neon

Release:2.5.0+6577b784
Date:Dec 21, 2017

neon is Intel Nervana ‘s reference deep learning framework committed to best performance on all hardware. Designed for ease-of-use and extensibility.

Features include:

  • Support for commonly used models including convnets, RNNs, LSTMs, and autoencoders. You can find many pre-trained implementations of these in our model zoo
  • Tight integration with our state-of-the-art GPU kernel library and Intel CPU MKLML library
  • 3s/macrobatch (3072 images) on AlexNet on Titan X (Full run on 1 GPU ~ 32 hrs)
  • Basic automatic differentiation support
  • Framework for visualization
  • Swappable hardware backends: write code once and deploy on CPUs, GPUs, or Nervana hardware

New features in this release:

  • Optimized SSD MKL backend performance (~3X boost version over version)
  • Bumped aeon version to v1.3.0
  • Fixed inference performance issue of MKL batchnorm
  • Fixed batch prediction issue for gpu backend
  • Enabled subset_pct for MNIST_DCGAN example
  • Updated “make clean” to clean up mkl artifacts
  • Added dockerfile for IA mkl
  • See more in the change log.

We use neon internally at Intel to solve our customers’ problems in many domains. Consider joining us. We are hiring across several roles. Apply here!