Friday, October 19, 2018
Search
  
Submit your own News for
inclusion in our Site.
Click here...
Breaking News
Micron Wants to Buy Remaining Interest in IM Flash Technologies to Advance the 3D XPoint Technology
YouTube to Sell Concert Tickets Through Music Videos
Apple Expected to Unveil New iPad and MacBook on October 30
Pioneer's New In-Ear Headphones Combine Styling With Sound Quality
Samsung Debuts the Galaxy Book2, an always on, always connected 2-in-1 PC With Snapdragon 850
Sony Releases the World's First 4-layer 128GB BD-R XL Disc
SoundCloud to Offer Access to Music Directly Through the DJ Software
Western Digital Releases New 3D NAND UFS Embedded Flash Drive For Connected Cars
Active Discussions
Which of these DVD media are the best, most durable?
How to back up a PS2 DL game
Copy a protected DVD?
roxio issues with xp pro
Help make DVDInfoPro better with dvdinfomantis!!!
menu making
Optiarc AD-7260S review
cdrw trouble
 Home > News > General Computing > Intel O...
Last 7 Days News : SU MO TU WE TH FR SA All News

Thursday, April 19, 2018
Intel Open Sources the nGraph Compiler for Deep Learning Systems


Intel's nGraph Compiler, a framework-neutral deep neural network (DNN) model compiler, is now open source, allowing support for multiple deep learning frameworks while optimizing models for multiple hardware solutions.

"Finding the right technology for AI solutions can be daunting for companies, and it's our goal to make it as easy as possible. With the nGraph Compiler, data scientists can create deep learning models without having to think about how that model needs to be adjusted across different frameworks, and its open source nature means getting access to the tools they need, quickly and easily," said Arjun Bansal, VP, AI Software, Intel.

With nGraph, data scientists can focus on data science rather than worrying about how to adapt their DNN models to train and run efficiently on different devices.

Currently, the nGraph Compiler supports three deep learning compute devices and six third-party deep learning frameworks: TensorFlow, MXNet, neon, PyTorch, CNTK and Caffe2. Users can run these frameworks on several devices: Intel Architecture (x86, Intel Xeon and Xeon Phi), GPU (NVIDIA cuDNN), and Intel Nervana Neural Network Processor (NNP).

When Deep Learning (DL) frameworks first emerged as the vehicle for running training and inference models, they were designed around kernels optimized for a particular device. As a result, many device details were being exposed in the model definitions, complicating the adaptability and portability of DL models to other, or more advanced, devices.

The traditional approach means that an algorithm developer faces tediousness in taking their model to an upgraded device. Enabling a model to run on a different framework is also problematic because the developer must separate the essence of the model from the performance adjustments made for the device, translate to similar ops in the new framework, and finally make the necessary changes for the preferred device configuration on the new framework.

Intel designed the nGraph library to reduce these kinds of engineering complexities. While optimized kernels for DL primitives are provided through the project and via libraries like Intel Math Kernel Library for Deep Neural Networks (Intel MKL-DNN), there are also several compiler-inspired ways in which performance can be further optimized.


Previous
Next
Garmin Announces Connect IQ 3.0 with New apps from Trailforks, Yelp, iHeartRadio        All News        Facebook Seeking to Hire Chip Designers
SpaceX Successfully Launches NASA's TESS Spacecraft     General Computing News      Facebook Seeking to Hire Chip Designers

Get RSS feed Easy Print E-Mail this Message

Related News
Micron Wants to Buy Remaining Interest in IM Flash Technologies to Advance the 3D XPoint Technology
Samsung to Acquire Zhilabs to Expand AI-Based Automation Portfolio
ARM and Intel to Secure Internet of Things
Intel Further Reduces Stake in EUV Equipment Maker ASML
Micron Announces New $100 Million Venture Investment in AI
New Intel Vision Accelerator Solutions Speed Up Deep Learning and Artificial Intelligence on Edge Devices
Huawei Unveils AI Strategy and New Chips
Intel Announces 9th-Gen Core Processors, Updated Core X chips and a new 28 Core Xeon Processor
ASRock Launches Intel Z390 Motherboards
Intel to Add $1 Billion to Capital Equipment Budget, Says 10nm is On Track for 2019
Microsoft's Mobile Phone Keyboard SwiftKey Translates As You Text
Intel Adds to Portfolio of FPGA Programmable Acceleration Cards

Most Popular News
 
Home | News | All News | Reviews | Articles | Guides | Download | Expert Area | Forum | Site Info
Site best viewed at 1024x768+ - CDRINFO.COM 1998-2018 - All rights reserved -
Privacy policy - Contact Us .