• L.S. Cook's avatar
    Leona/editing (#498) · db595a3a
    L.S. Cook authored
    * Doc the A-ops.
    
    * Better structure for ops and the docs around them, based on cyphers branch for doc-the-a-ops
    
    * More edits for merge into preview branch
    
    * Update link to framework integration guide page on testing libngraph
    
    * New branch for editing public-facing docs
    
    * Make sure updated graphic gets added, correct compiler version on install page
    
    * Update README to match content on legacy Python repo
    
    * Let's see if this fixes the bad merge
    
    * Working down in doc directory, forgot to update top-level readme with feedback from review
    
    * Correct typo
    
    * Trying to fix the ops
    
    * Try adding convolution manually from master
    
    * Update pictorial image of nGraph IR
    db595a3a
README.md 1.05 KB

Intel:registered: nGraph:tm: library

Welcome to Intel nGraph, an open source C++ library for developers of Deep Learning (DL) systems. Here you will find a suite of components, APIs, and documentation that can be used to compile and run Deep Neural Network (DNN) models defined in a variety of frameworks.

The nGraph library translates a framework’s representation of computations into an Intermediate Representation (IR) designed to promote computational efficiency on target hardware. Initially-supported backends include Intel Architecture CPUs, the Intel:registered: Nervana Neural Network Processor:tm: (NNP), and NVIDIA* GPUs. Currently-supported compiler optimizations include efficient memory management and data layout abstraction.

See our install docs for how to get started.

For this early release, we provide framework integration guides to compile MXNet and TensorFlow-based projects.