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304 lines
11 KiB
C++
304 lines
11 KiB
C++
/* ************************************************************************
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* Copyright (C) 2016-2024 Advanced Micro Devices, Inc. All rights reserved.
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*
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* Permission is hereby granted, free of charge, to any person obtaining a copy
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* of this software and associated documentation files (the "Software"), to deal
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* in the Software without restriction, including without limitation the rights
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* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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* copies of the Software, and to permit persons to whom the Software is
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* furnished to do so, subject to the following conditions:
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*
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* The above copyright notice and this permission notice shall be included in
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* all copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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* SOFTWARE.
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*
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* ************************************************************************ */
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#include <fstream>
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#include <iostream>
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#include <stdlib.h>
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#include <vector>
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#include "testing_common.hpp"
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/* ============================================================================================ */
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using hipblasTrsvBatchedModel
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= ArgumentModel<e_a_type, e_uplo, e_transA, e_diag, e_N, e_lda, e_incx, e_batch_count>;
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inline void testname_trsv_batched(const Arguments& arg, std::string& name)
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{
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hipblasTrsvBatchedModel{}.test_name(arg, name);
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}
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template <typename T>
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void testing_trsv_batched_bad_arg(const Arguments& arg)
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{
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bool FORTRAN = arg.api == hipblas_client_api::FORTRAN;
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auto hipblasTrsvBatchedFn
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= FORTRAN ? hipblasTrsvBatched<T, true> : hipblasTrsvBatched<T, false>;
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auto hipblasTrsvBatchedFn_64
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= arg.api == FORTRAN_64 ? hipblasTrsvBatched_64<T, true> : hipblasTrsvBatched_64<T, false>;
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for(auto pointer_mode : {HIPBLAS_POINTER_MODE_HOST, HIPBLAS_POINTER_MODE_DEVICE})
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{
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hipblasLocalHandle handle(arg);
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CHECK_HIPBLAS_ERROR(hipblasSetPointerMode(handle, pointer_mode));
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hipblasOperation_t transA = HIPBLAS_OP_N;
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hipblasFillMode_t uplo = HIPBLAS_FILL_MODE_UPPER;
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hipblasDiagType_t diag = HIPBLAS_DIAG_NON_UNIT;
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int64_t N = 100;
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int64_t lda = 100;
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int64_t incx = 1;
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int64_t batch_count = 2;
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// Allocate device memory
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device_batch_matrix<T> dA(N, N, lda, batch_count);
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device_batch_vector<T> dx(N, incx, batch_count);
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DAPI_EXPECT(HIPBLAS_STATUS_NOT_INITIALIZED,
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hipblasTrsvBatchedFn,
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(nullptr,
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uplo,
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transA,
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diag,
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N,
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dA.ptr_on_device(),
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lda,
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dx.ptr_on_device(),
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incx,
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batch_count));
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DAPI_EXPECT(HIPBLAS_STATUS_INVALID_VALUE,
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hipblasTrsvBatchedFn,
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(handle,
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HIPBLAS_FILL_MODE_FULL,
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transA,
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diag,
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N,
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dA.ptr_on_device(),
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lda,
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dx.ptr_on_device(),
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incx,
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batch_count));
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DAPI_EXPECT(HIPBLAS_STATUS_INVALID_ENUM,
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hipblasTrsvBatchedFn,
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(handle,
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(hipblasFillMode_t)HIPBLAS_OP_N,
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transA,
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diag,
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N,
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dA.ptr_on_device(),
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lda,
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dx.ptr_on_device(),
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incx,
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batch_count));
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DAPI_EXPECT(HIPBLAS_STATUS_INVALID_ENUM,
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hipblasTrsvBatchedFn,
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(handle,
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uplo,
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(hipblasOperation_t)HIPBLAS_FILL_MODE_FULL,
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diag,
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N,
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dA.ptr_on_device(),
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lda,
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dx.ptr_on_device(),
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incx,
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batch_count));
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DAPI_EXPECT(HIPBLAS_STATUS_INVALID_ENUM,
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hipblasTrsvBatchedFn,
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(handle,
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uplo,
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transA,
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(hipblasDiagType_t)HIPBLAS_FILL_MODE_FULL,
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N,
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dA.ptr_on_device(),
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lda,
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dx.ptr_on_device(),
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incx,
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batch_count));
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DAPI_EXPECT(
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HIPBLAS_STATUS_INVALID_VALUE,
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hipblasTrsvBatchedFn,
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(handle, uplo, transA, diag, N, nullptr, lda, dx.ptr_on_device(), incx, batch_count));
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DAPI_EXPECT(
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HIPBLAS_STATUS_INVALID_VALUE,
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hipblasTrsvBatchedFn,
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(handle, uplo, transA, diag, N, dA.ptr_on_device(), lda, nullptr, incx, batch_count));
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// With N == 0, can have all nullptrs
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DAPI_CHECK(hipblasTrsvBatchedFn,
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(handle, uplo, transA, diag, 0, nullptr, lda, nullptr, incx, batch_count));
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DAPI_CHECK(hipblasTrsvBatchedFn,
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(handle, uplo, transA, diag, N, nullptr, lda, nullptr, incx, 0));
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}
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}
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template <typename T>
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void testing_trsv_batched(const Arguments& arg)
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{
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bool FORTRAN = arg.api == hipblas_client_api::FORTRAN;
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auto hipblasTrsvBatchedFn
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= FORTRAN ? hipblasTrsvBatched<T, true> : hipblasTrsvBatched<T, false>;
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auto hipblasTrsvBatchedFn_64
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= arg.api == FORTRAN_64 ? hipblasTrsvBatched_64<T, true> : hipblasTrsvBatched_64<T, false>;
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hipblasFillMode_t uplo = char2hipblas_fill(arg.uplo);
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hipblasDiagType_t diag = char2hipblas_diagonal(arg.diag);
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hipblasOperation_t transA = char2hipblas_operation(arg.transA);
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int64_t N = arg.N;
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int64_t incx = arg.incx;
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int64_t lda = arg.lda;
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int64_t batch_count = arg.batch_count;
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size_t abs_incx = incx < 0 ? -incx : incx;
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hipblasLocalHandle handle(arg);
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// argument sanity check, quick return if input parameters are invalid before allocating invalid
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// memory
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bool invalid_size = N < 0 || lda < N || lda < 1 || !incx || batch_count < 0;
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if(invalid_size || !N || !batch_count)
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{
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DAPI_EXPECT(invalid_size ? HIPBLAS_STATUS_INVALID_VALUE : HIPBLAS_STATUS_SUCCESS,
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hipblasTrsvBatchedFn,
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(handle, uplo, transA, diag, N, nullptr, lda, nullptr, incx, batch_count));
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return;
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}
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// Naming: `h` is in CPU (host) memory(eg hA), `d` is in GPU (device) memory (eg dA).
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// Allocate host memory
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host_batch_matrix<T> hA(N, N, lda, batch_count);
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host_batch_vector<T> hb(N, incx, batch_count);
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host_batch_vector<T> hx(N, incx, batch_count);
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host_batch_vector<T> hx_or_b(N, incx, batch_count);
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// Check host memory allocation
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CHECK_HIP_ERROR(hA.memcheck());
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CHECK_HIP_ERROR(hb.memcheck());
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CHECK_HIP_ERROR(hx.memcheck());
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CHECK_HIP_ERROR(hx_or_b.memcheck());
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// Allocate device memory
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device_batch_matrix<T> dA(N, N, lda, batch_count);
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device_batch_vector<T> dx_or_b(N, incx, batch_count);
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// Check device memory allocation
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CHECK_DEVICE_ALLOCATION(dA.memcheck());
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CHECK_DEVICE_ALLOCATION(dx_or_b.memcheck());
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double hipblas_error{0}, cumulative_hipblas_error{0};
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// Initial Data on CPU
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hipblas_init_matrix(hA,
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arg,
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hipblas_client_never_set_nan,
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hipblas_diagonally_dominant_triangular_matrix,
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true,
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false);
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hipblas_init_vector(hx, arg, hipblas_client_never_set_nan, false, true);
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hb.copy_from(hx);
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if(diag == HIPBLAS_DIAG_UNIT)
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{
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make_unit_diagonal(uplo, hA);
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}
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for(size_t b = 0; b < batch_count; b++)
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{
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// Calculate hb = hA*hx;
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ref_trmv<T>(uplo, transA, diag, N, hA[b], lda, hb[b], incx);
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}
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hx_or_b.copy_from(hb);
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CHECK_HIP_ERROR(dx_or_b.transfer_from(hx_or_b));
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CHECK_HIP_ERROR(dA.transfer_from(hA));
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/* =====================================================================
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HIPBLAS
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=================================================================== */
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if(arg.unit_check || arg.norm_check)
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{
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CHECK_HIPBLAS_ERROR(hipblasSetPointerMode(handle, HIPBLAS_POINTER_MODE_HOST));
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DAPI_CHECK(hipblasTrsvBatchedFn,
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(handle,
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uplo,
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transA,
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diag,
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N,
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dA.ptr_on_device(),
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lda,
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dx_or_b.ptr_on_device(),
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incx,
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batch_count));
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CHECK_HIP_ERROR(hx_or_b.transfer_from(dx_or_b));
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// Calculating error
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// For norm_check/bench, currently taking the cumulative sum of errors over all batches
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for(size_t b = 0; b < batch_count; b++)
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{
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hipblas_error = hipblas_abs(vector_norm_1<T>(N, abs_incx, hx[b], hx_or_b[b]));
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if(arg.unit_check)
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{
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double tolerance = std::numeric_limits<real_t<T>>::epsilon() * 40 * N;
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unit_check_error(hipblas_error, tolerance);
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}
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cumulative_hipblas_error += hipblas_error;
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}
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}
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if(arg.timing)
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{
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double gpu_time_used{0};
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hipStream_t stream;
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CHECK_HIPBLAS_ERROR(hipblasGetStream(handle, &stream));
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CHECK_HIPBLAS_ERROR(hipblasSetPointerMode(handle, HIPBLAS_POINTER_MODE_HOST));
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int runs = arg.cold_iters + arg.iters;
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for(int iter = 0; iter < runs; iter++)
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{
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if(iter == arg.cold_iters)
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gpu_time_used = get_time_us_sync(stream);
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DAPI_DISPATCH(hipblasTrsvBatchedFn,
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(handle,
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uplo,
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transA,
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diag,
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N,
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dA.ptr_on_device(),
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lda,
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dx_or_b.ptr_on_device(),
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incx,
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batch_count));
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}
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gpu_time_used = get_time_us_sync(stream) - gpu_time_used; // in microseconds
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hipblasTrsvBatchedModel{}.log_args<T>(std::cout,
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arg,
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gpu_time_used,
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trsv_gflop_count<T>(N),
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trsv_gbyte_count<T>(N),
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cumulative_hipblas_error);
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}
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}
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