Reorder between CPU and GPU enginesΒΆ
This C API example demonstrates programming flow when reordering memory between CPU and GPU engines.
This C API example demonstrates programming flow when reordering memory between CPU and GPU engines.
/******************************************************************************* * Copyright 2019-2022 Intel Corporation * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. *******************************************************************************/ #include <stdio.h> #include <stdlib.h> #include "oneapi/dnnl/dnnl.h" #include "example_utils.h" size_t product(int n_dims, const dnnl_dim_t dims[]) { size_t n_elems = 1; for (int d = 0; d < n_dims; ++d) { n_elems *= (size_t)dims[d]; } return n_elems; } void fill(dnnl_memory_t mem, int n_dims, const dnnl_dim_t dims[]) { const size_t n_elems = product(n_dims, dims); float *array = (float *)malloc(n_elems * sizeof(float)); if (!array) COMPLAIN_EXAMPLE_ERROR_AND_EXIT("%s", "malloc returned NULL"); for (size_t e = 0; e < n_elems; ++e) { array[e] = e % 7 ? 1.0f : -1.0f; } write_to_dnnl_memory(array, mem); free(array); } int find_negative(dnnl_memory_t mem, int n_dims, const dnnl_dim_t dims[]) { const size_t n_elems = product(n_dims, dims); float *array = (float *)malloc(n_elems * sizeof(float)); if (!array) COMPLAIN_EXAMPLE_ERROR_AND_EXIT("%s", "malloc returned NULL"); read_from_dnnl_memory(array, mem); int negs = 0; for (size_t e = 0; e < n_elems; ++e) { negs += array[e] < 0.0f; } free(array); return negs; } void cross_engine_reorder() { dnnl_engine_t engine_cpu, engine_gpu; CHECK(dnnl_engine_create(&engine_cpu, validate_engine_kind(dnnl_cpu), 0)); CHECK(dnnl_engine_create(&engine_gpu, validate_engine_kind(dnnl_gpu), 0)); const dnnl_dims_t tz = {2, 16, 1, 1}; dnnl_memory_desc_t m_cpu_md, m_gpu_md; CHECK(dnnl_memory_desc_create_with_tag( &m_cpu_md, 4, tz, dnnl_f32, dnnl_nchw)); CHECK(dnnl_memory_desc_create_with_tag( &m_gpu_md, 4, tz, dnnl_f32, dnnl_nchw)); dnnl_memory_t m_cpu, m_gpu; CHECK(dnnl_memory_create( &m_cpu, m_cpu_md, engine_cpu, DNNL_MEMORY_ALLOCATE)); CHECK(dnnl_memory_create( &m_gpu, m_gpu_md, engine_gpu, DNNL_MEMORY_ALLOCATE)); fill(m_cpu, 4, tz); if (find_negative(m_cpu, 4, tz) == 0) COMPLAIN_EXAMPLE_ERROR_AND_EXIT( "%s", "incorrect data fill, no negative values found"); /* reorder cpu -> gpu */ dnnl_primitive_desc_t r1_pd; CHECK(dnnl_reorder_primitive_desc_create( &r1_pd, m_cpu_md, engine_cpu, m_gpu_md, engine_gpu, NULL)); dnnl_primitive_t r1; CHECK(dnnl_primitive_create(&r1, r1_pd)); /* relu gpu */ dnnl_primitive_desc_t relu_pd; CHECK(dnnl_eltwise_forward_primitive_desc_create(&relu_pd, engine_gpu, dnnl_forward, dnnl_eltwise_relu, m_gpu_md, m_gpu_md, 0.0f, 0.0f, NULL)); dnnl_primitive_t relu; CHECK(dnnl_primitive_create(&relu, relu_pd)); /* reorder gpu -> cpu */ dnnl_primitive_desc_t r2_pd; CHECK(dnnl_reorder_primitive_desc_create( &r2_pd, m_gpu_md, engine_gpu, m_cpu_md, engine_cpu, NULL)); dnnl_primitive_t r2; CHECK(dnnl_primitive_create(&r2, r2_pd)); dnnl_stream_t stream_gpu; CHECK(dnnl_stream_create( &stream_gpu, engine_gpu, dnnl_stream_default_flags)); dnnl_exec_arg_t r1_args[] = {{DNNL_ARG_FROM, m_cpu}, {DNNL_ARG_TO, m_gpu}}; CHECK(dnnl_primitive_execute(r1, stream_gpu, 2, r1_args)); dnnl_exec_arg_t relu_args[] = {{DNNL_ARG_SRC, m_gpu}, {DNNL_ARG_DST, m_gpu}}; CHECK(dnnl_primitive_execute(relu, stream_gpu, 2, relu_args)); dnnl_exec_arg_t r2_args[] = {{DNNL_ARG_FROM, m_gpu}, {DNNL_ARG_TO, m_cpu}}; CHECK(dnnl_primitive_execute(r2, stream_gpu, 2, r2_args)); CHECK(dnnl_stream_wait(stream_gpu)); if (find_negative(m_cpu, 4, tz) != 0) COMPLAIN_EXAMPLE_ERROR_AND_EXIT( "%s", "found negative values after ReLU applied"); /* clean up */ dnnl_primitive_desc_destroy(relu_pd); dnnl_primitive_desc_destroy(r1_pd); dnnl_primitive_desc_destroy(r2_pd); dnnl_primitive_destroy(relu); dnnl_primitive_destroy(r1); dnnl_primitive_destroy(r2); dnnl_memory_destroy(m_cpu); dnnl_memory_destroy(m_gpu); dnnl_memory_desc_destroy(m_cpu_md); dnnl_memory_desc_destroy(m_gpu_md); dnnl_stream_destroy(stream_gpu); dnnl_engine_destroy(engine_cpu); dnnl_engine_destroy(engine_gpu); } int main() { cross_engine_reorder(); printf("Example passed on CPU/GPU.\n"); return 0; }