6f754052cf
* [GPU] extended remote context to accept user queues for each stream * [GPU] OV2.0 API for queue sharing. Removed deviceName arg for context creation
77 lines
2.8 KiB
C++
77 lines
2.8 KiB
C++
#define CL_HPP_MINIMUM_OPENCL_VERSION 120
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#define CL_HPP_TARGET_OPENCL_VERSION 120
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#include <ie_core.hpp>
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#include <CL/cl2.hpp>
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#include <gpu/gpu_context_api_ocl.hpp>
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int main() {
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using namespace InferenceEngine;
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//! [part0]
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// ...
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// initialize the core and read the network
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InferenceEngine::Core ie;
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auto net = ie.ReadNetwork("network.xml");
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// initialize opencl context and create queue
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cl::Context ctx = get_my_OpenCL_context();
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cl::CommandQueue queue = get_my_OpenCL_queue();
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// share the queue with GPU plugin and compile ExecutableNetwork
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auto remote_context = gpu::make_shared_context(ie, "GPU", queue.get());
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auto exec_net_shared = ie.LoadNetwork(net, remote_context);
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// create the OpenCL buffers within the context
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cl::Buffer shared_in_buffer(ctx, CL_MEM_READ_WRITE, image_size * num_channels, NULL, &err);
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cl::Buffer shared_out_buffer(ctx, CL_MEM_READ_WRITE, image_size * num_channels, NULL, &err);
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// wrap in and out buffers into RemoteBlob and set them to infer request
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auto shared_in_blob = gpu::make_shared_blob(input_info->getTensorDesc(), remote_context, shared_in_buffer);
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auto shared_out_blob = gpu::make_shared_blob(out_data->getTensorDesc(), remote_context, shared_out_buffer);
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auto infer_request = exec_net_shared.CreateInferRequest();
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infer_request.SetBlob(input_name, shared_in_blob);
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infer_request.SetBlob(output_name, shared_out_blob);
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// ...
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// execute user kernel
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cl::Kernel kernel_preproc(program, kernel_name_preproc.c_str());
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kernel_preproc.setArg(0, shared_in_buffer);
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queue.enqueueNDRangeKernel(kernel_preproc,
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cl::NDRange(0),
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cl::NDRange(image_size),
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cl::NDRange(1),
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nullptr, // wait events *
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&profileEvent);
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// Blocking clFinish() call is not required, but this barrier is added to the queue to guarantee that user kernel is finished
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// before any inference primitive is started
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queue.enqueueBarrierWithWaitList(nullptr, nullptr);
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// ...
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// pass results to the inference
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// since the remote context is created with queue sharing, StartAsync() guarantees that scheduling is finished
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infer_request.StartAsync();
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// execute some postprocessing kernel.
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// infer_request.Wait() is not called, synchonization between inference and post-processing is done via
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// enqueueBarrierWithWaitList call.
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cl::Kernel kernel_postproc(program, kernel_name_postproc.c_str());
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kernel_postproc.setArg(0, shared_out_buffer);
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queue.enqueueBarrierWithWaitList(nullptr, nullptr);
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queue.enqueueNDRangeKernel(kernel_postproc,
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cl::NDRange(0),
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cl::NDRange(image_size),
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cl::NDRange(1),
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nullptr, // wait events *
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&profileEvent);
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// Wait for pipeline completion
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queue.finish();
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//! [part0]
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return 0;
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}
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