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

1397 lines
57 KiB
C++

/* ************************************************************************
* Copyright (C) 2020-2025 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 "clientcommon.hpp"
template <testAPI_t API, typename T, typename TT, typename W, typename U>
void gesvd_checkBadArgs(const hipsolverHandle_t handle,
const char left_svect,
const char right_svect,
const int m,
const int n,
W dA,
const int lda,
const int stA,
TT dS,
const int stS,
T dU,
const int ldu,
const int stU,
T dV,
const int ldv,
const int stV,
T dWork,
const int lwork,
TT dE,
const int stE,
U dinfo,
const int bc)
{
// handle
EXPECT_ROCBLAS_STATUS(hipsolver_gesvd(API,
false,
nullptr,
left_svect,
right_svect,
m,
n,
dA,
lda,
stA,
dS,
stS,
dU,
ldu,
stU,
dV,
ldv,
stV,
dWork,
lwork,
dE,
stE,
dinfo,
bc),
HIPSOLVER_STATUS_NOT_INITIALIZED);
// values
EXPECT_ROCBLAS_STATUS(hipsolver_gesvd(API,
false,
handle,
'\0',
right_svect,
m,
n,
dA,
lda,
stA,
dS,
stS,
dU,
ldu,
stU,
dV,
ldv,
stV,
dWork,
lwork,
dE,
stE,
dinfo,
bc),
HIPSOLVER_STATUS_INVALID_VALUE);
EXPECT_ROCBLAS_STATUS(hipsolver_gesvd(API,
false,
handle,
left_svect,
'\0',
m,
n,
dA,
lda,
stA,
dS,
stS,
dU,
ldu,
stU,
dV,
ldv,
stV,
dWork,
lwork,
dE,
stE,
dinfo,
bc),
HIPSOLVER_STATUS_INVALID_VALUE);
EXPECT_ROCBLAS_STATUS(hipsolver_gesvd(API,
false,
handle,
'O',
'O',
m,
n,
dA,
lda,
stA,
dS,
stS,
dU,
ldu,
stU,
dV,
ldv,
stV,
dWork,
lwork,
dE,
stE,
dinfo,
bc),
HIPSOLVER_STATUS_INVALID_VALUE);
#if defined(__HIP_PLATFORM_HCC__) || defined(__HIP_PLATFORM_AMD__)
// pointers
EXPECT_ROCBLAS_STATUS(hipsolver_gesvd(API,
false,
handle,
left_svect,
right_svect,
m,
n,
(W) nullptr,
lda,
stA,
dS,
stS,
dU,
ldu,
stU,
dV,
ldv,
stV,
dWork,
lwork,
dE,
stE,
dinfo,
bc),
HIPSOLVER_STATUS_INVALID_VALUE);
EXPECT_ROCBLAS_STATUS(hipsolver_gesvd(API,
false,
handle,
left_svect,
right_svect,
m,
n,
dA,
lda,
stA,
(TT) nullptr,
stS,
dU,
ldu,
stU,
dV,
ldv,
stV,
dWork,
lwork,
dE,
stE,
dinfo,
bc),
HIPSOLVER_STATUS_INVALID_VALUE);
EXPECT_ROCBLAS_STATUS(hipsolver_gesvd(API,
false,
handle,
left_svect,
right_svect,
m,
n,
dA,
lda,
stA,
dS,
stS,
(T) nullptr,
ldu,
stU,
dV,
ldv,
stV,
dWork,
lwork,
dE,
stE,
dinfo,
bc),
HIPSOLVER_STATUS_INVALID_VALUE);
EXPECT_ROCBLAS_STATUS(hipsolver_gesvd(API,
false,
handle,
left_svect,
right_svect,
m,
n,
dA,
lda,
stA,
dS,
stS,
dU,
ldu,
stU,
(T) nullptr,
ldv,
stV,
dWork,
lwork,
dE,
stE,
dinfo,
bc),
HIPSOLVER_STATUS_INVALID_VALUE);
EXPECT_ROCBLAS_STATUS(hipsolver_gesvd(API,
false,
handle,
left_svect,
right_svect,
m,
n,
dA,
lda,
stA,
dS,
stS,
dU,
ldu,
stU,
dV,
ldv,
stV,
dWork,
lwork,
dE,
stE,
(U) nullptr,
bc),
HIPSOLVER_STATUS_INVALID_VALUE);
#endif
}
template <testAPI_t API, bool BATCHED, bool STRIDED, typename T>
void testing_gesvd_bad_arg()
{
using S = decltype(std::real(T{}));
// safe arguments
hipsolver_local_handle handle;
char left_svect = 'A';
char right_svect = 'A';
int m = 2;
int n = 2;
int lda = 2;
int ldu = 2;
int ldv = 2;
int stA = 2;
int stS = 2;
int stU = 2;
int stV = 2;
int stE = 2;
int bc = 1;
if(BATCHED)
{
// // memory allocations
// device_batch_vector<T> dA(1, 1, 1);
// device_strided_batch_vector<S> dS(1, 1, 1, 1);
// device_strided_batch_vector<T> dU(1, 1, 1, 1);
// device_strided_batch_vector<T> dV(1, 1, 1, 1);
// device_strided_batch_vector<S> dE(1, 1, 1, 1);
// device_strided_batch_vector<int> dinfo(1, 1, 1, 1);
// CHECK_HIP_ERROR(dA.memcheck());
// CHECK_HIP_ERROR(dS.memcheck());
// CHECK_HIP_ERROR(dU.memcheck());
// CHECK_HIP_ERROR(dV.memcheck());
// CHECK_HIP_ERROR(dE.memcheck());
// CHECK_HIP_ERROR(dinfo.memcheck());
// int size_W;
// hipsolver_gesvd_bufferSize(API, handle, left_svect, right_svect, m, n, dA.data(), lda, &size_W);
// size_t bytes_W = std::getenv("HIPSOLVER_BUFFERSIZE_RETURN_BYTES") != nullptr ? size_W : sizeof(T) * size_W;
// device_strided_batch_vector<T> dWork(bytes_W, 1, bytes_W, 1);
// if(size_W)
// CHECK_HIP_ERROR(dWork.memcheck());
// // check bad arguments
// gesvd_checkBadArgs<API>(handle, left_svect, right_svect, m, n, dA.data(), lda, stA,
// dS.data(), stS, dU.data(), ldu, stU, dV.data(), ldv, stV,
// dWork.data(), size_W, dE.data(), stE, dinfo.data(), bc);
}
else
{
// memory allocations
device_strided_batch_vector<T> dA(1, 1, 1, 1);
device_strided_batch_vector<S> dS(1, 1, 1, 1);
device_strided_batch_vector<T> dU(1, 1, 1, 1);
device_strided_batch_vector<T> dV(1, 1, 1, 1);
device_strided_batch_vector<S> dE(1, 1, 1, 1);
device_strided_batch_vector<int> dinfo(1, 1, 1, 1);
CHECK_HIP_ERROR(dA.memcheck());
CHECK_HIP_ERROR(dS.memcheck());
CHECK_HIP_ERROR(dU.memcheck());
CHECK_HIP_ERROR(dV.memcheck());
CHECK_HIP_ERROR(dE.memcheck());
CHECK_HIP_ERROR(dinfo.memcheck());
int size_W;
hipsolver_gesvd_bufferSize(
API, handle, left_svect, right_svect, m, n, dA.data(), lda, &size_W);
size_t bytes_W = std::getenv("HIPSOLVER_BUFFERSIZE_RETURN_BYTES") != nullptr
? size_W
: sizeof(T) * size_W;
device_strided_batch_vector<T> dWork(bytes_W, 1, bytes_W, 1);
if(size_W)
CHECK_HIP_ERROR(dWork.memcheck());
// check bad arguments
gesvd_checkBadArgs<API>(handle,
left_svect,
right_svect,
m,
n,
dA.data(),
lda,
stA,
dS.data(),
stS,
dU.data(),
ldu,
stU,
dV.data(),
ldv,
stV,
dWork.data(),
size_W,
dE.data(),
stE,
dinfo.data(),
bc);
}
}
template <bool CPU, bool GPU, typename T, typename Td, typename Th>
void gesvd_initData(const hipsolverHandle_t handle,
const char left_svect,
const char right_svect,
const int m,
const int n,
Td& dA,
const int lda,
const int bc,
Th& hA,
std::vector<T>& A,
bool test = true)
{
if(CPU)
{
rocblas_init<T>(hA, true);
for(int b = 0; b < bc; ++b)
{
// scale A to avoid singularities
for(int i = 0; i < m; i++)
{
for(int j = 0; j < n; j++)
{
if(i == j)
hA[b][i + j * lda] += 400;
else
hA[b][i + j * lda] -= 4;
}
}
// make copy of original data to test vectors if required
if(test && (left_svect != 'N' || right_svect != 'N'))
{
for(int i = 0; i < m; i++)
{
for(int j = 0; j < n; j++)
A[b * lda * n + i + j * lda] = hA[b][i + j * lda];
}
}
}
}
if(GPU)
{
// now copy to the GPU
CHECK_HIP_ERROR(dA.transfer_from(hA));
}
}
template <testAPI_t API,
bool NRWK,
typename T,
typename Wd,
typename Td,
typename Ud,
typename Id,
typename Wh,
typename Th,
typename Uh,
typename Ih>
void gesvd_getError(const hipsolverHandle_t handle,
const char left_svect,
const char right_svect,
const int m,
const int n,
Wd& dA,
const int lda,
const int stA,
Td& dS,
const int stS,
Ud& dU,
const int ldu,
const int stU,
Ud& dV,
const int ldv,
const int stV,
Ud& dWork,
const int lwork,
Td& dE,
const int stE,
Id& dinfo,
const int bc,
const char left_svectT,
const char right_svectT,
const int mT,
const int nT,
Ud& dUT,
const int lduT,
const int stUT,
Ud& dVT,
const int ldvT,
const int stVT,
Wh& hA,
Th& hS,
Th& hSres,
Uh& hU,
Uh& Ures,
const int ldures,
Uh& hV,
Uh& Vres,
const int ldvres,
Th& hE,
Th& hEres,
Ih& hinfo,
Ih& hinfoRes,
double* max_err,
double* max_errv)
{
int size_W = 5 * max(m, n);
std::vector<T> hWork(size_W);
std::vector<T> A(lda * n * bc);
// input data initialization
gesvd_initData<true, true, T>(handle, left_svect, right_svect, m, n, dA, lda, bc, hA, A);
// execute computations:
// complementary execution to compute all singular vectors if needed (always in-place to ensure
// we don't combine results computed by gemm_batched with results computed by gemm_strided_batched)
CHECK_ROCBLAS_ERROR(hipsolver_gesvd(API,
NRWK,
handle,
left_svectT,
right_svectT,
mT,
nT,
dA.data(),
lda,
stA,
dS.data(),
stS,
dUT.data(),
lduT,
stUT,
dVT.data(),
ldvT,
stVT,
dWork.data(),
lwork,
dE.data(),
stE,
dinfo.data(),
bc));
if(left_svect == 'N' && right_svect != 'N')
CHECK_HIP_ERROR(Ures.transfer_from(dUT));
if(right_svect == 'N' && left_svect != 'N')
CHECK_HIP_ERROR(Vres.transfer_from(dVT));
gesvd_initData<false, true, T>(handle, left_svect, right_svect, m, n, dA, lda, bc, hA, A);
// CPU lapack
for(int b = 0; b < bc; ++b)
cpu_gesvd(left_svect,
right_svect,
m,
n,
hA[b],
lda,
hS[b],
hU[b],
ldu,
hV[b],
ldv,
hWork.data(),
size_W,
hE[b],
hinfo[b]);
// GPU lapack
CHECK_ROCBLAS_ERROR(hipsolver_gesvd(API,
NRWK,
handle,
left_svect,
right_svect,
m,
n,
dA.data(),
lda,
stA,
dS.data(),
stS,
dU.data(),
ldu,
stU,
dV.data(),
ldv,
stV,
dWork.data(),
lwork,
dE.data(),
stE,
dinfo.data(),
bc));
CHECK_HIP_ERROR(hSres.transfer_from(dS));
CHECK_HIP_ERROR(hEres.transfer_from(dE));
CHECK_HIP_ERROR(hinfoRes.transfer_from(dinfo));
if(left_svect == 'S' || left_svect == 'A')
CHECK_HIP_ERROR(Ures.transfer_from(dU));
if(right_svect == 'S' || right_svect == 'A')
CHECK_HIP_ERROR(Vres.transfer_from(dV));
if(left_svect == 'O')
{
CHECK_HIP_ERROR(hA.transfer_from(dA));
for(int b = 0; b < bc; ++b)
{
for(int i = 0; i < m; i++)
{
for(int j = 0; j < min(m, n); j++)
Ures[b][i + j * ldures] = hA[b][i + j * lda];
}
}
}
if(right_svect == 'O')
{
CHECK_HIP_ERROR(hA.transfer_from(dA));
for(int b = 0; b < bc; ++b)
{
for(int i = 0; i < min(m, n); i++)
{
for(int j = 0; j < n; j++)
Vres[b][i + j * ldvres] = hA[b][i + j * lda];
}
}
}
// Check info for non-convergence
*max_err = 0;
for(int b = 0; b < bc; ++b)
{
EXPECT_EQ(hinfo[b][0], hinfoRes[b][0]) << "where b = " << b;
if(hinfo[b][0] != hinfoRes[b][0])
*max_err += 1;
}
// (We expect the used input matrices to always converge. Testing
// implicitly the equivalent non-converged matrix is very complicated and it boils
// down to essentially run the algorithm again and until convergence is achieved).
double err;
*max_errv = 0;
for(int b = 0; b < bc; ++b)
{
// error is ||hS - hSres||
err = norm_error('F', 1, min(m, n), 1, hS[b], hSres[b]);
*max_err = err > *max_err ? err : *max_err;
// Check the singular vectors if required
if(hinfo[b][0] == 0 && (left_svect != 'N' || right_svect != 'N'))
{
err = 0;
// check singular vectors implicitly (A*v_k = s_k*u_k)
for(int k = 0; k < min(m, n); ++k)
{
for(int i = 0; i < m; ++i)
{
T tmp = 0;
for(int j = 0; j < n; ++j)
tmp += A[b * lda * n + i + j * lda] * std::conj(Vres[b][k + j * ldvres]);
tmp -= hSres[b][k] * Ures[b][i + k * ldures];
err += std::abs(tmp) * std::abs(tmp);
}
}
err = std::sqrt(err) / double(snorm('F', m, n, A.data() + b * lda * n, lda));
*max_errv = err > *max_errv ? err : *max_errv;
}
}
}
template <testAPI_t API,
bool NRWK,
typename T,
typename Wd,
typename Td,
typename Ud,
typename Id,
typename Wh,
typename Th,
typename Uh,
typename Ih>
void gesvd_getPerfData(const hipsolverHandle_t handle,
const char left_svect,
const char right_svect,
const int m,
const int n,
Wd& dA,
const int lda,
const int stA,
Td& dS,
const int stS,
Ud& dU,
const int ldu,
const int stU,
Ud& dV,
const int ldv,
const int stV,
Ud& dWork,
const int lwork,
Td& dE,
const int stE,
Id& dinfo,
const int bc,
Wh& hA,
Th& hS,
Uh& hU,
Uh& hV,
Th& hE,
Ih& hinfo,
double* gpu_time_used,
double* cpu_time_used,
const int hot_calls,
const bool perf)
{
int size_W = 5 * max(m, n);
std::vector<T> hWork(size_W);
std::vector<T> A;
if(!perf)
{
gesvd_initData<true, false, T>(
handle, left_svect, right_svect, m, n, dA, lda, bc, hA, A, 0);
// cpu-lapack performance (only if not in perf mode)
*cpu_time_used = get_time_us_no_sync();
for(int b = 0; b < bc; ++b)
cpu_gesvd(left_svect,
right_svect,
m,
n,
hA[b],
lda,
hS[b],
hU[b],
ldu,
hV[b],
ldv,
hWork.data(),
size_W,
hE[b],
hinfo[b]);
*cpu_time_used = get_time_us_no_sync() - *cpu_time_used;
}
gesvd_initData<true, false, T>(handle, left_svect, right_svect, m, n, dA, lda, bc, hA, A, 0);
// cold calls
for(int iter = 0; iter < 2; iter++)
{
gesvd_initData<false, true, T>(
handle, left_svect, right_svect, m, n, dA, lda, bc, hA, A, 0);
CHECK_ROCBLAS_ERROR(hipsolver_gesvd(API,
NRWK,
handle,
left_svect,
right_svect,
m,
n,
dA.data(),
lda,
stA,
dS.data(),
stS,
dU.data(),
ldu,
stU,
dV.data(),
ldv,
stV,
dWork.data(),
lwork,
dE.data(),
stE,
dinfo.data(),
bc));
}
// gpu-lapack performance
hipStream_t stream;
CHECK_ROCBLAS_ERROR(hipsolverGetStream(handle, &stream));
double start;
for(int iter = 0; iter < hot_calls; iter++)
{
gesvd_initData<false, true, T>(
handle, left_svect, right_svect, m, n, dA, lda, bc, hA, A, 0);
start = get_time_us_sync(stream);
hipsolver_gesvd(API,
NRWK,
handle,
left_svect,
right_svect,
m,
n,
dA.data(),
lda,
stA,
dS.data(),
stS,
dU.data(),
ldu,
stU,
dV.data(),
ldv,
stV,
dWork.data(),
lwork,
dE.data(),
stE,
dinfo.data(),
bc);
*gpu_time_used += get_time_us_sync(stream) - start;
}
*gpu_time_used /= hot_calls;
}
template <testAPI_t API, bool BATCHED, bool STRIDED, bool NRWK, typename T>
void testing_gesvd(Arguments& argus)
{
using S = decltype(std::real(T{}));
// get arguments
hipsolver_local_handle handle;
char leftv = argus.get<char>("jobu");
char rightv = argus.get<char>("jobv");
int m = argus.get<int>("m");
int n = argus.get<int>("n", m);
int lda = argus.get<int>("lda", m);
int ldu = argus.get<int>("ldu", m);
int ldv = argus.get<int>("ldv", (rightv == 'A' ? n : min(m, n)));
int stA = argus.get<int>("strideA", lda * n);
int stS = argus.get<int>("strideS", min(m, n));
int stU = argus.get<int>("strideU", ldu * m);
int stV = argus.get<int>("strideV", ldv * n);
int stE = argus.get<int>("strideE", min(m, n) - 1);
int bc = argus.batch_count;
int hot_calls = argus.iters;
// check non-supported values
if(rightv == 'O' && leftv == 'O')
{
if(BATCHED)
{
// EXPECT_ROCBLAS_STATUS(hipsolver_gesvd(API,
// NRWK,
// handle,
// leftv,
// rightv,
// m,
// n,
// (T* const*)nullptr,
// lda,
// stA,
// (S*)nullptr,
// stS,
// (T*)nullptr,
// ldu,
// stU,
// (T*)nullptr,
// ldv,
// stV,
// (T*)nullptr,
// 0,
// (S*)nullptr,
// stE,
// (int*)nullptr,
// bc),
// HIPSOLVER_STATUS_INVALID_VALUE);
}
else
{
EXPECT_ROCBLAS_STATUS(hipsolver_gesvd(API,
NRWK,
handle,
leftv,
rightv,
m,
n,
(T*)nullptr,
lda,
stA,
(S*)nullptr,
stS,
(T*)nullptr,
ldu,
stU,
(T*)nullptr,
ldv,
stV,
(T*)nullptr,
0,
(S*)nullptr,
stE,
(int*)nullptr,
bc),
HIPSOLVER_STATUS_INVALID_VALUE);
}
if(argus.timing)
rocsolver_bench_inform(inform_invalid_args);
return;
}
/** TESTING OF SINGULAR VECTORS IS DONE IMPLICITLY, NOT EXPLICITLY COMPARING
WITH LAPACK. SO, WE ALWAYS NEED TO COMPUTE THE SAME NUMBER OF ELEMENTS OF
THE RIGHT AND LEFT VECTORS. WHILE DOING THIS, IF MORE VECTORS THAN THE
SPECIFIED IN THE MAIN CALL NEED TO BE COMPUTED, WE DO SO WITH AN EXTRA CALL **/
signed char leftvT = 'N';
signed char rightvT = 'N';
int ldvT = 1;
int lduT = 1;
int mT = 0;
int nT = 0;
bool svects = (leftv != 'N' || rightv != 'N');
if(svects)
{
if(leftv == 'N')
{
leftvT = 'A';
lduT = m;
mT = m;
nT = n;
// if((n > m && fa == rocblas_outofplace) || (n > m && rightv == 'O'))
// rightvT = 'O';
}
if(rightv == 'N')
{
rightvT = 'A';
ldvT = n;
mT = m;
nT = n;
// if((m >= n && fa == rocblas_outofplace) || (m >= n && leftv == 'O'))
// leftvT = 'O';
}
}
// determine sizes
int ldures = 1;
int ldvres = 1;
size_t size_Sres = 0;
size_t size_Eres = 0;
size_t size_Ures = 0;
size_t size_Vres = 0;
size_t size_UT = 0;
size_t size_VT = 0;
size_t size_A = size_t(lda) * n;
size_t size_S = size_t(min(m, n));
size_t size_E = size_t(min(m, n) - 1);
size_t size_V = size_t(ldv) * n;
size_t size_U = size_t(ldu) * m;
if(argus.unit_check || argus.norm_check)
{
size_VT = size_t(ldvT) * nT;
size_UT = size_t(lduT) * mT;
size_Sres = size_S;
size_Eres = size_E;
if(svects)
{
if(leftv == 'N')
{
size_Ures = size_UT;
ldures = lduT;
}
else if(leftv == 'S' || leftv == 'A')
{
size_Ures = size_U;
ldures = ldu;
}
else
{
size_Ures = m * m;
ldures = m;
}
if(rightv == 'N')
{
size_Vres = size_VT;
ldvres = ldvT;
}
else if(rightv == 'S' || rightv == 'A')
{
size_Vres = size_V;
ldvres = ldv;
}
else
{
size_Vres = n * n;
ldvres = n;
}
}
}
int stUT = size_UT;
int stVT = size_VT;
int stUres = size_Ures;
int stVres = size_Vres;
double max_error = 0, gpu_time_used = 0, cpu_time_used = 0, max_errorv = 0;
// check invalid sizes
bool invalid_size = (n < 0 || m < 0 || lda < m || ldu < 1 || ldv < 1 || bc < 0)
|| ((leftv == 'A' || leftv == 'S') && ldu < m)
|| ((rightv == 'A' && ldv < n) || (rightv == 'S' && ldv < min(m, n)));
if(invalid_size)
{
if(BATCHED)
{
// EXPECT_ROCBLAS_STATUS(hipsolver_gesvd(API,
// NRWK,
// handle,
// leftv,
// rightv,
// m,
// n,
// (T* const*)nullptr,
// lda,
// stA,
// (S*)nullptr,
// stS,
// (T*)nullptr,
// ldu,
// stU,
// (T*)nullptr,
// ldv,
// stV,
// (T*)nullptr,
// 0,
// (S*)nullptr,
// stE,
// (int*)nullptr,
// bc),
// HIPSOLVER_STATUS_INVALID_VALUE);
}
else
{
EXPECT_ROCBLAS_STATUS(hipsolver_gesvd(API,
NRWK,
handle,
leftv,
rightv,
m,
n,
(T*)nullptr,
lda,
stA,
(S*)nullptr,
stS,
(T*)nullptr,
ldu,
stU,
(T*)nullptr,
ldv,
stV,
(T*)nullptr,
0,
(S*)nullptr,
stE,
(int*)nullptr,
bc),
HIPSOLVER_STATUS_INVALID_VALUE);
}
if(argus.timing)
rocsolver_bench_inform(inform_invalid_size);
return;
}
// memory size query is necessary
int size_W, w1, w2;
hipsolver_gesvd_bufferSize(API, handle, leftv, rightv, m, n, (T*)nullptr, lda, &w1);
hipsolver_gesvd_bufferSize(API, handle, leftvT, rightvT, mT, nT, (T*)nullptr, lda, &w2);
size_W = max(w1, w2);
size_t bytes_W
= std::getenv("HIPSOLVER_BUFFERSIZE_RETURN_BYTES") != nullptr ? size_W : sizeof(T) * size_W;
if(argus.mem_query)
{
rocsolver_bench_inform(inform_mem_query, bytes_W);
return;
}
// memory allocations (all cases)
// host
host_strided_batch_vector<S> hE(5 * max(m, n), 1, 5 * max(m, n), bc);
host_strided_batch_vector<S> hS(size_S, 1, stS, bc);
host_strided_batch_vector<T> hV(size_V, 1, stV, bc);
host_strided_batch_vector<T> hU(size_U, 1, stU, 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<S> hSres(size_Sres, 1, stS, bc);
host_strided_batch_vector<S> hEres(size_Eres, 1, stE, bc);
host_strided_batch_vector<T> Vres(size_Vres, 1, stVres, bc);
host_strided_batch_vector<T> Ures(size_Ures, 1, stUres, bc);
// device
device_strided_batch_vector<S> dE(size_E, 1, stE, bc);
device_strided_batch_vector<S> dS(size_S, 1, stS, bc);
device_strided_batch_vector<T> dV(size_V, 1, stV, bc);
device_strided_batch_vector<T> dU(size_U, 1, stU, bc);
device_strided_batch_vector<int> dinfo(1, 1, 1, bc);
device_strided_batch_vector<T> dVT(size_VT, 1, stVT, bc);
device_strided_batch_vector<T> dUT(size_UT, 1, stUT, bc);
device_strided_batch_vector<T> dWork(bytes_W, 1, bytes_W, 1); // bytes_W accounts for bc
if(size_VT)
CHECK_HIP_ERROR(dVT.memcheck());
if(size_UT)
CHECK_HIP_ERROR(dUT.memcheck());
if(size_E)
CHECK_HIP_ERROR(dE.memcheck());
if(size_S)
CHECK_HIP_ERROR(dS.memcheck());
if(size_V)
CHECK_HIP_ERROR(dV.memcheck());
if(size_U)
CHECK_HIP_ERROR(dU.memcheck());
CHECK_HIP_ERROR(dinfo.memcheck());
if(size_W)
CHECK_HIP_ERROR(dWork.memcheck());
if(BATCHED)
{
// // memory allocations
// host_batch_vector<T> hA(size_A, 1, bc);
// device_batch_vector<T> dA(size_A, 1, bc);
// if(size_A)
// CHECK_HIP_ERROR(dA.memcheck());
// // check computations
// if(argus.unit_check || argus.norm_check)
// {
// gesvd_getError<API, NRWK, T>(handle,
// leftv,
// rightv,
// m,
// n,
// dA,
// lda,
// stA,
// dS,
// stS,
// dU,
// ldu,
// stU,
// dV,
// ldv,
// stV,
// dWork,
// size_W,
// dE,
// stE,
// dinfo,
// bc,
// leftvT,
// rightvT,
// mT,
// nT,
// dUT,
// lduT,
// stUT,
// dVT,
// ldvT,
// stVT,
// hA,
// hS,
// hSres,
// hU,
// Ures,
// ldures,
// hV,
// Vres,
// ldvres,
// hE,
// hEres,
// hinfo,
// hinfoRes,
// &max_error,
// &max_errorv);
// }
// // collect performance data
// if(argus.timing)
// {
// gesvd_getPerfData<API, NRWK, T>(handle,
// leftv,
// rightv,
// m,
// n,
// dA,
// lda,
// stA,
// dS,
// stS,
// dU,
// ldu,
// stU,
// dV,
// ldv,
// stV,
// dWork,
// size_W,
// dE,
// stE,
// dinfo,
// bc,
// hA,
// hS,
// hU,
// hV,
// hE,
// hinfo,
// &gpu_time_used,
// &cpu_time_used,
// hot_calls,
// argus.perf);
// }
}
else
{
// memory allocations
host_strided_batch_vector<T> hA(size_A, 1, stA, bc);
device_strided_batch_vector<T> dA(size_A, 1, stA, bc);
if(size_A)
CHECK_HIP_ERROR(dA.memcheck());
// check computations
if(argus.unit_check || argus.norm_check)
{
gesvd_getError<API, NRWK, T>(handle,
leftv,
rightv,
m,
n,
dA,
lda,
stA,
dS,
stS,
dU,
ldu,
stU,
dV,
ldv,
stV,
dWork,
size_W,
dE,
stE,
dinfo,
bc,
leftvT,
rightvT,
mT,
nT,
dUT,
lduT,
stUT,
dVT,
ldvT,
stVT,
hA,
hS,
hSres,
hU,
Ures,
ldures,
hV,
Vres,
ldvres,
hE,
hEres,
hinfo,
hinfoRes,
&max_error,
&max_errorv);
}
// collect performance data
if(argus.timing)
{
gesvd_getPerfData<API, NRWK, T>(handle,
leftv,
rightv,
m,
n,
dA,
lda,
stA,
dS,
stS,
dU,
ldu,
stU,
dV,
ldv,
stV,
dWork,
size_W,
dE,
stE,
dinfo,
bc,
hA,
hS,
hU,
hV,
hE,
hinfo,
&gpu_time_used,
&cpu_time_used,
hot_calls,
argus.perf);
}
}
// validate results for rocsolver-test
// using 2 * min(m, n) * machine_precision as tolerance
if(argus.unit_check)
{
ROCSOLVER_TEST_CHECK(T, max_error, 2 * min(m, n));
if(svects)
ROCSOLVER_TEST_CHECK(T, max_errorv, 2 * min(m, n));
}
// output results for rocsolver-bench
if(argus.timing)
{
if(svects)
max_error = (max_error >= max_errorv) ? max_error : max_errorv;
if(!argus.perf)
{
std::cerr << "\n============================================\n";
std::cerr << "Arguments:\n";
std::cerr << "============================================\n";
if(BATCHED)
{
rocsolver_bench_output("jobu",
"jobv",
"m",
"n",
"lda",
"strideS",
"ldu",
"strideU",
"ldv",
"strideV",
"strideE",
"batch_c");
rocsolver_bench_output(leftv, rightv, m, n, lda, stS, ldu, stU, ldv, stV, stE, bc);
}
else if(STRIDED)
{
rocsolver_bench_output("jobu",
"jobv",
"m",
"n",
"lda",
"strideA",
"strideS",
"ldu",
"strideU",
"ldv",
"strideV",
"strideE",
"batch_c");
rocsolver_bench_output(
leftv, rightv, m, n, lda, stA, stS, ldu, stU, ldv, stV, stE, bc);
}
else
{
rocsolver_bench_output("jobu", "jobv", "m", "n", "lda", "ldu", "ldv");
rocsolver_bench_output(leftv, rightv, m, n, lda, ldu, ldv);
}
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();
}