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* updating examples with current api calls * Fixing capitalization in api calls, adding RKNPU update * Correcting nuphar and rknpu ep api calls * Include creating session in readme
35 lines
1.8 KiB
Markdown
35 lines
1.8 KiB
Markdown
# DNNL Execution Provider
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Intel® Math Kernel Library for Deep Neural Networks (Intel® DNNL) is an open-source performance library for deep-learning applications. The library accelerates deep-learning applications and frameworks on Intel® architecture and Intel® Processor Graphics Architecture. Intel DNNL contains vectorized and threaded building blocks that you can use to implement deep neural networks (DNN) with C and C++ interfaces. For more, please see the DNNL documentation on (https://intel.github.io/mkl-dnn/).
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Intel and Microsoft have developed DNNL Execution Provider (EP) for ONNX Runtime to accelerate performance of ONNX Runtime using Intel® Math Kernel Library for Deep Neural Networks (Intel® DNNL) optimized primitives.
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For information on how DNNL optimizes subgraphs, see [Subgraph Optimization](./MKL-DNN-Subgraphs.md)
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## Build
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For build instructions, please see the [BUILD page](../../BUILD.md#dnnl-and-mklml).
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## Supported OS
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* Ubuntu 16.04
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* Windows 10
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* Mac OS X
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## Supported backend
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* CPU
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## Using the DNNL Execution Provider
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### C/C++
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The DNNLExecutionProvider execution provider needs to be registered with ONNX Runtime to enable in the inference session.
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```
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Ort::Env env = Ort::Env{ORT_LOGGING_LEVEL_ERROR, "Default"};
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Ort::SessionOptions sf;
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bool enable_cpu_mem_arena = true;
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Ort::ThrowOnError(OrtSessionOptionsAppendExecutionProvider_Dnnl(sf, enable_cpu_mem_arena));
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```
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The C API details are [here](../C_API.md#c-api).
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### Python
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When using the python wheel from the ONNX Runtime built with DNNL execution provider, it will be automatically prioritized over the CPU execution provider. Python APIs details are [here](https://aka.ms/onnxruntime-python).
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## Performance Tuning
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For performance tuning, please see guidance on this page: [ONNX Runtime Perf Tuning](../ONNX_Runtime_Perf_Tuning.md)
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