/* ************************************************************************ * 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 #include #include #include "testing_common.hpp" /* ============================================================================================ */ using hipblasCopyBatchedModel = ArgumentModel; inline void testname_copy_batched(const Arguments& arg, std::string& name) { hipblasCopyBatchedModel{}.test_name(arg, name); } template void testing_copy_batched_bad_arg(const Arguments& arg) { bool FORTRAN = arg.api == hipblas_client_api::FORTRAN; auto hipblasCopyBatchedFn = FORTRAN ? hipblasCopyBatched : hipblasCopyBatched; auto hipblasCopyBatchedFn_64 = arg.api == FORTRAN_64 ? hipblasCopyBatched_64 : hipblasCopyBatched_64; hipblasLocalHandle handle(arg); int64_t N = 100; int64_t incx = 1; int64_t incy = 1; int64_t batch_count = 2; device_batch_vector dx(N, incx, batch_count); device_batch_vector dy(N, incy, batch_count); DAPI_EXPECT(HIPBLAS_STATUS_NOT_INITIALIZED, hipblasCopyBatchedFn, (nullptr, N, dx, incx, dy, incy, batch_count)); DAPI_EXPECT(HIPBLAS_STATUS_INVALID_VALUE, hipblasCopyBatchedFn, (handle, N, nullptr, incx, dy, incy, batch_count)); DAPI_EXPECT(HIPBLAS_STATUS_INVALID_VALUE, hipblasCopyBatchedFn, (handle, N, dx, incx, nullptr, incy, batch_count)); } template void testing_copy_batched(const Arguments& arg) { bool FORTRAN = arg.api == hipblas_client_api::FORTRAN; auto hipblasCopyBatchedFn = FORTRAN ? hipblasCopyBatched : hipblasCopyBatched; auto hipblasCopyBatchedFn_64 = arg.api == FORTRAN_64 ? hipblasCopyBatched_64 : hipblasCopyBatched_64; int64_t N = arg.N; int64_t incx = arg.incx; int64_t incy = arg.incy; int64_t batch_count = arg.batch_count; hipblasLocalHandle handle(arg); // argument sanity check, quick return if input parameters are invalid before allocating invalid // memory if(N <= 0 || batch_count <= 0) { DAPI_CHECK(hipblasCopyBatchedFn, (handle, N, nullptr, incx, nullptr, incy, batch_count)); return; } int64_t abs_incy = incy >= 0 ? incy : -incy; double hipblas_error = 0.0; double gpu_time_used = 0.0; // Naming: dX is in GPU (device) memory. hK is in CPU (host) memory, plz follow this practice host_batch_vector hx(N, incx, batch_count); host_batch_vector hy(N, incy, batch_count); host_batch_vector hx_cpu(N, incx, batch_count); host_batch_vector hy_cpu(N, incy, batch_count); device_batch_vector dx(N, incx, batch_count); device_batch_vector dy(N, incy, batch_count); CHECK_DEVICE_ALLOCATION(dx.memcheck()); CHECK_DEVICE_ALLOCATION(dy.memcheck()); hipblas_init_vector(hx, arg, hipblas_client_alpha_sets_nan, true); hipblas_init_vector(hy, arg, hipblas_client_alpha_sets_nan, false); hx_cpu.copy_from(hx); hy_cpu.copy_from(hy); CHECK_DEVICE_ALLOCATION(dx.transfer_from(hx)); CHECK_DEVICE_ALLOCATION(dy.transfer_from(hy)); if(arg.unit_check || arg.norm_check) { /* ===================================================================== HIPBLAS =================================================================== */ DAPI_CHECK(hipblasCopyBatchedFn, (handle, N, dx.ptr_on_device(), incx, dy.ptr_on_device(), incy, batch_count)); // copy output from device to CPU CHECK_HIP_ERROR(hy.transfer_from(dy)); /* ===================================================================== CPU BLAS =================================================================== */ for(int64_t b = 0; b < batch_count; b++) { ref_copy(N, hx_cpu[b], incx, hy_cpu[b], incy); } // enable unit check, notice unit check is not invasive, but norm check is, // unit check and norm check can not be interchanged their order if(arg.unit_check) { unit_check_general(1, N, batch_count, abs_incy, hy_cpu, hy); } if(arg.norm_check) { hipblas_error = norm_check_general('F', 1, N, abs_incy, hy_cpu, hy, batch_count); } } // end of if unit check if(arg.timing) { hipStream_t stream; CHECK_HIPBLAS_ERROR(hipblasGetStream(handle, &stream)); 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_CHECK( hipblasCopyBatchedFn, (handle, N, dx.ptr_on_device(), incx, dy.ptr_on_device(), incy, batch_count)); } gpu_time_used = get_time_us_sync(stream) - gpu_time_used; hipblasCopyBatchedModel{}.log_args(std::cout, arg, gpu_time_used, copy_gflop_count(N), copy_gbyte_count(N), hipblas_error); } }