derek.holloway
7502bf64a4
CodeQL / Analyze (actions) (push) Canceled after 0s
CodeQL / Analyze (python) (push) Canceled after 0s
pre-commit / pre-commit (push) Canceled after 0s
Multi-Arch CI / setup (push) Canceled after 0s
Publish build_manylinux_x86_64 images / publish_build_manylinux_x86_64 (push) Canceled after 0s
Setup (Multi-Arch) / setup (push) Canceled after 0s
Multi-Arch CI / Linux::${{ fromJSON(needs.setup.outputs.linux_build_config || '{}').build_variant_label || 'skip' }} (push) Canceled after 0s
Publish TheRock Docker image / build-and-push-image (push) Canceled after 0s
Publish no_rocm_image_ubi10 image / publish_no_rocm_image_ubi10 (push) Canceled after 0s
Multi-Arch CI / Windows::${{ fromJSON(needs.setup.outputs.windows_build_config || '{}').build_variant_label || 'skip' }} (push) Canceled after 0s
Publish TheRock Docker image / build-and-push-image (push) Canceled after 0s
Multi-Arch CI / Manifest Diff (push) Canceled after 0s
TheRock Manifest Diff Report / Generate Manifest Diff Report (push) Canceled after 0s
Multi-Arch CI / CI Summary (push) Canceled after 0s
Publish no_rocm_image_ubuntu24_04 images / publish_no_rocm_image_ubuntu24_04 (push) Canceled after 0s
Publish no_rocm_image_ubuntu24_04_ocl_rt images / publish_no_rocm_image_ubuntu24_04_ocl_rt (push) Canceled after 0s
Publish TheRock Docker image / build-and-push-image (push) Canceled after 0s
Publish TheRock Docker image / build-and-push-image (push) Canceled after 0s
Publish no_rocm_image_ubuntu24_04 images / publish_no_rocm_image_ubuntu24_04_rocgdb (push) Canceled after 0s
Publish no_rocm_image_ubuntu24_04_rocgdb images / publish_no_rocm_image_ubuntu24_04_rocgdb (push) Canceled after 0s
Publish no_rocm_image_ubuntu24_04 images / publish_no_rocm_image_ubuntu24_04_ocl_rt (push) Canceled after 0s
Publish TheRock Docker image / build-and-push-image (push) Canceled after 0s
Unit Tests / Unit Tests :: ubuntu-24.04 (push) Canceled after 0s
Unit Tests / Unit Tests :: windows-2022 (push) Canceled after 0s
Publish no_rocm_image_ubuntu24_04 images / publish_no_rocm_image_ubuntu24_04_media (push) Canceled after 0s
Unit Tests / Unit Tests Summary (push) Canceled after 0s
Publish no_rocm_image_ubuntu24_04 images / publish_no_rocm_image_ubuntu24_04_openmpi (push) Canceled after 0s
1202 lines
48 KiB
C++
1202 lines
48 KiB
C++
/* ************************************************************************
|
|
* Copyright (C) 2026 Advanced Micro Devices, Inc. All rights reserved.
|
|
*
|
|
* Permission is hereby granted, free of charge, to any person obtaining a copy
|
|
* of this software and associated documentation files (the "Software"), to deal
|
|
* in the Software without restriction, including without limitation the rights
|
|
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell cop-
|
|
* ies of the Software, and to permit persons to whom the Software is furnished
|
|
* to do so, subject to the following conditions:
|
|
*
|
|
* The above copyright notice and this permission notice shall be included in all
|
|
* copies or substantial portions of the Software.
|
|
*
|
|
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IM-
|
|
* PLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS
|
|
* FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
|
|
* COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER
|
|
* IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNE-
|
|
* CTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
|
|
*
|
|
*
|
|
* ************************************************************************ */
|
|
|
|
#pragma once
|
|
|
|
#include <cstdio>
|
|
#include <iostream>
|
|
#include <string>
|
|
#include <type_traits>
|
|
|
|
#include "clientcommon.hpp"
|
|
|
|
static bool test_left_eigenvectors
|
|
= false; // Computing left eigenvectors is not supported in cuSOLVER.
|
|
static bool test_right_eigenvectors = true;
|
|
|
|
template <testAPI_t API,
|
|
typename I,
|
|
typename SIZE,
|
|
typename Td,
|
|
typename Wd,
|
|
typename INTd,
|
|
typename Th>
|
|
void geev_checkBadArgs(const hipsolverHandle_t handle,
|
|
const hipsolverDnParams_t params,
|
|
const hipsolverEigMode_t jobvl,
|
|
const hipsolverEigMode_t jobvr,
|
|
const I n,
|
|
Td dA,
|
|
const I lda,
|
|
Wd dW,
|
|
Td dVL,
|
|
const I ldvl,
|
|
Td dVR,
|
|
const I ldvr,
|
|
Td dWork,
|
|
const SIZE dlwork,
|
|
Th hWork,
|
|
const SIZE hlwork,
|
|
INTd dinfo)
|
|
{
|
|
// Check handle.
|
|
EXPECT_ROCBLAS_STATUS(hipsolver_geev(API,
|
|
(hipsolverHandle_t) nullptr,
|
|
params,
|
|
jobvl,
|
|
jobvr,
|
|
n,
|
|
dA,
|
|
lda,
|
|
dW,
|
|
dVL,
|
|
ldvl,
|
|
dVR,
|
|
ldvr,
|
|
dWork,
|
|
dlwork,
|
|
hWork,
|
|
hlwork,
|
|
dinfo),
|
|
HIPSOLVER_STATUS_NOT_INITIALIZED);
|
|
|
|
#if defined(__HIP_PLATFORM_HCC__) || defined(__HIP_PLATFORM_AMD__)
|
|
//
|
|
// Check pointers.
|
|
//
|
|
EXPECT_ROCBLAS_STATUS(hipsolver_geev(API,
|
|
handle,
|
|
(hipsolverDnParams_t) nullptr,
|
|
jobvl,
|
|
jobvr,
|
|
n,
|
|
dA,
|
|
lda,
|
|
dW,
|
|
dVL,
|
|
ldvl,
|
|
dVR,
|
|
ldvr,
|
|
dWork,
|
|
dlwork,
|
|
hWork,
|
|
hlwork,
|
|
dinfo),
|
|
HIPSOLVER_STATUS_INVALID_VALUE);
|
|
EXPECT_ROCBLAS_STATUS(hipsolver_geev(API,
|
|
handle,
|
|
params,
|
|
jobvl,
|
|
jobvr,
|
|
n,
|
|
(Td) nullptr,
|
|
lda,
|
|
dW,
|
|
dVL,
|
|
ldvl,
|
|
dVR,
|
|
ldvr,
|
|
dWork,
|
|
dlwork,
|
|
hWork,
|
|
hlwork,
|
|
dinfo),
|
|
HIPSOLVER_STATUS_INVALID_VALUE);
|
|
EXPECT_ROCBLAS_STATUS(hipsolver_geev(API,
|
|
handle,
|
|
params,
|
|
jobvl,
|
|
jobvr,
|
|
n,
|
|
dA,
|
|
lda,
|
|
(Wd) nullptr,
|
|
dVL,
|
|
ldvl,
|
|
dVR,
|
|
ldvr,
|
|
dWork,
|
|
dlwork,
|
|
hWork,
|
|
hlwork,
|
|
dinfo),
|
|
HIPSOLVER_STATUS_INVALID_VALUE);
|
|
EXPECT_ROCBLAS_STATUS(hipsolver_geev(API,
|
|
handle,
|
|
params,
|
|
HIPSOLVER_EIG_MODE_VECTOR,
|
|
jobvr,
|
|
n,
|
|
dA,
|
|
lda,
|
|
dW,
|
|
(Td) nullptr,
|
|
ldvl,
|
|
dVR,
|
|
ldvr,
|
|
dWork,
|
|
dlwork,
|
|
hWork,
|
|
hlwork,
|
|
dinfo),
|
|
HIPSOLVER_STATUS_INVALID_VALUE);
|
|
EXPECT_ROCBLAS_STATUS(hipsolver_geev(API,
|
|
handle,
|
|
params,
|
|
jobvl,
|
|
HIPSOLVER_EIG_MODE_VECTOR,
|
|
n,
|
|
dA,
|
|
lda,
|
|
dW,
|
|
dVL,
|
|
ldvl,
|
|
(Td) nullptr,
|
|
ldvr,
|
|
dWork,
|
|
dlwork,
|
|
hWork,
|
|
hlwork,
|
|
dinfo),
|
|
HIPSOLVER_STATUS_INVALID_VALUE);
|
|
/* Note: `workOnDevice` is still allowed to be `nullptr` */
|
|
/* EXPECT_ROCBLAS_STATUS(hipsolver_geev(API, */
|
|
/* handle, */
|
|
/* params, */
|
|
/* jobvl, */
|
|
/* jobvr, */
|
|
/* n, */
|
|
/* dA, */
|
|
/* lda, */
|
|
/* dW, */
|
|
/* dVL, */
|
|
/* ldvl, */
|
|
/* dVR, */
|
|
/* ldvr, */
|
|
/* (Td) nullptr, */
|
|
/* dlwork, */
|
|
/* hWork, */
|
|
/* hlwork, */
|
|
/* dinfo), */
|
|
/* HIPSOLVER_STATUS_INVALID_VALUE); */
|
|
EXPECT_ROCBLAS_STATUS(hipsolver_geev(API,
|
|
handle,
|
|
params,
|
|
jobvl,
|
|
jobvr,
|
|
n,
|
|
dA,
|
|
lda,
|
|
dW,
|
|
dVL,
|
|
ldvl,
|
|
dVR,
|
|
ldvr,
|
|
dWork,
|
|
dlwork,
|
|
(Th) nullptr,
|
|
hlwork,
|
|
dinfo),
|
|
HIPSOLVER_STATUS_INVALID_VALUE);
|
|
EXPECT_ROCBLAS_STATUS(hipsolver_geev(API,
|
|
handle,
|
|
params,
|
|
jobvl,
|
|
jobvr,
|
|
n,
|
|
dA,
|
|
lda,
|
|
dW,
|
|
dVL,
|
|
ldvl,
|
|
dVR,
|
|
ldvr,
|
|
dWork,
|
|
dlwork,
|
|
hWork,
|
|
hlwork,
|
|
(INTd) nullptr),
|
|
HIPSOLVER_STATUS_INVALID_VALUE);
|
|
//
|
|
// Check values.
|
|
//
|
|
EXPECT_ROCBLAS_STATUS(hipsolver_geev(API,
|
|
handle,
|
|
params,
|
|
hipsolverEigMode_t(-1),
|
|
jobvr,
|
|
n,
|
|
dA,
|
|
lda,
|
|
dW,
|
|
dVL,
|
|
ldvl,
|
|
dVR,
|
|
ldvr,
|
|
dWork,
|
|
dlwork,
|
|
hWork,
|
|
hlwork,
|
|
dinfo),
|
|
HIPSOLVER_STATUS_INVALID_ENUM);
|
|
EXPECT_ROCBLAS_STATUS(hipsolver_geev(API,
|
|
handle,
|
|
params,
|
|
jobvl,
|
|
hipsolverEigMode_t(-1),
|
|
n,
|
|
dA,
|
|
lda,
|
|
dW,
|
|
dVL,
|
|
ldvl,
|
|
dVR,
|
|
ldvr,
|
|
dWork,
|
|
dlwork,
|
|
hWork,
|
|
hlwork,
|
|
dinfo),
|
|
HIPSOLVER_STATUS_INVALID_ENUM);
|
|
EXPECT_ROCBLAS_STATUS(hipsolver_geev(API,
|
|
handle,
|
|
params,
|
|
jobvl,
|
|
jobvr,
|
|
-1,
|
|
dA,
|
|
lda,
|
|
dW,
|
|
dVL,
|
|
ldvl,
|
|
dVR,
|
|
ldvr,
|
|
dWork,
|
|
dlwork,
|
|
hWork,
|
|
hlwork,
|
|
dinfo),
|
|
HIPSOLVER_STATUS_INVALID_VALUE);
|
|
EXPECT_ROCBLAS_STATUS(hipsolver_geev(API,
|
|
handle,
|
|
params,
|
|
jobvl,
|
|
jobvr,
|
|
n,
|
|
dA,
|
|
-1,
|
|
dW,
|
|
dVL,
|
|
ldvl,
|
|
dVR,
|
|
ldvr,
|
|
dWork,
|
|
dlwork,
|
|
hWork,
|
|
hlwork,
|
|
dinfo),
|
|
HIPSOLVER_STATUS_INVALID_VALUE);
|
|
EXPECT_ROCBLAS_STATUS(hipsolver_geev(API,
|
|
handle,
|
|
params,
|
|
jobvl,
|
|
jobvr,
|
|
n,
|
|
dA,
|
|
lda,
|
|
dW,
|
|
dVL,
|
|
-1,
|
|
dVR,
|
|
ldvr,
|
|
dWork,
|
|
dlwork,
|
|
hWork,
|
|
hlwork,
|
|
dinfo),
|
|
HIPSOLVER_STATUS_INVALID_VALUE);
|
|
EXPECT_ROCBLAS_STATUS(hipsolver_geev(API,
|
|
handle,
|
|
params,
|
|
jobvl,
|
|
jobvr,
|
|
n,
|
|
dA,
|
|
lda,
|
|
dW,
|
|
dVL,
|
|
ldvl,
|
|
dVR,
|
|
-1,
|
|
dWork,
|
|
dlwork,
|
|
hWork,
|
|
hlwork,
|
|
dinfo),
|
|
HIPSOLVER_STATUS_INVALID_VALUE);
|
|
#endif
|
|
}
|
|
|
|
template <testAPI_t API,
|
|
bool BATCHED,
|
|
bool STRIDED,
|
|
typename T,
|
|
typename W,
|
|
typename I,
|
|
typename SIZE>
|
|
void testing_geev_bad_arg()
|
|
{
|
|
// safe arguments
|
|
hipsolver_local_handle handle;
|
|
hipsolver_local_params params;
|
|
hipsolverEigMode_t jobvl = HIPSOLVER_EIG_MODE_NOVECTOR;
|
|
hipsolverEigMode_t jobvr = HIPSOLVER_EIG_MODE_NOVECTOR;
|
|
I n = 1;
|
|
I lda = 1;
|
|
I ldvl = 1;
|
|
I ldvr = 1;
|
|
|
|
if(BATCHED)
|
|
{
|
|
// unsupported
|
|
}
|
|
else
|
|
{
|
|
// memory allocations
|
|
device_strided_batch_vector<T> dA(1, 1, 1, 1);
|
|
device_strided_batch_vector<W> dW(1, 1, 1, 1);
|
|
device_strided_batch_vector<T> dVL(1, 1, 1, 1);
|
|
device_strided_batch_vector<T> dVR(1, 1, 1, 1);
|
|
device_strided_batch_vector<int> dInfo(1, 1, 1, 1);
|
|
CHECK_HIP_ERROR(dA.memcheck());
|
|
CHECK_HIP_ERROR(dW.memcheck());
|
|
CHECK_HIP_ERROR(dVL.memcheck());
|
|
CHECK_HIP_ERROR(dVR.memcheck());
|
|
CHECK_HIP_ERROR(dInfo.memcheck());
|
|
|
|
SIZE size_dW, size_hW;
|
|
CHECK_ROCBLAS_ERROR(hipsolver_geev_bufferSize(API,
|
|
handle,
|
|
params,
|
|
jobvl,
|
|
jobvr,
|
|
n,
|
|
dA.data(),
|
|
lda,
|
|
dW.data(),
|
|
dVL.data(),
|
|
ldvl,
|
|
dVR.data(),
|
|
ldvr,
|
|
&size_dW,
|
|
&size_hW));
|
|
host_strided_batch_vector<T> hWork(size_hW, 1, size_hW, 1);
|
|
device_strided_batch_vector<T> dWork(size_dW, 1, size_dW, 1);
|
|
if(size_dW)
|
|
CHECK_HIP_ERROR(dWork.memcheck());
|
|
|
|
// check bad arguments
|
|
geev_checkBadArgs<API>(handle,
|
|
params,
|
|
jobvl,
|
|
jobvr,
|
|
n,
|
|
dA.data(),
|
|
lda,
|
|
dW.data(),
|
|
dVL.data(),
|
|
ldvl,
|
|
dVR.data(),
|
|
ldvr,
|
|
dWork.data(),
|
|
size_dW,
|
|
hWork.data(),
|
|
size_hW,
|
|
dInfo.data());
|
|
}
|
|
}
|
|
|
|
template <bool CPU, bool GPU, typename T, typename I, typename Td, typename Th>
|
|
void geev_initData(const hipsolverHandle_t handle,
|
|
const hipsolverDnParams_t params,
|
|
const I n,
|
|
Td& dA,
|
|
const I lda,
|
|
Th& hA)
|
|
{
|
|
if(CPU)
|
|
{
|
|
// TODO: Add option to create defective matrices.
|
|
|
|
// Create a (non-symmetric) Sylvester-Kac/Clement matrix. For a given
|
|
// dimension `n`, the spectrum of hA[0] is composed of the following `n`
|
|
// distinct integers:
|
|
//
|
|
// -(n-1), -(n-1) + 2, -(n-1) + 4, ..., (n-1) - 2, (n-1).
|
|
//
|
|
for(int i = 0; i < n; ++i)
|
|
{
|
|
for(int j = 0; j < n; ++j)
|
|
{
|
|
hA[0][i + j * lda] = T(0);
|
|
}
|
|
}
|
|
|
|
for(int i = 1; i < n; ++i)
|
|
{
|
|
hA[0][i + (i - 1) * lda] = T(n - i);
|
|
hA[0][(i - 1) + i * lda] = T(i);
|
|
}
|
|
|
|
/* // Temporary: Create a symmetric Clement matrix to simplify testing. */
|
|
/* // */
|
|
/* // The main reason to rely on the symmetric version of the Clement */
|
|
/* // matrices is to guarantee that computed eigenvalues will be real */
|
|
/* // (numerically) for all relevant test sizes; this will be removed in */
|
|
/* // favor of the general (non-symmetric) Clement matrices when the test */
|
|
/* // routine is complete. */
|
|
/* for(int i = 0; i < n; ++i) */
|
|
/* { */
|
|
/* for(int j = 0; j < n; ++j) */
|
|
/* { */
|
|
/* if(i == j + 1) */
|
|
/* { */
|
|
/* hA[0][i + j * lda] = std::sqrt(i * (n - i)); */
|
|
/* hA[0][j + i * lda] = std::sqrt(i * (n - i)); */
|
|
/* } */
|
|
/* else */
|
|
/* { */
|
|
/* hA[0][i + j * lda] = T(0); */
|
|
/* } */
|
|
/* } */
|
|
/* } */
|
|
/* print_array(hA[0], n, n, lda, "hA[0] = "); */
|
|
}
|
|
|
|
if(GPU)
|
|
{
|
|
// now copy data to the GPU
|
|
CHECK_HIP_ERROR(dA.transfer_from(hA));
|
|
}
|
|
}
|
|
|
|
template <testAPI_t API,
|
|
typename T,
|
|
typename W,
|
|
typename I,
|
|
typename SIZE,
|
|
typename Td,
|
|
typename Wd,
|
|
typename INTd,
|
|
typename Th,
|
|
typename Wh,
|
|
typename CTh,
|
|
typename INTh>
|
|
void geev_getError(const hipsolverHandle_t handle,
|
|
const hipsolverDnParams_t params,
|
|
const hipsolverEigMode_t jobvl,
|
|
const hipsolverEigMode_t jobvr,
|
|
const I n,
|
|
Td& dA,
|
|
const I lda,
|
|
Wd& dW,
|
|
Td& dVL,
|
|
const I ldvl,
|
|
Td& dVR,
|
|
const I ldvr,
|
|
Td& dWork,
|
|
const SIZE dlwork,
|
|
Th& hWork,
|
|
const SIZE hlwork,
|
|
INTd& dInfo,
|
|
Th& hA,
|
|
CTh& hCA,
|
|
Th& hARes,
|
|
Wh& hW,
|
|
Wh& hWRes,
|
|
CTh& hVL,
|
|
Th& hVLRes,
|
|
CTh& hVR,
|
|
Th& hVRRes,
|
|
INTh& hInfo,
|
|
INTh& hInfoRes,
|
|
Th& hD,
|
|
CTh& hCD,
|
|
Th& hErr,
|
|
CTh& hCErr,
|
|
double* max_err)
|
|
{
|
|
// Initialize extra type used to simplify testing when type `T` is real.
|
|
using CT = std::conditional_t<
|
|
std::is_same_v<T, float>,
|
|
hipsolverComplex,
|
|
std::conditional_t<std::is_same_v<T, double>, hipsolverDoubleComplex, T>>;
|
|
|
|
// Initialize variables used in 2nd run.
|
|
bool vl_2nd_run = test_left_eigenvectors;
|
|
bool vr_2nd_run = test_right_eigenvectors;
|
|
hipsolverEigMode_t jobvl_2nd_run
|
|
= test_left_eigenvectors ? HIPSOLVER_EIG_MODE_VECTOR : HIPSOLVER_EIG_MODE_NOVECTOR;
|
|
hipsolverEigMode_t jobvr_2nd_run
|
|
= test_right_eigenvectors ? HIPSOLVER_EIG_MODE_VECTOR : HIPSOLVER_EIG_MODE_NOVECTOR;
|
|
I ldvl_2nd_run = n;
|
|
I ldvr_2nd_run = n;
|
|
I ldvl_{ldvl};
|
|
I ldvr_{ldvr};
|
|
|
|
// input data initialization
|
|
geev_initData<true, true, T>(handle, params, n, dA, lda, hA);
|
|
|
|
//
|
|
// Execute computations
|
|
// GPU lapack
|
|
//
|
|
CHECK_ROCBLAS_ERROR(hipsolver_geev(API,
|
|
handle,
|
|
params,
|
|
jobvl,
|
|
jobvr,
|
|
n,
|
|
dA.data(),
|
|
lda,
|
|
dW.data(),
|
|
dVL.data(),
|
|
ldvl,
|
|
dVR.data(),
|
|
ldvr,
|
|
dWork.data(),
|
|
dlwork,
|
|
hWork.data(),
|
|
hlwork,
|
|
dInfo.data()));
|
|
CHECK_HIP_ERROR(hARes.transfer_from(dA));
|
|
CHECK_HIP_ERROR(hWRes.transfer_from(dW));
|
|
if(jobvl != HIPSOLVER_EIG_MODE_NOVECTOR)
|
|
{
|
|
CHECK_HIP_ERROR(hVLRes.transfer_from(dVL));
|
|
vl_2nd_run = false;
|
|
jobvl_2nd_run = HIPSOLVER_EIG_MODE_NOVECTOR;
|
|
}
|
|
if(jobvr != HIPSOLVER_EIG_MODE_NOVECTOR)
|
|
{
|
|
CHECK_HIP_ERROR(hVRRes.transfer_from(dVR));
|
|
vr_2nd_run = false;
|
|
jobvr_2nd_run = HIPSOLVER_EIG_MODE_NOVECTOR;
|
|
}
|
|
CHECK_HIP_ERROR(hInfoRes.transfer_from(dInfo));
|
|
|
|
//
|
|
// `geev` is supposed to converge for all input test matrices, if
|
|
// `info != 0` test has failed.
|
|
//
|
|
EXPECT_EQ(hInfoRes[0][0], 0);
|
|
if(hInfoRes[0][0] != 0)
|
|
{
|
|
*max_err += 1;
|
|
return;
|
|
}
|
|
|
|
//
|
|
// Execute `geev` a second time to get missing left and right eigenvectors
|
|
// (if necessary).
|
|
//
|
|
CHECK_HIP_ERROR(dA.transfer_from(hA));
|
|
if(vl_2nd_run || vr_2nd_run)
|
|
{
|
|
CHECK_ROCBLAS_ERROR(hipsolver_geev(API,
|
|
handle,
|
|
params,
|
|
jobvl_2nd_run,
|
|
jobvr_2nd_run,
|
|
n,
|
|
dA.data(),
|
|
lda,
|
|
dW.data(),
|
|
dVL.data(),
|
|
ldvl_2nd_run,
|
|
dVR.data(),
|
|
ldvr_2nd_run,
|
|
dWork.data(),
|
|
dlwork,
|
|
hWork.data(),
|
|
hlwork,
|
|
dInfo.data()));
|
|
|
|
if(jobvl_2nd_run != HIPSOLVER_EIG_MODE_NOVECTOR)
|
|
{
|
|
CHECK_HIP_ERROR(hVLRes.transfer_from(dVL));
|
|
ldvl_ = ldvl_2nd_run;
|
|
}
|
|
if(jobvr_2nd_run != HIPSOLVER_EIG_MODE_NOVECTOR)
|
|
{
|
|
CHECK_HIP_ERROR(hVRRes.transfer_from(dVR));
|
|
ldvr_ = ldvr_2nd_run;
|
|
}
|
|
}
|
|
|
|
//
|
|
// [Not implemented:] Execute `geev` a third time (if necessary) to check if eigenvalues change when
|
|
// `geev`'s input parameters change.
|
|
//
|
|
|
|
//
|
|
// Compute error(s).
|
|
// *** Note: FOR NOW, the tests' code require the spectrum of A to be real. ***
|
|
//
|
|
double err{};
|
|
double normA = snorm('F', n, n, hA[0], lda);
|
|
CT alpha, beta;
|
|
|
|
CT* A = hCA[0];
|
|
CT* D = hCD[0];
|
|
CT* VR = hVR[0];
|
|
CT* VL = hVL[0];
|
|
CT* Err = hCErr[0];
|
|
if constexpr(!std::is_same<W, CT>())
|
|
{
|
|
for(int j = 0; j < n; ++j)
|
|
{
|
|
for(int i = 0; i < n; ++i)
|
|
{
|
|
if(i == j)
|
|
D[i + j * n] = {hWRes[0][j], hWRes[0][j + n]};
|
|
else
|
|
D[i + j * n] = CT(0);
|
|
}
|
|
}
|
|
}
|
|
else // is_same<W, CT>
|
|
{
|
|
for(int j = 0; j < n; ++j)
|
|
{
|
|
for(int i = 0; i < n; ++i)
|
|
{
|
|
if(i == j)
|
|
D[i + j * n] = hWRes[0][j];
|
|
else
|
|
D[i + j * n] = CT(0);
|
|
}
|
|
}
|
|
}
|
|
|
|
if constexpr(!is_complex<T>)
|
|
{
|
|
for(int j = 0; j < n; ++j)
|
|
{
|
|
auto VRij = [ld = ldvr_, V = hVRRes[0]](I i, I j) -> T { return V[i + j * ld]; };
|
|
auto VLij = [ld = ldvl_, V = hVLRes[0]](I i, I j) -> T { return V[i + j * ld]; };
|
|
for(int i = 0; i < n; ++i)
|
|
{
|
|
A[i + j * lda] = {hA[0][i + j * lda], 0};
|
|
|
|
if(D[j + j * n].imag() > 0)
|
|
{
|
|
if(test_right_eigenvectors)
|
|
VR[i + j * ldvr_] = {VRij(i, j), VRij(i, j + 1)};
|
|
if(test_left_eigenvectors)
|
|
VL[i + j * ldvl_] = {VLij(i, j), VLij(i, j + 1)};
|
|
}
|
|
else if(D[j + j * n].imag() < 0)
|
|
{
|
|
if(test_right_eigenvectors)
|
|
VR[i + j * ldvr_] = {VRij(i, j - 1), -VRij(i, j)};
|
|
if(test_left_eigenvectors)
|
|
VL[i + j * ldvl_] = {VLij(i, j - 1), -VLij(i, j)};
|
|
}
|
|
else
|
|
{
|
|
if(test_right_eigenvectors)
|
|
VR[i + j * ldvr_] = {VRij(i, j), 0};
|
|
if(test_left_eigenvectors)
|
|
VL[i + j * ldvl_] = {VLij(i, j), 0};
|
|
}
|
|
}
|
|
}
|
|
}
|
|
else // is_complex<T> == true
|
|
{
|
|
VR = hVRRes[0];
|
|
VL = hVLRes[0];
|
|
A = hA[0];
|
|
}
|
|
|
|
// [Not implemented:] 1. Check if eigenvalues computed with different parameters match.
|
|
|
|
// 2a. If computing left eigenvectors: check if ||VL_i|| == 1, for 0 <= i < n, and if entry
|
|
// with largest absolute value of VL is real.
|
|
if(test_left_eigenvectors && (jobvl != HIPSOLVER_EIG_MODE_NOVECTOR))
|
|
{
|
|
for(int j = 0; j < n; ++j)
|
|
{
|
|
auto VLij = [ld = ldvl_, V = VL](I i, I j) -> CT { return V[i + j * ld]; };
|
|
double norm = 0.;
|
|
double abs_max = 0.;
|
|
I imax = I(0);
|
|
for(int i = 0; i < n; ++i)
|
|
{
|
|
auto vij = VLij(i, j);
|
|
norm += std::norm<double>({vij.real(), vij.imag()});
|
|
if(std::abs(VLij(i, j)) >= abs_max)
|
|
{
|
|
imax = i;
|
|
abs_max = std::abs(VLij(i, j));
|
|
}
|
|
}
|
|
err = (std::sqrt(norm) - 1.) / normA;
|
|
*max_err = *max_err < err ? err : *max_err;
|
|
|
|
if(std::abs(VLij(imax, j).imag()) > 0)
|
|
{
|
|
*max_err += 1.;
|
|
}
|
|
}
|
|
}
|
|
|
|
// 2b. If computing right eigenvectors: check if ||VR_i|| == 1, for 0 <= i < n, and if entry
|
|
// with largest absolute value of VR is real.
|
|
if(test_right_eigenvectors && (jobvr != HIPSOLVER_EIG_MODE_NOVECTOR))
|
|
{
|
|
for(int j = 0; j < n; ++j)
|
|
{
|
|
auto VRij = [ld = ldvr_, V = VR](I i, I j) -> CT { return V[i + j * ld]; };
|
|
double norm = 0.;
|
|
double abs_max = 0.;
|
|
I imax = I(0);
|
|
for(int i = 0; i < n; ++i)
|
|
{
|
|
auto vij = VRij(i, j);
|
|
norm += std::norm<double>({vij.real(), vij.imag()});
|
|
if(std::abs(VRij(i, j)) >= abs_max)
|
|
{
|
|
imax = i;
|
|
abs_max = std::abs(VRij(i, j));
|
|
}
|
|
}
|
|
err = (std::sqrt(norm) - 1.) / normA;
|
|
*max_err = *max_err < err ? err : *max_err;
|
|
|
|
if(std::abs(VRij(imax, j).imag()) > 0)
|
|
{
|
|
*max_err += 1.;
|
|
}
|
|
}
|
|
}
|
|
|
|
// 3a. Check reconstruction with right eigenvectors (VR): ||A*VR - VR*W||/|A|| <= n * eps
|
|
if(test_right_eigenvectors && (jobvr != HIPSOLVER_EIG_MODE_NOVECTOR))
|
|
{
|
|
alpha = T(1);
|
|
beta = T(0);
|
|
cpu_gemm(HIPSOLVER_OP_N, HIPSOLVER_OP_N, n, n, n, alpha, A, lda, VR, ldvr_, beta, Err, n);
|
|
|
|
alpha = T(-1);
|
|
beta = T(1);
|
|
cpu_gemm(HIPSOLVER_OP_N, HIPSOLVER_OP_N, n, n, n, alpha, VR, ldvr_, D, n, beta, Err, n);
|
|
|
|
err = snorm('F', n, n, Err, n) / normA;
|
|
/* std::cout << "err (VR) = " << err << std::endl; */
|
|
|
|
*max_err = *max_err < err ? err : *max_err;
|
|
}
|
|
|
|
// 3b. Check reconstruction with left eigenvectors (VL): ||A'*VL - VL*W||/||A|| <= n * eps
|
|
if(test_left_eigenvectors && (jobvl != HIPSOLVER_EIG_MODE_NOVECTOR))
|
|
{
|
|
alpha = T(1);
|
|
beta = T(0);
|
|
cpu_gemm(HIPSOLVER_OP_T, HIPSOLVER_OP_N, n, n, n, alpha, A, lda, VL, ldvl_, beta, Err, n);
|
|
|
|
alpha = T(-1);
|
|
beta = T(1);
|
|
cpu_gemm(HIPSOLVER_OP_N, HIPSOLVER_OP_N, n, n, n, alpha, VL, ldvl_, D, n, beta, Err, n);
|
|
|
|
err = snorm('F', n, n, Err, n) / normA;
|
|
/* std::cout << "err (VL) = " << err << std::endl; */
|
|
|
|
*max_err = *max_err < err ? err : *max_err;
|
|
}
|
|
|
|
// TODO
|
|
// Save different errors in different variables instead of accumulating everything in `max_err`.
|
|
}
|
|
|
|
template <testAPI_t API,
|
|
typename T,
|
|
typename W,
|
|
typename I,
|
|
typename SIZE,
|
|
typename Td,
|
|
typename Wd,
|
|
typename INTd,
|
|
typename Th>
|
|
void geev_getPerfData(const hipsolverHandle_t handle,
|
|
const hipsolverDnParams_t params,
|
|
const hipsolverEigMode_t jobvl,
|
|
const hipsolverEigMode_t jobvr,
|
|
const I n,
|
|
Td& dA,
|
|
const I lda,
|
|
Wd& dW,
|
|
Td& dVL,
|
|
const I ldvl,
|
|
Td& dVR,
|
|
const I ldvr,
|
|
Td& dWork,
|
|
const SIZE dlwork,
|
|
Th& hWork,
|
|
const SIZE hlwork,
|
|
INTd& dInfo,
|
|
Th& hA,
|
|
double* gpu_time_used,
|
|
double* cpu_time_used,
|
|
const int hot_calls,
|
|
const bool perf)
|
|
{
|
|
if(!perf)
|
|
{
|
|
// TODO
|
|
}
|
|
|
|
geev_initData<true, false, T>(handle, params, n, dA, lda, hA);
|
|
|
|
// cold calls
|
|
for(int iter = 0; iter < 2; iter++)
|
|
{
|
|
geev_initData<false, true, T>(handle, params, n, dA, lda, hA);
|
|
|
|
CHECK_ROCBLAS_ERROR(hipsolver_geev(API,
|
|
handle,
|
|
params,
|
|
jobvl,
|
|
jobvr,
|
|
n,
|
|
dA.data(),
|
|
lda,
|
|
dW.data(),
|
|
dVL.data(),
|
|
ldvl,
|
|
dVR.data(),
|
|
ldvr,
|
|
dWork.data(),
|
|
dlwork,
|
|
hWork.data(),
|
|
hlwork,
|
|
dInfo.data()));
|
|
}
|
|
|
|
// gpu-lapack performance
|
|
hipStream_t stream;
|
|
CHECK_ROCBLAS_ERROR(hipsolverGetStream(handle, &stream));
|
|
double start;
|
|
|
|
for(int iter = 0; iter < hot_calls; iter++)
|
|
{
|
|
geev_initData<false, true, T>(handle, params, n, dA, lda, hA);
|
|
|
|
start = get_time_us_sync(stream);
|
|
hipsolver_geev(API,
|
|
handle,
|
|
params,
|
|
jobvl,
|
|
jobvr,
|
|
n,
|
|
dA.data(),
|
|
lda,
|
|
dW.data(),
|
|
dVL.data(),
|
|
ldvl,
|
|
dVR.data(),
|
|
ldvr,
|
|
dWork.data(),
|
|
dlwork,
|
|
hWork.data(),
|
|
hlwork,
|
|
dInfo.data());
|
|
*gpu_time_used += get_time_us_sync(stream) - start;
|
|
}
|
|
*gpu_time_used /= hot_calls;
|
|
}
|
|
|
|
template <testAPI_t API,
|
|
bool BATCHED,
|
|
bool STRIDED,
|
|
typename T,
|
|
typename W,
|
|
typename I,
|
|
typename SIZE>
|
|
void testing_geev(Arguments& argus)
|
|
{
|
|
// Initialize extra type used to simplify testing when type `T` is real.
|
|
using CT = std::conditional_t<
|
|
std::is_same_v<T, float>,
|
|
hipsolverComplex,
|
|
std::conditional_t<std::is_same_v<T, double>, hipsolverDoubleComplex, T>>;
|
|
|
|
// get arguments
|
|
hipsolver_local_handle handle;
|
|
hipsolver_local_params params;
|
|
char jobvlC = argus.get<char>("jobvl", 'N');
|
|
char jobvrC = argus.get<char>("jobvr");
|
|
I n = argus.get<int>("n");
|
|
I lda = argus.get<int>("lda", n);
|
|
I ldvl = argus.get<int>("ldvl", n);
|
|
I ldvr = argus.get<int>("ldvr", n);
|
|
|
|
hipsolverEigMode_t jobvl = char2hipsolver_evect(jobvlC);
|
|
hipsolverEigMode_t jobvr = char2hipsolver_evect(jobvrC);
|
|
int bc = argus.batch_count;
|
|
int hot_calls = argus.iters;
|
|
|
|
// check non-supported values
|
|
// N/A
|
|
|
|
// determine sizes
|
|
size_t size_A = size_t(lda) * n;
|
|
size_t size_W = is_complex<W> ? size_t(n) : size_t(2 * n);
|
|
size_t size_VL = jobvlC == 'N' ? size_t(n) * n : size_t(ldvl) * n;
|
|
size_t size_VR = jobvrC == 'N' ? size_t(n) * n : size_t(ldvr) * n;
|
|
size_t size_D = size_t(n) * n;
|
|
size_t size_Err = size_t(n) * n;
|
|
double max_error = 0, gpu_time_used = 0, cpu_time_used = 0;
|
|
|
|
size_t size_ARes = (argus.unit_check || argus.norm_check) ? size_A : 0;
|
|
size_t size_WRes = (argus.unit_check || argus.norm_check) ? size_W : 0;
|
|
size_t size_VLRes = (argus.unit_check || argus.norm_check) ? size_VL : 0;
|
|
size_t size_VRRes = (argus.unit_check || argus.norm_check) ? size_VR : 0;
|
|
|
|
// check invalid sizes
|
|
bool invalid_size = (n < 0 || lda < n || bc < 0);
|
|
bool invalid_size_vl = ldvl < (jobvl == HIPSOLVER_EIG_MODE_NOVECTOR ? 1 : n);
|
|
bool invalid_size_vr = ldvr < (jobvr == HIPSOLVER_EIG_MODE_NOVECTOR ? 1 : n);
|
|
if(invalid_size || invalid_size_vl || invalid_size_vr)
|
|
{
|
|
#if defined(__HIP_PLATFORM_HCC__) || defined(__HIP_PLATFORM_AMD__)
|
|
if(BATCHED)
|
|
{
|
|
// unsupported
|
|
}
|
|
else
|
|
{
|
|
EXPECT_ROCBLAS_STATUS(hipsolver_geev(API,
|
|
handle,
|
|
params,
|
|
jobvl,
|
|
jobvr,
|
|
n,
|
|
(T*)nullptr,
|
|
lda,
|
|
(W*)nullptr,
|
|
(T*)nullptr,
|
|
ldvl,
|
|
(T*)nullptr,
|
|
ldvr,
|
|
(T*)nullptr,
|
|
0,
|
|
(T*)nullptr,
|
|
0,
|
|
(int*)nullptr),
|
|
HIPSOLVER_STATUS_INVALID_VALUE);
|
|
}
|
|
#endif
|
|
|
|
if(argus.timing)
|
|
rocsolver_bench_inform(inform_invalid_size);
|
|
|
|
return;
|
|
}
|
|
|
|
// Memory size query is necessary.
|
|
//
|
|
// Note: current test implementation requires the computation of left and right eigenvectors.
|
|
SIZE size_dW, size_hW;
|
|
CHECK_ROCBLAS_ERROR(
|
|
hipsolver_geev_bufferSize(API,
|
|
handle,
|
|
params,
|
|
test_left_eigenvectors ? HIPSOLVER_EIG_MODE_VECTOR : jobvl,
|
|
test_right_eigenvectors ? HIPSOLVER_EIG_MODE_VECTOR : jobvr,
|
|
n,
|
|
(T*)nullptr,
|
|
lda,
|
|
(W*)nullptr,
|
|
(T*)nullptr,
|
|
std::max(ldvl, n),
|
|
(T*)nullptr,
|
|
std::max(ldvr, n),
|
|
&size_dW,
|
|
&size_hW));
|
|
|
|
if(argus.mem_query)
|
|
{
|
|
rocsolver_bench_inform(inform_mem_query, size_dW);
|
|
return;
|
|
}
|
|
|
|
if(BATCHED)
|
|
{
|
|
// unsupported
|
|
}
|
|
|
|
else
|
|
{
|
|
// memory allocations
|
|
host_strided_batch_vector<T> hA(size_A, 1, size_A, bc);
|
|
host_strided_batch_vector<CT> hCA(size_A, 1, size_A, bc);
|
|
host_strided_batch_vector<T> hARes(size_ARes, 1, size_ARes, bc);
|
|
host_strided_batch_vector<W> hW(size_W, 1, size_W, bc);
|
|
host_strided_batch_vector<W> hWRes(size_WRes, 1, size_WRes, bc);
|
|
host_strided_batch_vector<CT> hVL(size_VL, 1, size_VL, bc);
|
|
host_strided_batch_vector<T> hVLRes(size_VLRes, 1, size_VLRes, bc);
|
|
host_strided_batch_vector<CT> hVR(size_VR, 1, size_VR, bc);
|
|
host_strided_batch_vector<T> hVRRes(size_VRRes, 1, size_VRRes, bc);
|
|
host_strided_batch_vector<int> hInfo(1, 1, 1, bc);
|
|
host_strided_batch_vector<int> hInfoRes(1, 1, 1, bc);
|
|
host_strided_batch_vector<T> hWork(size_hW, 1, size_hW, 1); // size_hW accounts for bc
|
|
host_strided_batch_vector<T> hD(size_D, 1, size_D, bc);
|
|
host_strided_batch_vector<CT> hCD(size_D, 1, size_D, bc);
|
|
host_strided_batch_vector<T> hErr(size_Err, 1, size_Err, bc);
|
|
host_strided_batch_vector<CT> hCErr(size_Err, 1, size_Err, bc);
|
|
device_strided_batch_vector<T> dA(size_A, 1, size_A, bc);
|
|
device_strided_batch_vector<W> dW(size_W, 1, size_W, bc);
|
|
device_strided_batch_vector<T> dVL(size_VL, 1, size_VL, bc);
|
|
device_strided_batch_vector<T> dVR(size_VR, 1, size_VR, bc);
|
|
device_strided_batch_vector<int> dInfo(1, 1, 1, bc);
|
|
device_strided_batch_vector<T> dWork(size_dW, 1, size_dW, 1); // size_dW accounts for bc
|
|
if(size_A)
|
|
CHECK_HIP_ERROR(dA.memcheck());
|
|
CHECK_HIP_ERROR(dInfo.memcheck());
|
|
if(size_W)
|
|
CHECK_HIP_ERROR(dW.memcheck());
|
|
if(size_VL)
|
|
CHECK_HIP_ERROR(dVL.memcheck());
|
|
if(size_VR)
|
|
CHECK_HIP_ERROR(dVR.memcheck());
|
|
if(size_dW)
|
|
CHECK_HIP_ERROR(dWork.memcheck());
|
|
|
|
// check computations
|
|
if(argus.unit_check || argus.norm_check)
|
|
geev_getError<API, T, W>(handle,
|
|
params,
|
|
jobvl,
|
|
jobvr,
|
|
n,
|
|
dA,
|
|
lda,
|
|
dW,
|
|
dVL,
|
|
ldvl,
|
|
dVR,
|
|
ldvr,
|
|
dWork,
|
|
size_dW,
|
|
hWork,
|
|
size_hW,
|
|
dInfo,
|
|
hA,
|
|
hCA,
|
|
hARes,
|
|
hW,
|
|
hWRes,
|
|
hVL,
|
|
hVLRes,
|
|
hVR,
|
|
hVRRes,
|
|
hInfo,
|
|
hInfoRes,
|
|
hD,
|
|
hCD,
|
|
hErr,
|
|
hCErr,
|
|
&max_error);
|
|
|
|
// collect performance data
|
|
if(argus.timing)
|
|
geev_getPerfData<API, T, W>(handle,
|
|
params,
|
|
jobvl,
|
|
jobvr,
|
|
n,
|
|
dA,
|
|
lda,
|
|
dW,
|
|
dVL,
|
|
ldvl,
|
|
dVR,
|
|
ldvr,
|
|
dWork,
|
|
size_dW,
|
|
hWork,
|
|
size_hW,
|
|
dInfo,
|
|
hA,
|
|
&gpu_time_used,
|
|
&cpu_time_used,
|
|
hot_calls,
|
|
argus.perf);
|
|
}
|
|
|
|
// validate results for hipsolver-test
|
|
// using 5 * n * machine_precision as tolerance
|
|
if(argus.unit_check)
|
|
ROCSOLVER_TEST_CHECK(T, max_error, 5 * n);
|
|
|
|
// output results for rocsolver-bench
|
|
if(argus.timing)
|
|
{
|
|
if(!argus.perf)
|
|
{
|
|
std::cerr << "\n============================================\n";
|
|
std::cerr << "Arguments:\n";
|
|
std::cerr << "============================================\n";
|
|
rocsolver_bench_output("jobvl", "jobvr", "n", "lda", "ldvl", "ldvr");
|
|
rocsolver_bench_output(jobvlC, jobvrC, n, lda, ldvl, ldvr);
|
|
|
|
std::cerr << "\n============================================\n";
|
|
std::cerr << "Results:\n";
|
|
std::cerr << "============================================\n";
|
|
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);
|
|
}
|
|
std::cerr << std::endl;
|
|
}
|
|
else
|
|
{
|
|
if(argus.norm_check)
|
|
rocsolver_bench_output(gpu_time_used, max_error);
|
|
else
|
|
rocsolver_bench_output(gpu_time_used);
|
|
}
|
|
}
|
|
|
|
// ensure all arguments were consumed
|
|
argus.validate_consumed();
|
|
}
|