap).block(BDesc().nrows(n).ncols(n));
|
|
auto B_b = (*BWrap).block(BDesc().nrows(n).ncols(n));
|
|
|
|
// Get computed eigenvectors
|
|
auto V_b
|
|
= (*HMat::Wrap(hZRes[b], ldz, n)).block(BDesc().nrows(n).ncols(numRocsolverEigs));
|
|
|
|
// If rocSOLVER computed more eigen-pairs then the number of
|
|
// reference eigenvalues, select the eigen-pairs that match the
|
|
// reference
|
|
if(numRocsolverEigs > numMatchingEigs)
|
|
{
|
|
rocblas_int ii;
|
|
for(rocblas_int i = 0; i < numMatchingEigs; ++i)
|
|
{
|
|
ii = rocsolverEigsIds[i];
|
|
V_b.col(i, V_b.col(ii));
|
|
}
|
|
V_b = V_b.block(BDesc().nrows(n).ncols(numMatchingEigs));
|
|
}
|
|
|
|
//
|
|
// Check eigenpairs' accuracy with a "Relative Weyl" error
|
|
// bound, which (at its simplest form) states the following.
|
|
//
|
|
// Let X (cond(X) < Inf), and A (A^* = A) be such that A has
|
|
// eigenvalues {a_i} and H = X^t*A*X has eigenvalues {h_i}.
|
|
// Then:
|
|
//
|
|
// |a_i - h_i| <= |a_i|*||X^t*X - I||_2
|
|
//
|
|
// Note: for rocSOLVER's sygv, if V is the eigenvectors' matrix
|
|
// and B = L*L^t, then either X = L^t*V (cases 1 and 2) or X =
|
|
// inv(L)*V (case 3).
|
|
//
|
|
auto VE = HMat::Empty();
|
|
if(itype == rocblas_eform_bax)
|
|
{
|
|
VE = adjoint(V_b) * inv(B_b) * V_b - HMat::Eye(numMatchingEigs);
|
|
}
|
|
else // if ((itype == rocblas_eform_ax) || (itype == rocblas_eform_abx))
|
|
{
|
|
VE = adjoint(V_b) * B_b * V_b - HMat::Eye(numMatchingEigs);
|
|
}
|
|
S eta = std::max(VE.norm(), std::numeric_limits<S>::epsilon());
|
|
*max_err = eta > *max_err ? eta : *max_err;
|
|
|
|
auto AE = HMat::Empty();
|
|
if(itype == rocblas_eform_abx)
|
|
{
|
|
auto Z = B_b * V_b;
|
|
AE = adjoint(Z) * A_b * Z - HMat::Zeros(numMatchingEigs).diag(eigs);
|
|
}
|
|
else // if ((itype == rocblas_eform_ax) || (itype == rocblas_eform_bax))
|
|
{
|
|
AE = adjoint(V_b) * A_b * V_b - HMat::Zeros(numMatchingEigs).diag(eigs);
|
|
}
|
|
err = AE.norm() / eigsRef.norm();
|
|
err *= std::numeric_limits<S>::epsilon() / eta;
|
|
*max_err = err > *max_err ? err : *max_err;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
template <bool STRIDED, typename T, typename S, typename Td, typename Ud, typename Vd, typename Th, typename Uh, typename Vh>
|
|
void sygvdx_hegvdx_getPerfData(const rocblas_handle handle,
|
|
const rocblas_eform itype,
|
|
const rocblas_evect evect,
|
|
const rocblas_erange erange,
|
|
const rocblas_fill uplo,
|
|
const rocblas_int n,
|
|
Td& dA,
|
|
const rocblas_int lda,
|
|
const rocblas_stride stA,
|
|
Td& dB,
|
|
const rocblas_int ldb,
|
|
const rocblas_stride stB,
|
|
const S vl,
|
|
const S vu,
|
|
const rocblas_int il,
|
|
const rocblas_int iu,
|
|
Vd& dNev,
|
|
Ud& dW,
|
|
const rocblas_stride stW,
|
|
Td& dZ,
|
|
const rocblas_int ldz,
|
|
const rocblas_stride stZ,
|
|
Vd& dInfo,
|
|
const rocblas_int bc,
|
|
Th& hA,
|
|
Th& hB,
|
|
Vh& hNev,
|
|
Uh& hW,
|
|
Th& hZ,
|
|
Vh& hInfo,
|
|
double* gpu_time_used,
|
|
double* cpu_time_used,
|
|
const rocblas_int hot_calls,
|
|
const int profile,
|
|
const bool profile_kernels,
|
|
const bool perf,
|
|
const bool singular)
|
|
{
|
|
host_strided_batch_vector<T> A(lda * n, 1, lda * n, bc);
|
|
host_strided_batch_vector<T> B(ldb * n, 1, ldb * n, bc);
|
|
|
|
if(!perf)
|
|
{
|
|
// cpu-lapack performance (only if not in perf mode)
|
|
*cpu_time_used = nan("");
|
|
}
|
|
|
|
sygvdx_hegvdx_initData<true, false, T>(handle, itype, evect, n, dA, lda, stA, dB, ldb, stB, bc,
|
|
hA, hB, A, B, false, singular);
|
|
|
|
// cold calls
|
|
for(int iter = 0; iter < 2; iter++)
|
|
{
|
|
sygvdx_hegvdx_initData<false, true, T>(handle, itype, evect, n, dA, lda, stA, dB, ldb, stB,
|
|
bc, hA, hB, A, B, false, singular);
|
|
|
|
CHECK_ROCBLAS_ERROR(rocsolver_sygvdx_hegvdx(
|
|
STRIDED, handle, itype, evect, erange, uplo, n, dA.data(), lda, stA, dB.data(), ldb, stB,
|
|
vl, vu, il, iu, dNev.data(), dW.data(), stW, dZ.data(), ldz, stZ, dInfo.data(), bc));
|
|
}
|
|
|
|
// gpu-lapack performance
|
|
hipStream_t stream;
|
|
CHECK_ROCBLAS_ERROR(rocblas_get_stream(handle, &stream));
|
|
rocsolver_timer timer;
|
|
|
|
if(profile > 0)
|
|
{
|
|
if(profile_kernels)
|
|
rocsolver_log_set_layer_mode(rocblas_layer_mode_log_profile
|
|
| rocblas_layer_mode_ex_log_kernel);
|
|
else
|
|
rocsolver_log_set_layer_mode(rocblas_layer_mode_log_profile);
|
|
rocsolver_log_set_max_levels(profile);
|
|
}
|
|
|
|
for(rocblas_int iter = 0; iter < hot_calls; iter++)
|
|
{
|
|
sygvdx_hegvdx_initData<false, true, T>(handle, itype, evect, n, dA, lda, stA, dB, ldb, stB,
|
|
bc, hA, hB, A, B, false, singular);
|
|
|
|
timer.start(stream);
|
|
rocsolver_sygvdx_hegvdx(STRIDED, handle, itype, evect, erange, uplo, n, dA.data(), lda, stA,
|
|
dB.data(), ldb, stB, vl, vu, il, iu, dNev.data(), dW.data(), stW,
|
|
dZ.data(), ldz, stZ, dInfo.data(), bc);
|
|
timer.end(stream);
|
|
}
|
|
*gpu_time_used = timer.get_combined();
|
|
}
|
|
|
|
template <bool BATCHED, bool STRIDED, typename T>
|
|
void testing_sygvdx_hegvdx(Arguments& argus)
|
|
{
|
|
using S = decltype(std::real(T{}));
|
|
|
|
// get arguments
|
|
rocblas_local_handle handle;
|
|
char itypeC = argus.get<char>("itype");
|
|
char evectC = argus.get<char>("evect");
|
|
char erangeC = argus.get<char>("erange");
|
|
char uploC = argus.get<char>("uplo");
|
|
rocblas_int n = argus.get<rocblas_int>("n");
|
|
rocblas_int lda = argus.get<rocblas_int>("lda", n);
|
|
rocblas_int ldb = argus.get<rocblas_int>("ldb", n);
|
|
rocblas_int ldz = argus.get<rocblas_int>("ldz", n);
|
|
rocblas_stride stA = argus.get<rocblas_stride>("strideA", lda * n);
|
|
rocblas_stride stB = argus.get<rocblas_stride>("strideB", ldb * n);
|
|
rocblas_stride stW = argus.get<rocblas_stride>("strideW", n);
|
|
rocblas_stride stZ = argus.get<rocblas_stride>("strideZ", ldz * n);
|
|
|
|
S vl = S(argus.get<double>("vl", 0));
|
|
S vu = S(argus.get<double>("vu", erangeC == 'V' ? 1 : 0));
|
|
rocblas_int il = argus.get<rocblas_int>("il", erangeC == 'I' ? 1 : 0);
|
|
rocblas_int iu = argus.get<rocblas_int>("iu", erangeC == 'I' ? 1 : 0);
|
|
|
|
rocblas_eform itype = char2rocblas_eform(itypeC);
|
|
rocblas_evect evect = char2rocblas_evect(evectC);
|
|
rocblas_erange erange = char2rocblas_erange(erangeC);
|
|
rocblas_fill uplo = char2rocblas_fill(uploC);
|
|
rocblas_int bc = argus.batch_count;
|
|
rocblas_int hot_calls = argus.iters;
|
|
|
|
rocblas_stride stWRes = (argus.unit_check || argus.norm_check || argus.hash_check) ? stW : 0;
|
|
rocblas_stride stZRes = (argus.unit_check || argus.norm_check || argus.hash_check) ? stZ : 0;
|
|
|
|
// check non-supported values
|
|
if(uplo == rocblas_fill_full || evect == rocblas_evect_tridiagonal)
|
|
{
|
|
if(BATCHED)
|
|
EXPECT_ROCBLAS_STATUS(
|
|
rocsolver_sygvdx_hegvdx(STRIDED, handle, itype, evect, erange, uplo, n,
|
|
(T* const*)nullptr, lda, stA, (T* const*)nullptr, ldb, stB,
|
|
vl, vu, il, iu, (rocblas_int*)nullptr, (S*)nullptr, stW,
|
|
(T* const*)nullptr, ldz, stZ, (rocblas_int*)nullptr, bc),
|
|
rocblas_status_invalid_value);
|
|
else
|
|
EXPECT_ROCBLAS_STATUS(
|
|
rocsolver_sygvdx_hegvdx(STRIDED, handle, itype, evect, erange, uplo, n, (T*)nullptr,
|
|
lda, stA, (T*)nullptr, ldb, stB, vl, vu, il, iu,
|
|
(rocblas_int*)nullptr, (S*)nullptr, stW, (T*)nullptr, ldz,
|
|
stZ, (rocblas_int*)nullptr, bc),
|
|
rocblas_status_invalid_value);
|
|
|
|
if(argus.timing)
|
|
rocsolver_bench_inform(inform_invalid_args);
|
|
|
|
return;
|
|
}
|
|
|
|
// determine sizes
|
|
size_t size_A = size_t(lda) * n;
|
|
size_t size_B = size_t(ldb) * n;
|
|
size_t size_W = size_t(n);
|
|
size_t size_Z = size_t(ldz) * n;
|
|
double max_error = 0, gpu_time_used = 0, cpu_time_used = 0;
|
|
size_t hashA = 0, hashB = 0, hashW = 0, hashZ = 0;
|
|
|
|
size_t size_WRes = (argus.unit_check || argus.norm_check || argus.hash_check) ? size_W : 0;
|
|
size_t size_ZRes = (argus.unit_check || argus.norm_check || argus.hash_check) ? size_Z : 0;
|
|
|
|
// check invalid sizes
|
|
bool invalid_size = (n < 0 || lda < n || ldb < n || (evect != rocblas_evect_none && ldz < n)
|
|
|| bc < 0 || (erange == rocblas_erange_value && vl >= vu)
|
|
|| (erange == rocblas_erange_index && (il < 1 || iu < 0))
|
|
|| (erange == rocblas_erange_index && (iu > n || (n > 0 && il > iu))));
|
|
if(invalid_size)
|
|
{
|
|
if(BATCHED)
|
|
EXPECT_ROCBLAS_STATUS(
|
|
rocsolver_sygvdx_hegvdx(STRIDED, handle, itype, evect, erange, uplo, n,
|
|
(T* const*)nullptr, lda, stA, (T* const*)nullptr, ldb, stB,
|
|
vl, vu, il, iu, (rocblas_int*)nullptr, (S*)nullptr, stW,
|
|
(T* const*)nullptr, ldz, stZ, (rocblas_int*)nullptr, bc),
|
|
rocblas_status_invalid_size);
|
|
else
|
|
EXPECT_ROCBLAS_STATUS(
|
|
rocsolver_sygvdx_hegvdx(STRIDED, handle, itype, evect, erange, uplo, n, (T*)nullptr,
|
|
lda, stA, (T*)nullptr, ldb, stB, vl, vu, il, iu,
|
|
(rocblas_int*)nullptr, (S*)nullptr, stW, (T*)nullptr, ldz,
|
|
stZ, (rocblas_int*)nullptr, bc),
|
|
rocblas_status_invalid_size);
|
|
|
|
if(argus.timing)
|
|
rocsolver_bench_inform(inform_invalid_size);
|
|
|
|
return;
|
|
}
|
|
|
|
// memory size query is necessary
|
|
if(argus.mem_query)
|
|
{
|
|
CHECK_ROCBLAS_ERROR(rocblas_start_device_memory_size_query(handle));
|
|
if(BATCHED)
|
|
CHECK_ALLOC_QUERY(rocsolver_sygvdx_hegvdx(
|
|
STRIDED, handle, itype, evect, erange, uplo, n, (T* const*)nullptr, lda, stA,
|
|
(T* const*)nullptr, ldb, stB, vl, vu, il, iu, (rocblas_int*)nullptr, (S*)nullptr,
|
|
stW, (T* const*)nullptr, ldz, stZ, (rocblas_int*)nullptr, bc));
|
|
else
|
|
CHECK_ALLOC_QUERY(rocsolver_sygvdx_hegvdx(
|
|
STRIDED, handle, itype, evect, erange, uplo, n, (T*)nullptr, lda, stA, (T*)nullptr,
|
|
ldb, stB, vl, vu, il, iu, (rocblas_int*)nullptr, (S*)nullptr, stW, (T*)nullptr, ldz,
|
|
stZ, (rocblas_int*)nullptr, bc));
|
|
|
|
size_t size;
|
|
CHECK_ROCBLAS_ERROR(rocblas_stop_device_memory_size_query(handle, &size));
|
|
|
|
rocsolver_bench_inform(inform_mem_query, size);
|
|
return;
|
|
}
|
|
|
|
// memory allocations (all cases)
|
|
// host
|
|
host_strided_batch_vector<rocblas_int> hNev(1, 1, 1, bc);
|
|
host_strided_batch_vector<rocblas_int> hNevRes(1, 1, 1, bc);
|
|
host_strided_batch_vector<S> hW(size_W, 1, stW, bc);
|
|
host_strided_batch_vector<S> hWRes(size_WRes, 1, stWRes, bc);
|
|
host_strided_batch_vector<rocblas_int> hInfo(1, 1, 1, bc);
|
|
host_strided_batch_vector<rocblas_int> hInfoRes(1, 1, 1, bc);
|
|
// device
|
|
device_strided_batch_vector<rocblas_int> dNev(1, 1, 1, bc);
|
|
device_strided_batch_vector<S> dW(size_W, 1, stW, bc);
|
|
device_strided_batch_vector<rocblas_int> dInfo(1, 1, 1, bc);
|
|
CHECK_HIP_ERROR(dNev.memcheck());
|
|
CHECK_HIP_ERROR(dInfo.memcheck());
|
|
if(size_W)
|
|
CHECK_HIP_ERROR(dW.memcheck());
|
|
|
|
if(BATCHED)
|
|
{
|
|
// memory allocations
|
|
host_batch_vector<T> hA(size_A, 1, bc);
|
|
host_batch_vector<T> hB(size_B, 1, bc);
|
|
host_batch_vector<T> hZ(size_Z, 1, bc);
|
|
host_batch_vector<T> hZRes(size_ZRes, 1, bc);
|
|
device_batch_vector<T> dA(size_A, 1, bc);
|
|
device_batch_vector<T> dB(size_B, 1, bc);
|
|
device_batch_vector<T> dZ(size_Z, 1, bc);
|
|
if(size_A)
|
|
CHECK_HIP_ERROR(dA.memcheck());
|
|
if(size_B)
|
|
CHECK_HIP_ERROR(dB.memcheck());
|
|
if(size_Z)
|
|
CHECK_HIP_ERROR(dZ.memcheck());
|
|
|
|
// check quick return
|
|
if(n == 0 || bc == 0)
|
|
{
|
|
EXPECT_ROCBLAS_STATUS(
|
|
rocsolver_sygvdx_hegvdx(STRIDED, handle, itype, evect, erange, uplo, n, dA.data(),
|
|
lda, stA, dB.data(), ldb, stB, vl, vu, il, iu, dNev.data(),
|
|
dW.data(), stW, dZ.data(), ldz, stZ, dInfo.data(), bc),
|
|
rocblas_status_success);
|
|
if(argus.timing)
|
|
rocsolver_bench_inform(inform_quick_return);
|
|
|
|
return;
|
|
}
|
|
|
|
// check computations
|
|
if(argus.unit_check || argus.norm_check || argus.hash_check)
|
|
sygvdx_hegvdx_getError<STRIDED, T>(
|
|
handle, itype, evect, erange, uplo, n, dA, lda, stA, dB, ldb, stB, vl, vu, il, iu,
|
|
dNev, dW, stW, dZ, ldz, stZ, dInfo, bc, hA, hB, hNev, hNevRes, hW, hWRes, hZ, hZRes,
|
|
hInfo, hInfoRes, &max_error, argus.singular, hashA, hashB, hashW, hashZ);
|
|
|
|
// collect performance data
|
|
if(argus.timing && hot_calls > 0)
|
|
sygvdx_hegvdx_getPerfData<STRIDED, T>(
|
|
handle, itype, evect, erange, uplo, n, dA, lda, stA, dB, ldb, stB, vl, vu, il, iu,
|
|
dNev, dW, stW, dZ, ldz, stZ, dInfo, bc, hA, hB, hNev, hW, hZ, hInfo, &gpu_time_used,
|
|
&cpu_time_used, hot_calls, argus.profile, argus.profile_kernels, argus.perf,
|
|
argus.singular);
|
|
}
|
|
|
|
else
|
|
{
|
|
// memory allocations
|
|
host_strided_batch_vector<T> hA(size_A, 1, stA, bc);
|
|
host_strided_batch_vector<T> hB(size_B, 1, stB, bc);
|
|
host_strided_batch_vector<T> hZ(size_Z, 1, stZ, bc);
|
|
host_strided_batch_vector<T> hZRes(size_ZRes, 1, stZRes, bc);
|
|
device_strided_batch_vector<T> dA(size_A, 1, stA, bc);
|
|
device_strided_batch_vector<T> dB(size_B, 1, stB, bc);
|
|
device_strided_batch_vector<T> dZ(size_Z, 1, stZ, bc);
|
|
if(size_A)
|
|
CHECK_HIP_ERROR(dA.memcheck());
|
|
if(size_B)
|
|
CHECK_HIP_ERROR(dB.memcheck());
|
|
if(size_Z)
|
|
CHECK_HIP_ERROR(dZ.memcheck());
|
|
|
|
// check quick return
|
|
if(n == 0 || bc == 0)
|
|
{
|
|
EXPECT_ROCBLAS_STATUS(
|
|
rocsolver_sygvdx_hegvdx(STRIDED, handle, itype, evect, erange, uplo, n, dA.data(),
|
|
lda, stA, dB.data(), ldb, stB, vl, vu, il, iu, dNev.data(),
|
|
dW.data(), stW, dZ.data(), ldz, stZ, dInfo.data(), bc),
|
|
rocblas_status_success);
|
|
if(argus.timing)
|
|
rocsolver_bench_inform(inform_quick_return);
|
|
|
|
return;
|
|
}
|
|
|
|
// check computations
|
|
if(argus.unit_check || argus.norm_check || argus.hash_check)
|
|
sygvdx_hegvdx_getError<STRIDED, T>(
|
|
handle, itype, evect, erange, uplo, n, dA, lda, stA, dB, ldb, stB, vl, vu, il, iu,
|
|
dNev, dW, stW, dZ, ldz, stZ, dInfo, bc, hA, hB, hNev, hNevRes, hW, hWRes, hZ, hZRes,
|
|
hInfo, hInfoRes, &max_error, argus.singular, hashA, hashB, hashW, hashZ);
|
|
|
|
// collect performance data
|
|
if(argus.timing && hot_calls > 0)
|
|
sygvdx_hegvdx_getPerfData<STRIDED, T>(
|
|
handle, itype, evect, erange, uplo, n, dA, lda, stA, dB, ldb, stB, vl, vu, il, iu,
|
|
dNev, dW, stW, dZ, ldz, stZ, dInfo, bc, hA, hB, hNev, hW, hZ, hInfo, &gpu_time_used,
|
|
&cpu_time_used, hot_calls, argus.profile, argus.profile_kernels, argus.perf,
|
|
argus.singular);
|
|
}
|
|
|
|
// validate results for rocsolver-test
|
|
// using 8 * n * machine_precision as tolerance
|
|
if(argus.unit_check)
|
|
ROCSOLVER_TEST_CHECK(T, max_error, 8 * n);
|
|
|
|
// output results for rocsolver-bench
|
|
if(argus.timing)
|
|
{
|
|
if(!argus.perf)
|
|
{
|
|
rocsolver_bench_header("Arguments:");
|
|
if(BATCHED)
|
|
{
|
|
rocsolver_bench_output("itype", "evect", "erange", "uplo", "n", "lda", "ldb", "vl",
|
|
"vu", "il", "iu", "strideW", "ldz", "batch_c");
|
|
rocsolver_bench_output(itypeC, evectC, erangeC, uploC, n, lda, ldb, vl, vu, il, iu,
|
|
stW, ldz, bc);
|
|
}
|
|
else if(STRIDED)
|
|
{
|
|
rocsolver_bench_output("itype", "evect", "erange", "uplo", "n", "lda", "ldb",
|
|
"strideA", "strideB", "vl", "vu", "il", "iu", "strideW",
|
|
"ldz", "strideZ", "batch_c");
|
|
rocsolver_bench_output(itypeC, evectC, erangeC, uploC, n, lda, ldb, stA, stB, vl,
|
|
vu, il, iu, stW, ldz, stZ, bc);
|
|
}
|
|
else
|
|
{
|
|
rocsolver_bench_output("itype", "evect", "erange", "uplo", "n", "lda", "ldb", "vl",
|
|
"vu", "il", "iu", "ldz");
|
|
rocsolver_bench_output(itypeC, evectC, erangeC, uploC, n, lda, ldb, vl, vu, il, iu,
|
|
ldz);
|
|
}
|
|
rocsolver_bench_header("Results:");
|
|
if(argus.norm_check)
|
|
{
|
|
rocsolver_bench_output("cpu_time", "gpu_time", "error");
|
|
rocsolver_bench_output(cpu_time_used, gpu_time_used, max_error);
|
|
}
|
|
else
|
|
{
|
|
rocsolver_bench_output("cpu_time", "gpu_time");
|
|
rocsolver_bench_output(cpu_time_used, gpu_time_used);
|
|
}
|
|
rocsolver_bench_endl();
|
|
if(argus.hash_check)
|
|
{
|
|
rocsolver_bench_output("hash(A)", "hash(B)", "hash(W)", "hash(Z)");
|
|
rocsolver_bench_output(ROCSOLVER_FORMAT_HASH(hashA), ROCSOLVER_FORMAT_HASH(hashB),
|
|
ROCSOLVER_FORMAT_HASH(hashW), ROCSOLVER_FORMAT_HASH(hashZ));
|
|
rocsolver_bench_endl();
|
|
}
|
|
}
|
|
else
|
|
{
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if(argus.norm_check)
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|
rocsolver_bench_output(gpu_time_used, max_error);
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|
else
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rocsolver_bench_output(gpu_time_used);
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|
}
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|
}
|
|
|
|
// ensure all arguments were consumed
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|
argus.validate_consumed();
|
|
}
|
|
|
|
#define EXTERN_TESTING_SYGVDX_HEGVDX(...) \
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|
extern template void testing_sygvdx_hegvdx<__VA_ARGS__>(Arguments&);
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|
|
|
INSTANTIATE(EXTERN_TESTING_SYGVDX_HEGVDX, FOREACH_MATRIX_DATA_LAYOUT, FOREACH_SCALAR_TYPE, APPLY_STAMP)
|