Machine Learning at HPC User Forum: Drilling into Specific Use Cases

By Arno Kolster

September 22, 2017

The 66th HPC User Forum held September 5-7, in Milwaukee, Wisconsin, at the elegant and historic Pfister Hotel, highlighting the 1893 Victorian décor and art of “The Grand Hotel Of The West,” contrasted nicely with presentations on the latest trends in modern computing – deep learning, machine learning and AI.

Over the course of two days of presentations, a couple common themes became obvious: First, that machine and deep learning are focused currently on specific rather than general use cases and second, that ML and DL need to be part of an integrated workflow to be effective.

This was exemplified by Dr. Maarten Sierhuis from Nissan Research Facility Silicon Valley with his presentation “Technologies for Making Self-Driving Vehicles the Norm.” One of the most engaging talks, Dr. Sierhuis’s multi-media presentation on the triumphs and challenges facing Nissan while developing its self-driving vehicle program showcased that machine and deep learning “drives” the autonomous vehicle revolution.

The challenge that Nissan and other deep learning practitioners face is that current deep learning algorithms are programmed to learn to do one thing extremely well – the specific use case: image recognition of stop signs for example. Once an algorithm learns to recognize stop signs, the same amount of discrete learning must apply for every other road sign a vehicle may encounter. To create a general-purpose “road sign learning algorithm”, not only do you need a massive amount of image data (in the tens of millions of varied images), but also the compute to power the learning effort.

Dr. Weng-Keen Wong from the NSF echoed much the same distinction between the specific and general case algorithm during his talk “Research in Deep Learning: A Perspective From NSF” and was also mentioned by Nvidia’s Dale Southard during the disruptive technology panel. Arno Kolster from Providentia Worldwide in his presentation “Machine and Deep Learning: Practical Deployments and Best Practices for the Next Two Years” claimed as well that general purpose learning algorithms are obviously the way to go, but are still some time out.

Nissans’s Dr. Sierhuis went on to highlight some challenges computers still face which human drivers take for granted. For example, what does an autonomous vehicle do when a road crew is blocking the road in front of it? As a human driver, we’d simply move into the opposite lane to “just go around”, but to algorithms, this breaks all the rules: Crossing a double line, checking the opposite lane for oncoming traffic, shoulder checking, ensuring no crossing pedestrians, etc. All need real-time re-programming for the encountering vehicle and other vehicles that arriving at the obstacle.

Nissan proposes an “FAA-like” control system, but the viability of such a system remains to be seen. Certainly, autonomous technologies are integrating slowly into new cars to augment human drivers but a complete self-driving vehicle won’t appear in the marketplace overnight -cars will continue to function in a hybrid mode for some time. Rest assured, many of today’s young folks likely will never learn how to drive (or ask their parents to borrow the car on Saturday night).

This algorithmic specificity spotlights the difficulty of integrating deep learning into an actual production workflow.

Tim Barr’s (Cray) “Perspectives on HPC-Enabled AI” showed how Cray’s HPC technologies can be leveraged for Machine and Deep Learning for vision, speech and language. Stating that it all starts with analytics, Mr. Barr illustrated how industries such as Daimler improve manufacturing processes and products by leveraging deep learning to curtail vehicle noise and reduce vibration in its newest vehicles. Nikunj Oza from NASA Ames gave examples of machine learning behind aviation safety and astronaut health maintenance in “NASA Perspective on Deep Learning.” Dr. Oza’s background in analytics brought a fresh perspective to the proceedings and showcased that machine learning from history has earned a real place alongside modeling for industrial best practices.

In the simulation space, a fascinating talk from the LLNL HPC4Mfg program was William Elmer’s (LLNL) discussion of Proctor & Gamble’s “Faster Turnaround for Multiscale Models of Paper Fiber Products.” Simulating various paper product textures and fibers greatly reduce the amount of energy from drying and compaction. Likewise, Shiloh Industries’ Hal Gerber described “High Pressure Casting for Structural Requirements and The Implications on Simulation.” Shiloh’s team leverages HPC for changing vehicle structure — especially in creating lighter components with composites like carbon fiber and mixed materials.

It’s clear from the discussion that machine learning and AI are set to be first class citizens alongside traditional simulation within the HPC community in short order. While still unproven and with a wide variety of new software implementations, HP Labs presented a first-of-its-kind analysis of ML benchmarking on HPC Platforms. Hewlett Packard Labs’ Natalia Vassilieva’s “Characterization and Benchmarking of Deep Learning” showcased the “Book of Recipes” HP Labs is developing with various hardware and software configurations. Fresh off their integration of SGI technology into their technology stack, the talk not only highlighted the newer software platforms which the learning systems leverage, but demonstrated that HPE’s portfolio of systems and experience in both HPC and hyper scale environments is impressive indeed.

Graham Anthony, CFO of BioVista spoke on the “Pursuit of Sustainable Healthcare Through Personalized Medicine With HPC.” Mr. Anthony was very passionate about the work BioVista is doing with HPE and how HPC and deep learning change the costs of healthcare by increased precision in treatment through deriving better insights from data. BioVista takes insight from deep learning and feeds that into simulations for better treatments – a true illustration that learning is here to stay, and works hand in hand with business process flows for traditional HPC.

In his talk entitled “Charliecloud: Containers are Good for More Than Serving Cat Pictures?” Reid Priedhorsky from LANL covered a wide range of topics including software stacks, design philosophy and demoed Charliecloud which enables execution of docker containers on supercomputers.

The tongue-in-cheek title about cat pictures being synonymous with deep learning image recognition is not by accident. Stand-alone image recognition is really cool, but as expounded upon above, the true benefit from deep learning is having an integrated workflow where data sources are ingested by a general purpose deep learning platform with outcomes that benefit business, industry and academia.

From the talks, it is also clear that Machine Learning, Deep Learning and AI are presently fueled more by industry than by academia. This could be due to strategic and competitive business drivers as well as the sheer amount of data that companies like Facebook, Baidu and Google have available to them driving AI research and deep learning-backed products. HPC might not be needed to push these disciplines forward and is likely why we see this trend becoming more prevalent in everyday news.

There was obvious concern from the audience about a future where machines rule the world. Ethical questions of companies knowingly replacing workers with robots or AI came up in a very lively discussion. Some argued that there is a place for both humans and AI — quieting the fear that tens of thousands of people would be replaced by algorithms and robots. Others see a more dismal human future with evil and malevolent robots taking control and little left for humans to do. These are, of course, difficult questions to answer and further debates will engage and entertain everyone as we keep moving toward an uncertain, technical future.

On a lighter note, Wednesday evening’s dinner featured a local volunteer docent, Dave Fehlauer, giving an enjoyable, informative talk on Captain Frederick Pabst: his family, his world and his well-known Milwaukee staple, The Pabst Brewing Company.

By all accounts, this was one of the most enjoyed HPC User Forums meetings. With a coherent theme and a dynamic range of presentations, the Forum kept everyone’s interest and showcased the realm of possibilities within this encouraging trend of computing, both from industry and academic research perspectives.

The next domestic HPC User Forum will be held April 16-18, 2018 at the Loews Ventana Canyon in Tucson, Arizona. See http://hpcuserforum.com for further information.

About the Author

Arno Kolster is Principal & Co-Founder of Providentia Worldwide, a technical consulting firm. Arno focuses on bridging enterprise and HPC architectures and was co-winner of IDC’s HPC Innovation Award with his partner Ryan Quick in 2012 and 2014. He was recipient of the Alan El Faye HPC Inspiration Award in 2016. Arno can be reached at [email protected].

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!

GTC 2019: Chief Scientist Bill Dally Provides Glimpse into Nvidia Research Engine

March 22, 2019

Amid the frenzy of GTC this week – Nvidia’s annual conference showcasing all things GPU (and now AI) – William Dally, chief scientist and SVP of research, provided a brief but insightful portrait of Nvidia’s rese Read more…

By John Russell

ORNL Helps Identify Challenges of Extremely Heterogeneous Architectures

March 21, 2019

Exponential growth in classical computing over the last two decades has produced hardware and software that support lightning-fast processing speeds, but advancements are topping out as computing architectures reach thei Read more…

By Laurie Varma

Interview with 2019 Person to Watch Jim Keller

March 21, 2019

On the heels of Intel's reaffirmation that it will deliver the first U.S. exascale computer in 2021, which will feature the company's new Intel Xe architecture, we bring you our interview with our 2019 Person to Watch Jim Keller, head of the Silicon Engineering Group at Intel. Read more…

By HPCwire Editorial Team

HPE Extreme Performance Solutions

HPE and Intel® Omni-Path Architecture: How to Power a Cloud

Learn how HPE and Intel® Omni-Path Architecture provide critical infrastructure for leading Nordic HPC provider’s HPCFLOW cloud service.

powercloud_blog.jpgFor decades, HPE has been at the forefront of high-performance computing, and we’ve powered some of the fastest and most robust supercomputers in the world. Read more…

IBM Accelerated Insights

Insurance: Where’s the Risk?

Insurers are facing extreme competitive challenges in their core businesses. Property and Casualty (P&C) and Life and Health (L&H) firms alike are highly impacted by the ongoing globalization, increasing regulation, and digital transformation of their client bases. Read more…

What’s New in HPC Research: TensorFlow, Buddy Compression, Intel Optane & More

March 20, 2019

In this bimonthly feature, HPCwire highlights newly published research in the high-performance computing community and related domains. From parallel programming to exascale to quantum computing, the details are here. Read more…

By Oliver Peckham

GTC 2019: Chief Scientist Bill Dally Provides Glimpse into Nvidia Research Engine

March 22, 2019

Amid the frenzy of GTC this week – Nvidia’s annual conference showcasing all things GPU (and now AI) – William Dally, chief scientist and SVP of research, Read more…

By John Russell

At GTC: Nvidia Expands Scope of Its AI and Datacenter Ecosystem

March 19, 2019

In the high-stakes race to provide the AI life-cycle solution of choice, three of the biggest horses in the field are IBM, Intel and Nvidia. While the latter is only a fraction of the size of its two bigger rivals, and has been in business for only a fraction of the time, Nvidia continues to impress with an expanding array of new GPU-based hardware, software, robotics, partnerships and... Read more…

By Doug Black

Nvidia Debuts Clara AI Toolkit with Pre-Trained Models for Radiology Use

March 19, 2019

AI’s push into healthcare got a boost yesterday with Nvidia’s release of the Clara Deploy AI toolkit which includes 13 pre-trained models for use in radiolo Read more…

By John Russell

It’s Official: Aurora on Track to Be First US Exascale Computer in 2021

March 18, 2019

The U.S. Department of Energy along with Intel and Cray confirmed today that an Intel/Cray supercomputer, "Aurora," capable of sustained performance of one exaf Read more…

By Tiffany Trader

Why Nvidia Bought Mellanox: ‘Future Datacenters Will Be…Like High Performance Computers’

March 14, 2019

“Future datacenters of all kinds will be built like high performance computers,” said Nvidia CEO Jensen Huang during a phone briefing on Monday after Nvidia revealed scooping up the high performance networking company Mellanox for $6.9 billion. Read more…

By Tiffany Trader

Oil and Gas Supercloud Clears Out Remaining Knights Landing Inventory: All 38,000 Wafers

March 13, 2019

The McCloud HPC service being built by Australia’s DownUnder GeoSolutions (DUG) outside Houston is set to become the largest oil and gas cloud in the world th Read more…

By Tiffany Trader

Quick Take: Trump’s 2020 Budget Spares DoE-funded HPC but Slams NSF and NIH

March 12, 2019

U.S. President Donald Trump’s 2020 budget request, released yesterday, proposes deep cuts in many science programs but seems to spare HPC funding by the Depar Read more…

By John Russell

Nvidia Wins Mellanox Stakes for $6.9 Billion

March 11, 2019

The long-rumored acquisition of Mellanox came to fruition this morning with GPU chipmaker Nvidia’s announcement that it has purchased the high-performance net Read more…

By Doug Black

Quantum Computing Will Never Work

November 27, 2018

Amid the gush of money and enthusiastic predictions being thrown at quantum computing comes a proposed cold shower in the form of an essay by physicist Mikhail Read more…

By John Russell

The Case Against ‘The Case Against Quantum Computing’

January 9, 2019

It’s not easy to be a physicist. Richard Feynman (basically the Jimi Hendrix of physicists) once said: “The first principle is that you must not fool yourse Read more…

By Ben Criger

ClusterVision in Bankruptcy, Fate Uncertain

February 13, 2019

ClusterVision, European HPC specialists that have built and installed over 20 Top500-ranked systems in their nearly 17-year history, appear to be in the midst o Read more…

By Tiffany Trader

Why Nvidia Bought Mellanox: ‘Future Datacenters Will Be…Like High Performance Computers’

March 14, 2019

“Future datacenters of all kinds will be built like high performance computers,” said Nvidia CEO Jensen Huang during a phone briefing on Monday after Nvidia revealed scooping up the high performance networking company Mellanox for $6.9 billion. Read more…

By Tiffany Trader

Intel Reportedly in $6B Bid for Mellanox

January 30, 2019

The latest rumors and reports around an acquisition of Mellanox focus on Intel, which has reportedly offered a $6 billion bid for the high performance interconn Read more…

By Doug Black

Looking for Light Reading? NSF-backed ‘Comic Books’ Tackle Quantum Computing

January 28, 2019

Still baffled by quantum computing? How about turning to comic books (graphic novels for the well-read among you) for some clarity and a little humor on QC. The Read more…

By John Russell

Contract Signed for New Finnish Supercomputer

December 13, 2018

After the official contract signing yesterday, configuration details were made public for the new BullSequana system that the Finnish IT Center for Science (CSC Read more…

By Tiffany Trader

It’s Official: Aurora on Track to Be First US Exascale Computer in 2021

March 18, 2019

The U.S. Department of Energy along with Intel and Cray confirmed today that an Intel/Cray supercomputer, "Aurora," capable of sustained performance of one exaf Read more…

By Tiffany Trader

Leading Solution Providers

SC 18 Virtual Booth Video Tour

Advania @ SC18 AMD @ SC18
ASRock Rack @ SC18
DDN Storage @ SC18
HPE @ SC18
IBM @ SC18
Lenovo @ SC18 Mellanox Technologies @ SC18
NVIDIA @ SC18
One Stop Systems @ SC18
Oracle @ SC18 Panasas @ SC18
Supermicro @ SC18 SUSE @ SC18 TYAN @ SC18
Verne Global @ SC18

Deep500: ETH Researchers Introduce New Deep Learning Benchmark for HPC

February 5, 2019

ETH researchers have developed a new deep learning benchmarking environment – Deep500 – they say is “the first distributed and reproducible benchmarking s Read more…

By John Russell

IBM Quantum Update: Q System One Launch, New Collaborators, and QC Center Plans

January 10, 2019

IBM made three significant quantum computing announcements at CES this week. One was introduction of IBM Q System One; it’s really the integration of IBM’s Read more…

By John Russell

IBM Bets $2B Seeking 1000X AI Hardware Performance Boost

February 7, 2019

For now, AI systems are mostly machine learning-based and “narrow” – powerful as they are by today's standards, they're limited to performing a few, narro Read more…

By Doug Black

The Deep500 – Researchers Tackle an HPC Benchmark for Deep Learning

January 7, 2019

How do you know if an HPC system, particularly a larger-scale system, is well-suited for deep learning workloads? Today, that’s not an easy question to answer Read more…

By John Russell

HPC Reflections and (Mostly Hopeful) Predictions

December 19, 2018

So much ‘spaghetti’ gets tossed on walls by the technology community (vendors and researchers) to see what sticks that it is often difficult to peer through Read more…

By John Russell

Arm Unveils Neoverse N1 Platform with up to 128-Cores

February 20, 2019

Following on its Neoverse roadmap announcement last October, Arm today revealed its next-gen Neoverse microarchitecture with compute and throughput-optimized si Read more…

By Tiffany Trader

Move Over Lustre & Spectrum Scale – Here Comes BeeGFS?

November 26, 2018

Is BeeGFS – the parallel file system with European roots – on a path to compete with Lustre and Spectrum Scale worldwide in HPC environments? Frank Herold Read more…

By John Russell

France to Deploy AI-Focused Supercomputer: Jean Zay

January 22, 2019

HPE announced today that it won the contract to build a supercomputer that will drive France’s AI and HPC efforts. The computer will be part of GENCI, the Fre Read more…

By Tiffany Trader

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