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Welcome to Intel® nGraph™, an open source C++ library and compiler. This project enables modern compute platforms to run and train Deep Neural Network models. It is framework-neutral and supports a variety of backends used by Deep Learning frameworks.


For this early release, we’ve provided Framework Integration Guides to compile and run MXNet* and TensorFlow*-based projects. If you already have a trained model, see our section on How to Import a model and start working with the nGraph APIs.


The library code is under active development as we’re continually adding support for more ops, more frameworks, and more backends.

The nGraph++ library translates a framework’s representation of computations into an Intermediate Representation that promotes computational efficiency on target hardware. Initially-supported backends include Intel Architecture CPUs (CPU), the Intel® Nervana Neural Network Processor™ (NNP), and NVIDIA* GPUs. Currently-supported compiler optimizations include efficient memory management and data layout abstraction.

Further project details can be found on our About page.

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