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Nervana’s Deep
Learning Platform
MAKING MACHINES SMARTER.™
Hanlin Tang, PhD
Algorithms Engineer
Facebook DeepMask
Silver et al, 2016
The Atlantic, March 2016
“The error rate has been cut by a factor of
two in all the languages, more than a factor of
two in many cases. That’s mostly due to deep
learning and the way we have optimized it …”
Alex Acero, Siri Senior Director, Apple
Article in Backhannel/WIRED, Aug 2016
Deep Learning
neon deep
learning
framework
train deployexplore
nervana
engine
Fastest deep learning
framework
cloudn
• Unprecedented computing power
• 10x speedup over current Maxwell
GPUs (~55 TeraOps)
• 32 GB High-Bandwidth Memory
• Six bi-directional high-bandwidth links
for 3D torus interconnect
• 8 chips in a box, seamlessly scale to
multiple chassis
https://github.com/NervanaSystems/neon
• https://github.com/NervanaSystems/ModelZoo
• Pre-trained weights and models
SegNet
Deep Speech 2
Skip-thought
Autoencoders
Deep Dream
Badrinarayanan et al., 2015
Neon (ms) Caffe (ms) Speed-up
Forward 101 719 7.1x
Backward 164 746 4.5x
Total 265 1455 5.5x
neon v1.6 + mgpu v1.6
neon v2.0
Modular dataloader (aeon)
Neural machine translation model
neon v3.0
• Nervana Graph
• Tensorflow inter-operability
• Graph-enabled models
• Distributed computing
Deep Learning at Scale
“Training neural networks is a dark art.”
Hyperparameters:
•Number and type of units/layers
•Convolution filter size
•Weight Initialization
•Optimization method
•Learning Rate schedule
Deep Learning at Scale
Command Line client Web Interface
Nervana in action
Healthcare: Tumor detection
Automotive: Speech interfaces
Finance: Time-series search
engine
Positive:
Negative:
Agricultural Robotics Oil & Gas
Positive:
Negative:
Proteomics: Sequence analysis
Query:
Results:
+ n

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