/* ************************************************************************ * Copyright (C) 2016-2025 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 * 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 hipblasDotBatchedModel = ArgumentModel; inline void testname_dot_batched(const Arguments& arg, std::string& name) { hipblasDotBatchedModel{}.test_name(arg, name); } inline void testname_dotc_batched(const Arguments& arg, std::string& name) { hipblasDotBatchedModel{}.test_name(arg, name); } template void testing_dot_batched_bad_arg(const Arguments& arg) { bool FORTRAN = arg.api == hipblas_client_api::FORTRAN; auto hipblasDotBatchedFn = FORTRAN ? (CONJ ? hipblasDotcBatched : hipblasDotBatched) : (CONJ ? hipblasDotcBatched : hipblasDotBatched); auto hipblasDotBatchedFn_64 = arg.api == FORTRAN_64 ? (CONJ ? hipblasDotcBatched_64 : hipblasDotBatched_64) : (CONJ ? hipblasDotcBatched_64 : hipblasDotBatched_64); for(auto pointer_mode : {HIPBLAS_POINTER_MODE_HOST, HIPBLAS_POINTER_MODE_DEVICE}) { hipblasLocalHandle handle(arg); CHECK_HIPBLAS_ERROR(hipblasSetPointerMode(handle, pointer_mode)); int64_t N = 100; int64_t incx = 1; int64_t incy = 1; int64_t batch_count = 1; device_batch_vector dx(N, incx, batch_count); device_batch_vector dy(N, incy, batch_count); device_vector d_res(batch_count); // None of these test cases will write to result so using device pointer is fine for both modes DAPI_EXPECT(HIPBLAS_STATUS_NOT_INITIALIZED, hipblasDotBatchedFn, (nullptr, N, dx, incx, dy, incy, batch_count, d_res)); DAPI_EXPECT(HIPBLAS_STATUS_INVALID_VALUE, hipblasDotBatchedFn, (handle, N, nullptr, incx, dy, incy, batch_count, d_res)); DAPI_EXPECT(HIPBLAS_STATUS_INVALID_VALUE, hipblasDotBatchedFn, (handle, N, dx, incx, nullptr, incy, batch_count, d_res)); DAPI_EXPECT(HIPBLAS_STATUS_INVALID_VALUE, hipblasDotBatchedFn, (handle, N, dx, incx, dy, incy, batch_count, nullptr)); } } template void testing_dotc_batched_bad_arg(const Arguments& arg) { testing_dot_batched_bad_arg(arg); } template void testing_dot_batched(const Arguments& arg) { bool FORTRAN = arg.api == hipblas_client_api::FORTRAN; auto hipblasDotBatchedFn = FORTRAN ? (CONJ ? hipblasDotcBatched : hipblasDotBatched) : (CONJ ? hipblasDotcBatched : hipblasDotBatched); auto hipblasDotBatchedFn_64 = arg.api == FORTRAN_64 ? (CONJ ? hipblasDotcBatched_64 : hipblasDotBatched_64) : (CONJ ? hipblasDotcBatched_64 : hipblasDotBatched_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) { int64_t batches = std::max(int64_t(1), batch_count); device_vector d_hipblas_result_0(batches); host_vector h_hipblas_result_0(batches); hipblas_init_nan(h_hipblas_result_0.data(), batches); CHECK_HIP_ERROR(hipMemcpy( d_hipblas_result_0, h_hipblas_result_0, sizeof(T) * batches, hipMemcpyHostToDevice)); CHECK_HIPBLAS_ERROR(hipblasSetPointerMode(handle, HIPBLAS_POINTER_MODE_DEVICE)); DAPI_CHECK(hipblasDotBatchedFn, (handle, N, nullptr, incx, nullptr, incy, batch_count, d_hipblas_result_0)); if(batch_count > 0) { host_vector cpu_0(batch_count); host_vector gpu_0(batch_count); CHECK_HIP_ERROR(hipMemcpy( gpu_0, d_hipblas_result_0, sizeof(T) * batch_count, hipMemcpyDeviceToHost)); unit_check_general(1, batch_count, 1, cpu_0, gpu_0); } return; } double gpu_time_used{0}, hipblas_error_host{0}, hipblas_error_device{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_vector h_cpu_result(batch_count); host_vector h_hipblas_result1(batch_count); host_vector h_hipblas_result2(batch_count); device_batch_vector dx(N, incx, batch_count); device_batch_vector dy(N, incy, batch_count); device_vector d_hipblas_result(batch_count); CHECK_DEVICE_ALLOCATION(dx.memcheck()); CHECK_DEVICE_ALLOCATION(dy.memcheck()); CHECK_DEVICE_ALLOCATION(d_hipblas_result.memcheck()); hipblas_init_vector(hx, arg, hipblas_client_alpha_sets_nan, true, true); hipblas_init_vector(hy, arg, hipblas_client_alpha_sets_nan, false); CHECK_HIP_ERROR(dx.transfer_from(hx)); CHECK_HIP_ERROR(dy.transfer_from(hy)); if(arg.unit_check || arg.norm_check) { /* ===================================================================== HIPBLAS =================================================================== */ // hipblasDot accept both dev/host pointer for the scalar CHECK_HIPBLAS_ERROR(hipblasSetPointerMode(handle, HIPBLAS_POINTER_MODE_DEVICE)); DAPI_CHECK(hipblasDotBatchedFn, (handle, N, dx.ptr_on_device(), incx, dy.ptr_on_device(), incy, batch_count, d_hipblas_result)); CHECK_HIPBLAS_ERROR(hipblasSetPointerMode(handle, HIPBLAS_POINTER_MODE_HOST)); DAPI_CHECK(hipblasDotBatchedFn, (handle, N, dx.ptr_on_device(), incx, dy.ptr_on_device(), incy, batch_count, reinterpret_cast*>(h_hipblas_result1.data()))); CHECK_HIP_ERROR(hipMemcpy( h_hipblas_result2, d_hipblas_result, sizeof(T) * batch_count, hipMemcpyDeviceToHost)); /* ===================================================================== CPU BLAS =================================================================== */ for(int64_t b = 0; b < batch_count; b++) { (CONJ ? ref_dotc : ref_dot)(N, hx[b], incx, hy[b], incy, &(h_cpu_result[b])); } bool near_check = arg.initialization == hipblas_initialization::hpl; double abs_error = hipblas_type_epsilon * N; if(arg.unit_check) { if(near_check) { near_check_general( batch_count, 1, 1, h_cpu_result.data(), h_hipblas_result1.data(), abs_error); near_check_general( batch_count, 1, 1, h_cpu_result.data(), h_hipblas_result2.data(), abs_error); } else { unit_check_general(1, batch_count, 1, h_cpu_result, h_hipblas_result1); unit_check_general(1, batch_count, 1, h_cpu_result, h_hipblas_result2); } } if(arg.norm_check) { hipblas_error_host = norm_check_general('F', 1, batch_count, 1, h_cpu_result, h_hipblas_result1); hipblas_error_device = norm_check_general('F', 1, batch_count, 1, h_cpu_result, h_hipblas_result2); } } // end of if unit/norm check if(arg.timing) { hipStream_t stream; CHECK_HIPBLAS_ERROR(hipblasGetStream(handle, &stream)); CHECK_HIPBLAS_ERROR(hipblasSetPointerMode(handle, HIPBLAS_POINTER_MODE_DEVICE)); 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(hipblasDotBatchedFn, (handle, N, dx.ptr_on_device(), incx, dy.ptr_on_device(), incy, batch_count, d_hipblas_result)); } gpu_time_used = get_time_us_sync(stream) - gpu_time_used; hipblasDotBatchedModel{}.log_args(std::cout, arg, gpu_time_used, dot_gflop_count(N), dot_gbyte_count(N), hipblas_error_host, hipblas_error_device); } } template void testing_dotc_batched(const Arguments& arg) { testing_dot_batched(arg); }