Baidu Research Announces Next Generation Open Source Deep Learning Benchmark Tool
June 28 2017 - 9:00AM
Baidu Research, a division of Baidu Inc. (NASDAQ:BIDU), today
unveiled the next generation of DeepBench, the open source deep
learning benchmark that now includes measurement for inference. The
announcement was made at the O’Reilly AI Conference in New
York.
A photo accompanying this announcement is available at
http://www.globenewswire.com/NewsRoom/AttachmentNg/84bc287f-7afb-4c16-a380-d33356551343
In September of 2016, Baidu released the initial version of
DeepBench, which became the first tool to be opened up to the wider
deep learning community to evaluate how different processors
perform when they are used to train deep neural networks. Since its
initial release, several companies have used and contributed to the
DeepBench platform, including Intel, Nvidia, and AMD.
Following positive feedback from peers across the AI industry
and academia, Baidu Research has now incorporated requests to
include the measurement of deep learning inference, in addition to
training, across different hardware platforms. Inference involves
using a previously trained model to make predictions on a new data
set.
“Measuring inference is critical,” said Dr. Greg Diamos, Senior
Researcher at Baidu Research Silicon Valley AI Lab. “It covers the
operations needed to run neural networks on a device, be it in the
cloud, on a phone or a wearable. A better understanding of
performance of inference means better chips and neural networks in
real products.”
Benchmarking inference is a challenging problem. Many
applications that have been enabled by deep learning each have
their own unique performance characteristics and requirements. In
addition, there are several different deployment platforms.
DeepBench attempts to solve this problem by benchmarking
fundamental operations required for inference. “Speed is key to
training neural networks, and the first step to improving speed is
having an accurate measurement of performance,” said Sharan Narang,
Systems Researcher at Baidu Research Silicon Valley AI Lab. “With
the addition of the ability to measure inference, researchers will
now have a more comprehensive benchmark for the performance of
their AI hardware.”
In addition to measuring inference performance, DeepBench
provides new kernels for training from several different deep
learning models. It also sets new minimum precision requirements
for training. Based on a study conducted by Baidu Research,
DeepBench establishes 16 bit floating point for multiplication and
32 bit floating point for addition for training operations. It also
establishes 8 bit fixed point for multiplication and 32 bit fixed
point for addition.
DeepBench also provides results for training and inference
across a variety of processors. Baidu Research has collected
results for server deployment as well as mobile deployment
platforms such as the iPhone. For more information on DeepBench,
please visit https://svail.github.io/DeepBench-update/
About BaiduBaidu, Inc. is the leading Chinese
language Internet search provider. Baidu aims to make a complicated
world simpler for users and enterprises through technology. Baidu's
ADSs trade on the NASDAQ Global Select Market under the symbol
"BIDU". Currently, ten ADSs represent one Class A ordinary
share.
Media contact
Baidu International Communications:
Intlcomm@baidu.com
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