Files
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
Flatten subprojects into a single base monorepo
2026-09-02 16:34:47 -07:00

612 lines
25 KiB
C++

/* **************************************************************************
* Copyright (C) 2022-2025 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.
* *************************************************************************/
#pragma once
#include "common/misc/client_util.hpp"
#include "common/misc/clientcommon.hpp"
#include "common/misc/lapack_host_reference.hpp"
#include "common/misc/norm.hpp"
#include "common/misc/rocsolver.hpp"
#include "common/misc/rocsolver_arguments.hpp"
#include "common/misc/rocsolver_test.hpp"
#include "common/misc/rocsolver_timer.hpp"
template <typename T, typename U>
void bdsvdx_checkBadArgs(const rocblas_handle handle,
const rocblas_fill uplo,
const rocblas_svect svect,
const rocblas_srange srange,
const rocblas_int n,
U dD,
U dE,
const T vl,
const T vu,
const rocblas_int il,
const rocblas_int iu,
rocblas_int* dNsv,
U dS,
U dZ,
const rocblas_int ldz,
rocblas_int* dIfail,
rocblas_int* dInfo)
{
// handle
EXPECT_ROCBLAS_STATUS(rocsolver_bdsvdx(nullptr, uplo, svect, srange, n, dD, dE, vl, vu, il, iu,
dNsv, dS, dZ, ldz, dIfail, dInfo),
rocblas_status_invalid_handle);
// values
EXPECT_ROCBLAS_STATUS(rocsolver_bdsvdx(handle, rocblas_fill_full, svect, srange, n, dD, dE, vl,
vu, il, iu, dNsv, dS, dZ, ldz, dIfail, dInfo),
rocblas_status_invalid_value);
EXPECT_ROCBLAS_STATUS(rocsolver_bdsvdx(handle, uplo, rocblas_svect_all, srange, n, dD, dE, vl,
vu, il, iu, dNsv, dS, dZ, ldz, dIfail, dInfo),
rocblas_status_invalid_value);
EXPECT_ROCBLAS_STATUS(rocsolver_bdsvdx(handle, uplo, svect, rocblas_srange(0), n, dD, dE, vl,
vu, il, iu, dNsv, dS, dZ, ldz, dIfail, dInfo),
rocblas_status_invalid_value);
// pointers
EXPECT_ROCBLAS_STATUS(rocsolver_bdsvdx(handle, uplo, svect, srange, n, (U) nullptr, dE, vl, vu,
il, iu, dNsv, dS, dZ, ldz, dIfail, dInfo),
rocblas_status_invalid_pointer);
EXPECT_ROCBLAS_STATUS(rocsolver_bdsvdx(handle, uplo, svect, srange, n, dD, (U) nullptr, vl, vu,
il, iu, dNsv, dS, dZ, ldz, dIfail, dInfo),
rocblas_status_invalid_pointer);
EXPECT_ROCBLAS_STATUS(rocsolver_bdsvdx(handle, uplo, svect, srange, n, dD, dE, vl, vu, il, iu,
(rocblas_int*)nullptr, dS, dZ, ldz, dIfail, dInfo),
rocblas_status_invalid_pointer);
EXPECT_ROCBLAS_STATUS(rocsolver_bdsvdx(handle, uplo, svect, srange, n, dD, dE, vl, vu, il, iu,
dNsv, (U) nullptr, dZ, ldz, dIfail, dInfo),
rocblas_status_invalid_pointer);
EXPECT_ROCBLAS_STATUS(rocsolver_bdsvdx(handle, uplo, svect, srange, n, dD, dE, vl, vu, il, iu,
dNsv, dS, (U) nullptr, ldz, dIfail, dInfo),
rocblas_status_invalid_pointer);
EXPECT_ROCBLAS_STATUS(rocsolver_bdsvdx(handle, uplo, svect, srange, n, dD, dE, vl, vu, il, iu,
dNsv, dS, dZ, ldz, (rocblas_int*)nullptr, dInfo),
rocblas_status_invalid_pointer);
EXPECT_ROCBLAS_STATUS(rocsolver_bdsvdx(handle, uplo, svect, srange, n, dD, dE, vl, vu, il, iu,
dNsv, dS, dZ, ldz, dIfail, (rocblas_int*)nullptr),
rocblas_status_invalid_pointer);
// quick return with invalid pointers
EXPECT_ROCBLAS_STATUS(rocsolver_bdsvdx(handle, uplo, svect, srange, 0, (U) nullptr, (U) nullptr,
vl, vu, il, iu, dNsv, (U) nullptr, (U) nullptr, ldz,
(rocblas_int*)nullptr, dInfo),
rocblas_status_success);
}
template <typename T>
void testing_bdsvdx_bad_arg()
{
// safe arguments
rocblas_local_handle handle;
rocblas_int n = 2;
rocblas_fill uplo = rocblas_fill_upper;
rocblas_svect svect = rocblas_svect_singular;
rocblas_srange srange = rocblas_srange_all;
rocblas_int ldz = 4;
T vl = 0;
T vu = 0;
rocblas_int il = 0;
rocblas_int iu = 0;
// memory allocations
device_strided_batch_vector<T> dD(1, 1, 1, 1);
device_strided_batch_vector<T> dE(1, 1, 1, 1);
device_strided_batch_vector<T> dS(1, 1, 1, 1);
device_strided_batch_vector<T> dZ(1, 1, 1, 1);
device_strided_batch_vector<rocblas_int> dNsv(1, 1, 1, 1);
device_strided_batch_vector<rocblas_int> dIfail(1, 1, 1, 1);
device_strided_batch_vector<rocblas_int> dInfo(1, 1, 1, 1);
CHECK_HIP_ERROR(dD.memcheck());
CHECK_HIP_ERROR(dE.memcheck());
CHECK_HIP_ERROR(dS.memcheck());
CHECK_HIP_ERROR(dZ.memcheck());
CHECK_HIP_ERROR(dNsv.memcheck());
CHECK_HIP_ERROR(dIfail.memcheck());
CHECK_HIP_ERROR(dInfo.memcheck());
// check bad arguments
bdsvdx_checkBadArgs(handle, uplo, svect, srange, n, dD.data(), dE.data(), vl, vu, il, iu,
dNsv.data(), dS.data(), dZ.data(), ldz, dIfail.data(), dInfo.data());
}
template <bool CPU, bool GPU, typename T, typename Td, typename Th>
void bdsvdx_initData(const rocblas_handle handle, const rocblas_int n, Td& dD, Td& dE, Th& hD, Th& hE)
{
if(CPU)
{
rocblas_init<T>(hD, true);
rocblas_init<T>(hE, true);
// scale matrix and add fixed splits in the matrix to test split handling
// (scaling ensures that all singular values are in [0, 20])
for(rocblas_int i = 0; i < n; i++)
{
hD[0][i] += 10;
hE[0][i] = (hE[0][i] - 5) / 10;
if(i == n / 4 || i == n / 2 || i == n - 1)
hE[0][i] = 0;
if(i == n / 7 || i == n / 5 || i == n / 3)
hD[0][i] *= -1;
}
}
if(GPU)
{
// now copy to the GPU
CHECK_HIP_ERROR(dD.transfer_from(hD));
CHECK_HIP_ERROR(dE.transfer_from(hE));
}
}
template <typename T, typename Td, typename Ud, typename Th, typename Uh>
void bdsvdx_getError(const rocblas_handle handle,
const rocblas_fill uplo,
const rocblas_svect svect,
const rocblas_srange srange,
const rocblas_int n,
Td& dD,
Td& dE,
const T vl,
const T vu,
const rocblas_int il,
const rocblas_int iu,
Ud& dNsv,
Td& dS,
Td& dZ,
const rocblas_int ldz,
Ud& dIfail,
Ud& dInfo,
Th& hD,
Th& hE,
Uh& hNsv,
Uh& hNsvRes,
Th& hS,
Th& hSRes,
Th& hZ,
Th& hZRes,
Uh& hIfailRes,
Uh& hInfo,
Uh& hInfoRes,
double* max_err)
{
std::vector<T> work(14 * n);
std::vector<int> iwork(12 * n);
// input data initialization
bdsvdx_initData<true, true, T>(handle, n, dD, dE, hD, hE);
// execute computations
// GPU lapack
CHECK_ROCBLAS_ERROR(rocsolver_bdsvdx(handle, uplo, svect, srange, n, dD.data(), dE.data(), vl,
vu, il, iu, dNsv.data(), dS.data(), dZ.data(), ldz,
dIfail.data(), dInfo.data()));
CHECK_HIP_ERROR(hNsvRes.transfer_from(dNsv));
CHECK_HIP_ERROR(hSRes.transfer_from(dS));
CHECK_HIP_ERROR(hZRes.transfer_from(dZ));
CHECK_HIP_ERROR(hIfailRes.transfer_from(dIfail));
CHECK_HIP_ERROR(hInfoRes.transfer_from(dInfo));
// CPU lapack
// WORKAROUND: For some test cases, LAPACK's bdsvdx is returning incorrect singular values
// when srange is rocblas_srange_index. In this case, we use rocblas_srange_all to get
// all the singular values and offset and use il as an offset into the result array.
rocblas_int ioffset = 0;
if(srange == rocblas_srange_index)
{
cpu_bdsvdx(uplo, rocblas_svect_none, rocblas_srange_all, n, hD[0], hE[0], vl, vu, il, iu,
hNsv[0], hS[0], hZ[0], ldz, work.data(), iwork.data(), hInfo[0]);
ioffset = il - 1;
hNsv[0][0] = iu - il + 1;
}
else
{
cpu_bdsvdx(uplo, rocblas_svect_none, srange, n, hD[0], hE[0], vl, vu, il, iu, hNsv[0],
hS[0], hZ[0], ldz, work.data(), iwork.data(), hInfo[0]);
}
// check info
EXPECT_EQ(hInfo[0][0], hInfoRes[0][0]);
if(hInfo[0][0] != hInfoRes[0][0])
*max_err = 1;
else
*max_err = 0;
// if finding singular values succeeded, check values
double err;
if(hInfoRes[0][0] == 0)
{
// check number of computed singular values
rocblas_int nn = hNsvRes[0][0];
*max_err += std::abs(nn - hNsv[0][0]);
EXPECT_EQ(hNsv[0][0], hNsvRes[0][0]);
// error is ||hS - hSRes|| / ||hS||
// using frobenius norm
err = norm_error('F', 1, nn, 1, hS[0] + ioffset, hSRes[0]);
*max_err = err > *max_err ? err : *max_err;
// Check the singular vectors if required
// U is stored in hZRes, and V is stored in hZRes+n
if(svect != rocblas_svect_none)
{
// U and V should be orthonormal, if they are then U^T*U and V^T*V should be the identity
if(nn > 0)
{
std::vector<T> UUres(nn * nn, 0.0);
std::vector<T> VVres(nn * nn, 0.0);
std::vector<T> I(nn * nn, 0.0);
for(rocblas_int i = 0; i < nn; i++)
I[i + i * nn] = T(1);
cpu_gemm(rocblas_operation_conjugate_transpose, rocblas_operation_none, nn, nn, n,
T(1), hZRes[0], ldz, hZRes[0], ldz, T(0), UUres.data(), nn);
err = norm_error('F', nn, nn, nn, I.data(), UUres.data());
*max_err = err > *max_err ? err : *max_err;
cpu_gemm(rocblas_operation_conjugate_transpose, rocblas_operation_none, nn, nn, n,
T(1), hZRes[0] + n, ldz, hZRes[0] + n, ldz, T(0), VVres.data(), nn);
err = norm_error('F', nn, nn, nn, I.data(), VVres.data());
*max_err = err > *max_err ? err : *max_err;
}
err = 0;
// form bidiagonal matrix B
std::vector<T> B(n * n);
for(rocblas_int i = 0; i < n; i++)
{
for(rocblas_int j = 0; j < n; j++)
{
if(i == j)
B[i + j * n] = hD[0][i];
else if(i + 1 == j && uplo == rocblas_fill_upper)
B[i + j * n] = hE[0][i];
else if(i == j + 1 && uplo == rocblas_fill_lower)
B[i + j * n] = hE[0][j];
else
B[i + j * n] = 0;
}
}
// check singular vectors implicitly (B*v_k = s_k*u_k)
for(rocblas_int k = 0; k < nn; ++k)
{
cpu_gemv(rocblas_operation_none, n, n, T(1), B.data(), n, hZRes[0] + n + k * ldz, 1,
-hSRes[0][k], hZRes[0] + k * ldz, 1);
}
err = double(snorm('F', n, nn, hZRes[0], ldz)) / double(snorm('F', n, n, B.data(), n));
*max_err = err > *max_err ? err : *max_err;
// check ifail
err = 0;
for(int j = 0; j < nn; j++)
{
EXPECT_EQ(hIfailRes[0][j], 0) << "where j = " << j;
if(hIfailRes[0][j] != 0)
err++;
}
*max_err = err > *max_err ? err : *max_err;
}
}
else
{
if(svect != rocblas_svect_none)
{
// check ifail
err = 0;
for(int j = 0; j < hInfoRes[0][0]; j++)
{
EXPECT_NE(hIfailRes[0][j], 0) << "where j = " << j;
if(hIfailRes[0][j] == 0)
err++;
}
*max_err = err > *max_err ? err : *max_err;
}
}
}
template <typename T, typename Td, typename Ud, typename Th, typename Uh>
void bdsvdx_getPerfData(const rocblas_handle handle,
const rocblas_fill uplo,
const rocblas_svect svect,
const rocblas_srange srange,
const rocblas_int n,
Td& dD,
Td& dE,
const T vl,
const T vu,
const rocblas_int il,
const rocblas_int iu,
Ud& dNsv,
Td& dS,
Td& dZ,
const rocblas_int ldz,
Ud& dIfail,
Ud& dInfo,
Th& hD,
Th& hE,
Uh& hNsv,
Th& hS,
Th& hZ,
Uh& hInfo,
double* gpu_time_used,
double* cpu_time_used,
const rocblas_int hot_calls,
const int profile,
const bool profile_kernels,
const bool perf)
{
if(!perf)
{
std::vector<T> work(14 * n);
std::vector<int> iwork(12 * n);
bdsvdx_initData<true, false, T>(handle, n, dD, dE, hD, hE);
// cpu-lapack performance (only if not in perf mode)
*cpu_time_used = get_time_us_no_sync();
cpu_bdsvdx(uplo, svect, srange, n, hD[0], hE[0], vl, vu, il, iu, hNsv[0], hS[0], hZ[0], ldz,
work.data(), iwork.data(), hInfo[0]);
*cpu_time_used = get_time_us_no_sync() - *cpu_time_used;
}
bdsvdx_initData<true, false, T>(handle, n, dD, dE, hD, hE);
// cold calls
for(int iter = 0; iter < 2; iter++)
{
bdsvdx_initData<false, true, T>(handle, n, dD, dE, hD, hE);
CHECK_ROCBLAS_ERROR(rocsolver_bdsvdx(handle, uplo, svect, srange, n, dD.data(), dE.data(),
vl, vu, il, iu, dNsv.data(), dS.data(), dZ.data(), ldz,
dIfail.data(), dInfo.data()));
}
// 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++)
{
bdsvdx_initData<false, true, T>(handle, n, dD, dE, hD, hE);
timer.start(stream);
rocsolver_bdsvdx(handle, uplo, svect, srange, n, dD.data(), dE.data(), vl, vu, il, iu,
dNsv.data(), dS.data(), dZ.data(), ldz, dIfail.data(), dInfo.data());
timer.end(stream);
}
*gpu_time_used = timer.get_combined();
}
template <typename T>
void testing_bdsvdx(Arguments& argus)
{
// get arguments
rocblas_local_handle handle;
char uploC = argus.get<char>("uplo");
char svectC = argus.get<char>("svect");
char srangeC = argus.get<char>("srange");
rocblas_fill uplo = char2rocblas_fill(uploC);
rocblas_svect svect = char2rocblas_svect(svectC);
rocblas_srange srange = char2rocblas_srange(srangeC);
T vl = T(argus.get<double>("vl", 0));
T vu = T(argus.get<double>("vu", srangeC == 'V' ? 1 : 0));
rocblas_int il = argus.get<rocblas_int>("il", srangeC == 'I' ? 1 : 0);
rocblas_int iu = argus.get<rocblas_int>("iu", srangeC == 'I' ? 1 : 0);
rocblas_int n = argus.get<rocblas_int>("n");
rocblas_int ldz = argus.get<rocblas_int>("ldz", 2 * n);
rocblas_int nsv_max = (srange == rocblas_srange_index ? iu - il + 1 : n);
rocblas_int hot_calls = argus.iters;
// check non-supported values
if((uplo != rocblas_fill_upper && uplo != rocblas_fill_lower)
|| (svect != rocblas_svect_none && svect != rocblas_svect_singular))
{
EXPECT_ROCBLAS_STATUS(rocsolver_bdsvdx(handle, uplo, svect, srange, n, (T*)nullptr,
(T*)nullptr, vl, vu, il, iu, (rocblas_int*)nullptr,
(T*)nullptr, (T*)nullptr, ldz, (rocblas_int*)nullptr,
(rocblas_int*)nullptr),
rocblas_status_invalid_value);
if(argus.timing)
rocsolver_bench_inform(inform_invalid_args);
return;
}
// determine sizes
size_t size_D = n;
size_t size_E = n;
size_t size_S = nsv_max;
size_t size_S_cpu = n;
size_t size_Z = ldz * nsv_max;
size_t size_Ifail = n;
double max_error = 0, gpu_time_used = 0, cpu_time_used = 0;
size_t size_SRes = (argus.unit_check || argus.norm_check) ? size_S : 0;
size_t size_ZRes = (argus.unit_check || argus.norm_check) ? size_Z : 0;
size_t size_IfailRes = (argus.unit_check || argus.norm_check) ? size_Ifail : 0;
// check invalid sizes
bool invalid_size = (n < 0) || (svect == rocblas_svect_none && ldz < 1)
|| (svect != rocblas_svect_none && ldz < 2 * n)
|| (srange == rocblas_srange_value && (vl < 0 || vl >= vu))
|| (srange == rocblas_srange_index && ((iu > n) || (n > 0 && il > iu)))
|| (srange == rocblas_srange_index && (il < 1 || iu < 0));
if(invalid_size)
{
EXPECT_ROCBLAS_STATUS(rocsolver_bdsvdx(handle, uplo, svect, srange, n, (T*)nullptr,
(T*)nullptr, vl, vu, il, iu, (rocblas_int*)nullptr,
(T*)nullptr, (T*)nullptr, ldz, (rocblas_int*)nullptr,
(rocblas_int*)nullptr),
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));
CHECK_ALLOC_QUERY(rocsolver_bdsvdx(handle, uplo, svect, srange, n, (T*)nullptr, (T*)nullptr,
vl, vu, il, iu, (rocblas_int*)nullptr, (T*)nullptr,
(T*)nullptr, ldz, (rocblas_int*)nullptr,
(rocblas_int*)nullptr));
size_t size;
CHECK_ROCBLAS_ERROR(rocblas_stop_device_memory_size_query(handle, &size));
rocsolver_bench_inform(inform_mem_query, size);
return;
}
// memory allocations
// host
host_strided_batch_vector<T> hD(size_D, 1, size_D, 1);
host_strided_batch_vector<T> hE(size_E, 1, size_E, 1);
host_strided_batch_vector<T> hS(size_S_cpu, 1, size_S_cpu, 1); // extra space for cpu_bdsvdx
host_strided_batch_vector<T> hSRes(size_SRes, 1, size_SRes, 1);
host_strided_batch_vector<T> hZ(size_Z, 1, size_Z, 1);
host_strided_batch_vector<T> hZRes(size_ZRes, 1, size_ZRes, 1);
host_strided_batch_vector<rocblas_int> hNsv(1, 1, 1, 1);
host_strided_batch_vector<rocblas_int> hNsvRes(1, 1, 1, 1);
host_strided_batch_vector<rocblas_int> hIfailRes(size_IfailRes, 1, size_IfailRes, 1);
host_strided_batch_vector<rocblas_int> hInfo(1, 1, 1, 1);
host_strided_batch_vector<rocblas_int> hInfoRes(1, 1, 1, 1);
// device
device_strided_batch_vector<T> dD(size_D, 1, size_D, 1);
device_strided_batch_vector<T> dE(size_E, 1, size_E, 1);
device_strided_batch_vector<T> dS(size_S, 1, size_S, 1);
device_strided_batch_vector<T> dZ(size_Z, 1, size_Z, 1);
device_strided_batch_vector<rocblas_int> dNsv(1, 1, 1, 1);
device_strided_batch_vector<rocblas_int> dIfail(size_Ifail, 1, size_Ifail, 1);
device_strided_batch_vector<rocblas_int> dInfo(1, 1, 1, 1);
if(size_D)
CHECK_HIP_ERROR(dD.memcheck());
if(size_E)
CHECK_HIP_ERROR(dE.memcheck());
if(size_S)
CHECK_HIP_ERROR(dS.memcheck());
if(size_Z)
CHECK_HIP_ERROR(dZ.memcheck());
if(size_Ifail)
CHECK_HIP_ERROR(dIfail.memcheck());
CHECK_HIP_ERROR(dNsv.memcheck());
CHECK_HIP_ERROR(dInfo.memcheck());
// check quick return
if(n == 0)
{
EXPECT_ROCBLAS_STATUS(rocsolver_bdsvdx(handle, uplo, svect, srange, n, dD.data(), dE.data(),
vl, vu, il, iu, dNsv.data(), dS.data(), dZ.data(),
ldz, dIfail.data(), dInfo.data()),
rocblas_status_success);
if(argus.timing)
rocsolver_bench_inform(inform_quick_return);
return;
}
// check computations
if(argus.unit_check || argus.norm_check)
bdsvdx_getError<T>(handle, uplo, svect, srange, n, dD, dE, vl, vu, il, iu, dNsv, dS, dZ,
ldz, dIfail, dInfo, hD, hE, hNsv, hNsvRes, hS, hSRes, hZ, hZRes,
hIfailRes, hInfo, hInfoRes, &max_error);
// collect performance data
if(argus.timing && hot_calls > 0)
bdsvdx_getPerfData<T>(handle, uplo, svect, srange, n, dD, dE, vl, vu, il, iu, dNsv, dS, dZ,
ldz, dIfail, dInfo, hD, hE, hNsv, hS, hZ, hInfo, &gpu_time_used,
&cpu_time_used, hot_calls, argus.profile, argus.profile_kernels,
argus.perf);
// validate results for rocsolver-test
// using 2 * n * machine_precision as tolerance
if(argus.unit_check)
ROCSOLVER_TEST_CHECK(T, max_error, 2 * n);
// output results for rocsolver-bench
if(argus.timing)
{
if(!argus.perf)
{
rocsolver_bench_header("Arguments:");
rocsolver_bench_output("uplo", "svect", "srange", "n", "vl", "vu", "il", "iu", "ldz");
rocsolver_bench_output(uploC, svectC, srangeC, n, vl, vu, il, iu, ldz);
rocsolver_bench_header("Results:");
if(argus.norm_check)
{
rocsolver_bench_output("cpu_time_us", "gpu_time_us", "error");
rocsolver_bench_output(cpu_time_used, gpu_time_used, max_error);
}
else
{
rocsolver_bench_output("cpu_time_us", "gpu_time_us");
rocsolver_bench_output(cpu_time_used, gpu_time_used);
}
rocsolver_bench_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();
}
#define EXTERN_TESTING_BDSVDX(...) extern template void testing_bdsvdx<__VA_ARGS__>(Arguments&);
INSTANTIATE(EXTERN_TESTING_BDSVDX, FOREACH_REAL_TYPE, APPLY_STAMP)