nGraph is a deep learning compiler from Intel®. The integration of nGraph as an execution provider (EP) into ONNX Runtime accelerates performance of ONNX model workloads across wide range of hardware offerings. Microsoft and Intel worked closely to integrate the nGraph EP with ONNX Runtime to showcase the benefits of quantization (int8). The nGraph EP leverages Intel® DL Boost and delivers performance increase with minimal loss of accuracy relative to FP32 ONNX models. With the nGraph EP, the ONNX Runtime delivers better inference performance across range of Intel hardware including Intel® Xeon® Processors compared to a generic CPU execution provider.
Developers can now tap into the power of nGraph through ONNX Runtime to accelerate inference performance of ONNX models. Instructions for building the nGraph execution provider from the source is available here.
While the nGraph Compiler stack supports various operating systems and backends (full list available here), the nGraph execution provider for ONNX Runtime is validated for the following:
- Ubuntu 16.04
- More to be added soon!
- CPU
- More to be added soon!
To use nGraph as execution provider for inferencing, please register it as below.
InferenceSession session_object{so};
session_object.RegisterExecutionProvider(std::make_unique<::onnxruntime::NGRAPHExecutionProvider>());
status = session_object.Load(model_file_name);
The C API details are here.
When using the python wheel from the ONNX Runtime built with nGraph execution provider, it will be automatically prioritized over the CPU execution provider. Python APIs details are here.
You can test the performance of your ONNX Model with the nGraph execution provider. Use the flag -e ngraph in onnxruntime_perf_test.