Files
TheRock/rocm-libraries/projects/hipblas/clients/include/blas2/testing_trsv_batched.hpp
T
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

304 lines
11 KiB
C++

/* ************************************************************************
* Copyright (C) 2016-2024 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
* copies 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
* IMPLIED, 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 CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*
* ************************************************************************ */
#include <fstream>
#include <iostream>
#include <stdlib.h>
#include <vector>
#include "testing_common.hpp"
/* ============================================================================================ */
using hipblasTrsvBatchedModel
= ArgumentModel<e_a_type, e_uplo, e_transA, e_diag, e_N, e_lda, e_incx, e_batch_count>;
inline void testname_trsv_batched(const Arguments& arg, std::string& name)
{
hipblasTrsvBatchedModel{}.test_name(arg, name);
}
template <typename T>
void testing_trsv_batched_bad_arg(const Arguments& arg)
{
bool FORTRAN = arg.api == hipblas_client_api::FORTRAN;
auto hipblasTrsvBatchedFn
= FORTRAN ? hipblasTrsvBatched<T, true> : hipblasTrsvBatched<T, false>;
auto hipblasTrsvBatchedFn_64
= arg.api == FORTRAN_64 ? hipblasTrsvBatched_64<T, true> : hipblasTrsvBatched_64<T, false>;
for(auto pointer_mode : {HIPBLAS_POINTER_MODE_HOST, HIPBLAS_POINTER_MODE_DEVICE})
{
hipblasLocalHandle handle(arg);
CHECK_HIPBLAS_ERROR(hipblasSetPointerMode(handle, pointer_mode));
hipblasOperation_t transA = HIPBLAS_OP_N;
hipblasFillMode_t uplo = HIPBLAS_FILL_MODE_UPPER;
hipblasDiagType_t diag = HIPBLAS_DIAG_NON_UNIT;
int64_t N = 100;
int64_t lda = 100;
int64_t incx = 1;
int64_t batch_count = 2;
// Allocate device memory
device_batch_matrix<T> dA(N, N, lda, batch_count);
device_batch_vector<T> dx(N, incx, batch_count);
DAPI_EXPECT(HIPBLAS_STATUS_NOT_INITIALIZED,
hipblasTrsvBatchedFn,
(nullptr,
uplo,
transA,
diag,
N,
dA.ptr_on_device(),
lda,
dx.ptr_on_device(),
incx,
batch_count));
DAPI_EXPECT(HIPBLAS_STATUS_INVALID_VALUE,
hipblasTrsvBatchedFn,
(handle,
HIPBLAS_FILL_MODE_FULL,
transA,
diag,
N,
dA.ptr_on_device(),
lda,
dx.ptr_on_device(),
incx,
batch_count));
DAPI_EXPECT(HIPBLAS_STATUS_INVALID_ENUM,
hipblasTrsvBatchedFn,
(handle,
(hipblasFillMode_t)HIPBLAS_OP_N,
transA,
diag,
N,
dA.ptr_on_device(),
lda,
dx.ptr_on_device(),
incx,
batch_count));
DAPI_EXPECT(HIPBLAS_STATUS_INVALID_ENUM,
hipblasTrsvBatchedFn,
(handle,
uplo,
(hipblasOperation_t)HIPBLAS_FILL_MODE_FULL,
diag,
N,
dA.ptr_on_device(),
lda,
dx.ptr_on_device(),
incx,
batch_count));
DAPI_EXPECT(HIPBLAS_STATUS_INVALID_ENUM,
hipblasTrsvBatchedFn,
(handle,
uplo,
transA,
(hipblasDiagType_t)HIPBLAS_FILL_MODE_FULL,
N,
dA.ptr_on_device(),
lda,
dx.ptr_on_device(),
incx,
batch_count));
DAPI_EXPECT(
HIPBLAS_STATUS_INVALID_VALUE,
hipblasTrsvBatchedFn,
(handle, uplo, transA, diag, N, nullptr, lda, dx.ptr_on_device(), incx, batch_count));
DAPI_EXPECT(
HIPBLAS_STATUS_INVALID_VALUE,
hipblasTrsvBatchedFn,
(handle, uplo, transA, diag, N, dA.ptr_on_device(), lda, nullptr, incx, batch_count));
// With N == 0, can have all nullptrs
DAPI_CHECK(hipblasTrsvBatchedFn,
(handle, uplo, transA, diag, 0, nullptr, lda, nullptr, incx, batch_count));
DAPI_CHECK(hipblasTrsvBatchedFn,
(handle, uplo, transA, diag, N, nullptr, lda, nullptr, incx, 0));
}
}
template <typename T>
void testing_trsv_batched(const Arguments& arg)
{
bool FORTRAN = arg.api == hipblas_client_api::FORTRAN;
auto hipblasTrsvBatchedFn
= FORTRAN ? hipblasTrsvBatched<T, true> : hipblasTrsvBatched<T, false>;
auto hipblasTrsvBatchedFn_64
= arg.api == FORTRAN_64 ? hipblasTrsvBatched_64<T, true> : hipblasTrsvBatched_64<T, false>;
hipblasFillMode_t uplo = char2hipblas_fill(arg.uplo);
hipblasDiagType_t diag = char2hipblas_diagonal(arg.diag);
hipblasOperation_t transA = char2hipblas_operation(arg.transA);
int64_t N = arg.N;
int64_t incx = arg.incx;
int64_t lda = arg.lda;
int64_t batch_count = arg.batch_count;
size_t abs_incx = incx < 0 ? -incx : incx;
hipblasLocalHandle handle(arg);
// argument sanity check, quick return if input parameters are invalid before allocating invalid
// memory
bool invalid_size = N < 0 || lda < N || lda < 1 || !incx || batch_count < 0;
if(invalid_size || !N || !batch_count)
{
DAPI_EXPECT(invalid_size ? HIPBLAS_STATUS_INVALID_VALUE : HIPBLAS_STATUS_SUCCESS,
hipblasTrsvBatchedFn,
(handle, uplo, transA, diag, N, nullptr, lda, nullptr, incx, batch_count));
return;
}
// Naming: `h` is in CPU (host) memory(eg hA), `d` is in GPU (device) memory (eg dA).
// Allocate host memory
host_batch_matrix<T> hA(N, N, lda, batch_count);
host_batch_vector<T> hb(N, incx, batch_count);
host_batch_vector<T> hx(N, incx, batch_count);
host_batch_vector<T> hx_or_b(N, incx, batch_count);
// Check host memory allocation
CHECK_HIP_ERROR(hA.memcheck());
CHECK_HIP_ERROR(hb.memcheck());
CHECK_HIP_ERROR(hx.memcheck());
CHECK_HIP_ERROR(hx_or_b.memcheck());
// Allocate device memory
device_batch_matrix<T> dA(N, N, lda, batch_count);
device_batch_vector<T> dx_or_b(N, incx, batch_count);
// Check device memory allocation
CHECK_DEVICE_ALLOCATION(dA.memcheck());
CHECK_DEVICE_ALLOCATION(dx_or_b.memcheck());
double hipblas_error{0}, cumulative_hipblas_error{0};
// Initial Data on CPU
hipblas_init_matrix(hA,
arg,
hipblas_client_never_set_nan,
hipblas_diagonally_dominant_triangular_matrix,
true,
false);
hipblas_init_vector(hx, arg, hipblas_client_never_set_nan, false, true);
hb.copy_from(hx);
if(diag == HIPBLAS_DIAG_UNIT)
{
make_unit_diagonal(uplo, hA);
}
for(size_t b = 0; b < batch_count; b++)
{
// Calculate hb = hA*hx;
ref_trmv<T>(uplo, transA, diag, N, hA[b], lda, hb[b], incx);
}
hx_or_b.copy_from(hb);
CHECK_HIP_ERROR(dx_or_b.transfer_from(hx_or_b));
CHECK_HIP_ERROR(dA.transfer_from(hA));
/* =====================================================================
HIPBLAS
=================================================================== */
if(arg.unit_check || arg.norm_check)
{
CHECK_HIPBLAS_ERROR(hipblasSetPointerMode(handle, HIPBLAS_POINTER_MODE_HOST));
DAPI_CHECK(hipblasTrsvBatchedFn,
(handle,
uplo,
transA,
diag,
N,
dA.ptr_on_device(),
lda,
dx_or_b.ptr_on_device(),
incx,
batch_count));
CHECK_HIP_ERROR(hx_or_b.transfer_from(dx_or_b));
// Calculating error
// For norm_check/bench, currently taking the cumulative sum of errors over all batches
for(size_t b = 0; b < batch_count; b++)
{
hipblas_error = hipblas_abs(vector_norm_1<T>(N, abs_incx, hx[b], hx_or_b[b]));
if(arg.unit_check)
{
double tolerance = std::numeric_limits<real_t<T>>::epsilon() * 40 * N;
unit_check_error(hipblas_error, tolerance);
}
cumulative_hipblas_error += hipblas_error;
}
}
if(arg.timing)
{
double gpu_time_used{0};
hipStream_t stream;
CHECK_HIPBLAS_ERROR(hipblasGetStream(handle, &stream));
CHECK_HIPBLAS_ERROR(hipblasSetPointerMode(handle, HIPBLAS_POINTER_MODE_HOST));
int runs = arg.cold_iters + arg.iters;
for(int iter = 0; iter < runs; iter++)
{
if(iter == arg.cold_iters)
gpu_time_used = get_time_us_sync(stream);
DAPI_DISPATCH(hipblasTrsvBatchedFn,
(handle,
uplo,
transA,
diag,
N,
dA.ptr_on_device(),
lda,
dx_or_b.ptr_on_device(),
incx,
batch_count));
}
gpu_time_used = get_time_us_sync(stream) - gpu_time_used; // in microseconds
hipblasTrsvBatchedModel{}.log_args<T>(std::cout,
arg,
gpu_time_used,
trsv_gflop_count<T>(N),
trsv_gbyte_count<T>(N),
cumulative_hipblas_error);
}
}