Blog

Jan 24, 2018   |   Peng Zhang, Wei Wang, Baojun Liu, Jayaram Bobba

neon™ 2.6.0: Inference Optimizations for Single Shot MultiBox Detector on Intel® Xeon® Processor Architectures

We are excited to release the neon™ 2.6.0 framework, which features improvements for CPU inference path on a VGG-16 based Single Shot multibox Detector (SSD) neural network. These updates, along with the training optimizations released in neon 2.5.0, show that neon is gaining significant boosts in both training and inference performance.  (Granular configuration details, as well…

Read more

#Release Notes

Dec 19, 2017   |   Itai Caspi, Gal Leibovich, Gal Novik

Reinforcement Learning Coach v0.9

Since the release of Coach a couple of months ago, we have been working hard to push it into new frontiers that will improve its usability for real world applications. In this release, we are introducing several new features that will move Coach forward in this direction. Imitation Learning First, we added several convenient tools…

Read more

#Release Notes #Technology

Nov 14, 2017   |   Wei Wang, Peng Zhang, Jayaram Bobba

neon v2.3.0: Significant Performance Boost for Deep Speech 2 and VGG models

We are excited to announce the release of neon™ 2.3.0.  It ships with significant performance improvements for Deep Speech 2 (DS2) and VGG models running on Intel® architecture (IA). For the DS2 model, our tests show up to 6.8X improvement1,4 with the  (Intel® MKL) backend over the NumPy CPU backend with neon™ 2.3.0, and more…

Read more

#Release Notes

BDW-SKX Normalized Throughput

Sep 18, 2017   |   Jayaram Bobba

neon v2.1.0: Leveraging Intel® Advanced Vector Extensions 512 (Intel® AVX-512)

We are excited to announce the availability of neon™ 2.1 framework. An optimized backend based on Intel® Math Kernel Library (Intel® MKL), is enabled by default on CPU platforms with this release. neon™ 2.1 also uses a newer version of the Intel ® MKL for Deep Neural Networks (Intel ® MKL-DNN), which features optimizations for…

Read more

#Release Notes

Jul 13, 2017   |   Scott Leishman

Introducing the Aeon Dataloader and Other Enhancements in Nervana Cloud 1.5.0

Nervana Cloud 1.5.0 contains enormous under-the-hood changes and improvements.  We’ve revamped and updated a lot of the core underlying code, separated the various application components into their own microservices, re-written our job launcher, added support for a new container orchestration service, squashed more than 75 bugs, and greatly expanded our testing coverage. The biggest changes…

Read more

#Release Notes #Technology

Jun 28, 2017   |   Jayaram Bobba

neon™ 2.0: Optimized for Intel® Architectures

neon™ is a deep learning framework created by Nervana Systems with industry leading performance on GPUs thanks to its custom assembly kernels and optimized algorithms. After Nervana joined Intel, we have been working together to bring superior performance to CPU platforms as well. Today, after the result of a great collaboration between the teams, we…

Read more

#Release Notes

Dec 29, 2016   |   Jennifer Myers

neon v1.8.0 released!

Highlights from this release include:  * Skip Thought Vectors example * Dilated convolution support * Nesterov Accelerated Gradient option to SGD optimizer * MultiMetric class to allow wrapping Metric classes * Support for serializing and deserializing encoder-decoder models * Allow specifying the number of time steps to evaluate during beam search * A new community-contributed Docker image…

Read more

#Release Notes

Nov 22, 2016   |   Jennifer Myers

neon v1.7.0 released!

Highlights from this release include:  Update Data Loader to aeon for flexible, multi-threaded data loading and transformations. More information can be found in the docs, but in brief, aeon: provides an easy interface to adapt existing models to your own, custom, datasets supports images, video and audio and is easy to extend with your own providers for custom…

Read more

#Release Notes

Sep 22, 2016   |   Jennifer Myers

neon v1.6.0 released!

Highlights from this release include:  Faster RCNN model Sequence to Sequence container and char_rae recurrent autoencoder model Reshape Layer that reshapes the input[#221] Pip requirements in requirements.txt updated to latest versions [#289] Remove deprecated data loaders and update docs Use NEON_DATA_CACHE_DIR envvar as archive dir to store DataLoader ingested data Eliminate type conversion for FP16…

Read more

#Release Notes

Jul 01, 2016   |   Jennifer Myers

neon v1.5 released!

We’re excited to release neon v1.5 with Python 2 and Python 3 support, support for Pascal GPUs (GTX 1080) and performance enhancements such as persistent RNN kernels (based on the paper by Greg Diamos at Baidu), bringing a 12x performance gain compared to v1.4.0. Highlights from this release include: Python2/Python3 compatibility [#191] Support for Pascal…

Read more

#Release Notes

Stay Connected

Get the latest from Intel AI