Training Time Slashed for Deep Learning

By George Leopold

August 14, 2018

Fast.ai, an organization offering free courses on deep learning, claimed a new speed record for training a popular image database using Nvidia GPUs running on public cloud infrastructure.

A pair of researchers trained the ImageNet database with 93 percent accuracy in 18 minutes using 16 Amazon Web Services cloud instances, each with eight Nvidia Tesla V100 Tensor Core GPUs. Running Fast.ai and Pytorch libraries, the researchers claimed a 40-percent boost in speed and accuracy for training ImageNet on public infrastructure. The previous record was held by Google on its Tensor Processing Unit Pod cluster.

“Our approach uses the same number of processing units as Google’s benchmark (128) and costs around $40 to run,” Fast.ai reported. The researchers said they would release their software for training and monitoring distributed models running in the AWS cloud.

The researchers included a Fast.ai alumnus and a deep learning expert with the Defense Innovation Unit Experimental (DIUx), a Pentagon startup working to transfer commercial technologies to the military.

Fast.ai developed a set of tools for cropping database images while DIUx supplied a framework called a nexus-scheduler used to orchestrate training runs and track the results. The scheduler was tuned for multi-machine training.

The researchers said they were encouraged by a recent report that AWS was able to reduce training time on the image database to 47 minutes with comparable accuracy.

The Fast.ai effort employed what they called a “new training trick.”

“A lot of people mistakenly believe that convolutional neural networks can only work with one fixed image size, and that that must be rectangular,” Fast.ai’s Jeremy Howard explained in a blog post. “However, most libraries support ‘adaptive’ or ‘global’ pooling layers, which entirely avoid this limitation.”

Howard continued: “…unless users of these libraries replace those layers, they are stuck with just one image size and shape (generally 224 by 224 pixels). The Fast.ai library automatically converts fixed-size models to dynamically sized models.”

The researchers said training started with small images that were gradually increased in size as training progressed. Early, inaccurate models quickly learned to identify more and larger images while spotting more image detail and distinctions. To accelerate training, they also used larger batch sizes during intermediate training steps to better utilize GPU memory to avoid network latency.

Among the lessons drawn from the Fast.ai experiments are the assertion that deep learning researchers do not necessarily require massive processing power to accelerate training. The researchers argued that a combination of new training techniques such as dynamically sized models along with public cloud access to GPU infrastructure on demand can help democratize deep learning and other AI development tasks.

“There’s certainly plenty of room to go faster still,” Fast.ai’s Howard said.

This story originally appeared on our sister site Datanami.

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

How the United States Invests in Supercomputing

November 14, 2018

The CORAL supercomputers Summit and Sierra are now the world's fastest computers and are already contributing to science with early applications. Ahead of SC18, Maciej Chojnowski with ICM at the University of Warsaw discussed the details of the CORAL project with Dr. Dimitri Kusnezov from the U.S. Department of Energy. Read more…

By Maciej Chojnowski

At SC18: Humanitarianism Amid Boom Times for HPC

November 14, 2018

At SC18 in Dallas, the feeling on the ground is one of forward-looking buoyancy. Like boom times that cycle through the Texas oil fields, the HPC industry is enjoying a prosperity seen only every few decades, one driven Read more…

By Doug Black

Nvidia’s Jensen Huang Delivers Vision for the New HPC

November 14, 2018

For nearly two hours on Monday at SC18, Jensen Huang, CEO of Nvidia, presented his expansive view of the future of HPC (and computing in general) as only he can do. Animated. Backstopped by a stream of data charts, produ Read more…

By John Russell

HPE Extreme Performance Solutions

AI Can Be Scary. But Choosing the Wrong Partners Can Be Mortifying!

As you continue to dive deeper into AI, you will discover it is more than just deep learning. AI is an extremely complex set of machine learning, deep learning, reinforcement, and analytics algorithms with varying compute, storage, memory, and communications needs. Read more…

IBM Accelerated Insights

From Deep Blue to Summit – 30 Years of Supercomputing Innovation

This week, in honor of the 30th anniversary of the SC conference, we are highlighting some of the most significant IBM contributions to supercomputing over the past 30 years. Read more…

New Panasas High Performance Storage Straddles Commercial-Traditional HPC

November 13, 2018

High performance storage vendor Panasas has launched a new version of its ActiveStor product line this morning featuring what the company said is the industry’s first plug-and-play, portable parallel file system that delivers up to 75 Gb/s per rack on industry standard hardware combined with “enterprise-grade reliability and manageability.” Read more…

By Doug Black

How the United States Invests in Supercomputing

November 14, 2018

The CORAL supercomputers Summit and Sierra are now the world's fastest computers and are already contributing to science with early applications. Ahead of SC18, Maciej Chojnowski with ICM at the University of Warsaw discussed the details of the CORAL project with Dr. Dimitri Kusnezov from the U.S. Department of Energy. Read more…

By Maciej Chojnowski

At SC18: Humanitarianism Amid Boom Times for HPC

November 14, 2018

At SC18 in Dallas, the feeling on the ground is one of forward-looking buoyancy. Like boom times that cycle through the Texas oil fields, the HPC industry is en Read more…

By Doug Black

Nvidia’s Jensen Huang Delivers Vision for the New HPC

November 14, 2018

For nearly two hours on Monday at SC18, Jensen Huang, CEO of Nvidia, presented his expansive view of the future of HPC (and computing in general) as only he can Read more…

By John Russell

New Panasas High Performance Storage Straddles Commercial-Traditional HPC

November 13, 2018

High performance storage vendor Panasas has launched a new version of its ActiveStor product line this morning featuring what the company said is the industry’s first plug-and-play, portable parallel file system that delivers up to 75 Gb/s per rack on industry standard hardware combined with “enterprise-grade reliability and manageability.” Read more…

By Doug Black

SC18 Student Cluster Competition – Revealing the Field

November 13, 2018

It’s November again and we’re almost ready for the kick-off of one of the greatest computer sports events in the world – the SC Student Cluster Competitio Read more…

By Dan Olds

US Leads Supercomputing with #1, #2 Systems & Petascale Arm

November 12, 2018

The 31st Supercomputing Conference (SC) - commemorating 30 years since the first Supercomputing in 1988 - kicked off in Dallas yesterday, taking over the Kay Ba Read more…

By Tiffany Trader

OpenACC Talks Up Summit and Community Momentum at SC18

November 12, 2018

OpenACC – the directives-based parallel programing model for optimizing applications on heterogeneous architectures – is showcasing user traction and HPC im Read more…

By John Russell

How ASCI Revolutionized the World of High-Performance Computing and Advanced Modeling and Simulation

November 9, 2018

The 1993 Supercomputing Conference was held in Portland, Oregon. That conference and it’s show floor provided a good snapshot of the uncertainty that U.S. supercomputing was facing in the early 1990s. Many of the companies exhibiting that year would soon be gone, either bankrupt or acquired by somebody else. Read more…

By Alex R. Larzelere

Cray Unveils Shasta, Lands NERSC-9 Contract

October 30, 2018

Cray revealed today the details of its next-gen supercomputing architecture, Shasta, selected to be the next flagship system at NERSC. We've known of the code-name "Shasta" since the Argonne slice of the CORAL project was announced in 2015 and although the details of that plan have changed considerably, Cray didn't slow down its timeline for Shasta. Read more…

By Tiffany Trader

TACC Wins Next NSF-funded Major Supercomputer

July 30, 2018

The Texas Advanced Computing Center (TACC) has won the next NSF-funded big supercomputer beating out rivals including the National Center for Supercomputing Ap Read more…

By John Russell

IBM at Hot Chips: What’s Next for Power

August 23, 2018

With processor, memory and networking technologies all racing to fill in for an ailing Moore’s law, the era of the heterogeneous datacenter is well underway, Read more…

By Tiffany Trader

Requiem for a Phi: Knights Landing Discontinued

July 25, 2018

On Monday, Intel made public its end of life strategy for the Knights Landing "KNL" Phi product set. The announcement makes official what has already been wide Read more…

By Tiffany Trader

House Passes $1.275B National Quantum Initiative

September 17, 2018

Last Thursday the U.S. House of Representatives passed the National Quantum Initiative Act (NQIA) intended to accelerate quantum computing research and developm Read more…

By John Russell

CERN Project Sees Orders-of-Magnitude Speedup with AI Approach

August 14, 2018

An award-winning effort at CERN has demonstrated potential to significantly change how the physics based modeling and simulation communities view machine learni Read more…

By Rob Farber

Summit Supercomputer is Already Making its Mark on Science

September 20, 2018

Summit, now the fastest supercomputer in the world, is quickly making its mark in science – five of the six finalists just announced for the prestigious 2018 Read more…

By John Russell

New Deep Learning Algorithm Solves Rubik’s Cube

July 25, 2018

Solving (and attempting to solve) Rubik’s Cube has delighted millions of puzzle lovers since 1974 when the cube was invented by Hungarian sculptor and archite Read more…

By John Russell

Leading Solution Providers

US Leads Supercomputing with #1, #2 Systems & Petascale Arm

November 12, 2018

The 31st Supercomputing Conference (SC) - commemorating 30 years since the first Supercomputing in 1988 - kicked off in Dallas yesterday, taking over the Kay Ba Read more…

By Tiffany Trader

TACC’s ‘Frontera’ Supercomputer Expands Horizon for Extreme-Scale Science

August 29, 2018

The National Science Foundation and the Texas Advanced Computing Center announced today that a new system, called Frontera, will overtake Stampede 2 as the fast Read more…

By Tiffany Trader

HPE No. 1, IBM Surges, in ‘Bucking Bronco’ High Performance Server Market

September 27, 2018

Riding healthy U.S. and global economies, strong demand for AI-capable hardware and other tailwind trends, the high performance computing server market jumped 28 percent in the second quarter 2018 to $3.7 billion, up from $2.9 billion for the same period last year, according to industry analyst firm Hyperion Research. Read more…

By Doug Black

Intel Announces Cooper Lake, Advances AI Strategy

August 9, 2018

Intel's chief datacenter exec Navin Shenoy kicked off the company's Data-Centric Innovation Summit Wednesday, the day-long program devoted to Intel's datacenter Read more…

By Tiffany Trader

Germany Celebrates Launch of Two Fastest Supercomputers

September 26, 2018

The new high-performance computer SuperMUC-NG at the Leibniz Supercomputing Center (LRZ) in Garching is the fastest computer in Germany and one of the fastest i Read more…

By Tiffany Trader

Houston to Field Massive, ‘Geophysically Configured’ Cloud Supercomputer

October 11, 2018

Based on some news stories out today, one might get the impression that the next system to crack number one on the Top500 would be an industrial oil and gas mon Read more…

By Tiffany Trader

Google Releases Machine Learning “What-If” Analysis Tool

September 12, 2018

Training machine learning models has long been time-consuming process. Yesterday, Google released a “What-If Tool” for probing how data point changes affect a model’s prediction. The new tool is being launched as a new feature of the open source TensorBoard web application... Read more…

By John Russell

The Convergence of Big Data and Extreme-Scale HPC

August 31, 2018

As we are heading towards extreme-scale HPC coupled with data intensive analytics like machine learning, the necessary integration of big data and HPC is a curr Read more…

By Rob Farber

  • arrow
  • Click Here for More Headlines
  • arrow
Do NOT follow this link or you will be banned from the site!
Share This