NSF-NCSA Study Probes Relationship between Industrial Applications and Underlying Science

By Steve Conway

October 3, 2012

NSF and NCSA recently commissioned a study to see whether improvements in the science inside applications and other factors could help industrial HPC users. Merle Giles, director of NCSA’s Private Sector Program, discusses the findings with HPCwire.

HPCwire: What was the goal of the study?

Merle Giles: The main goal was to better understand the root causes that limit the realism and performance of today’s HPC applications and to solicit ideas for improving the applications’ performance and realism for industrial users.

HPCwire: Why is HPC use in industry important to NCSA and NSF?

Giles: Engineering and scientific research problems have a lot in common. They can be equally complex and are based on the same underlying science, so advances in science can often be leveraged across both domains for greater benefit to society. Industrial engineering has a special value because it can function as a living laboratory for applying new science and getting feedback under the tight time constraints of the product design window.

HPCwire: How are NSF and NCSA involved in helping industrial HPC users?

Giles: NSF and NCSA are heavily involved in supporting engineering as well as science. NSF’s XSEDE program stands for Extreme Science and Engineering Discovery Environment. It’s a five-year, $121 million initiative to support scientific and industrial researchers across the world with, quote, “the most advanced, powerful, and robust collection of integrated advanced digital resources and services in the world.”

NCSA is the lead institution in this partnership, which involves more than a dozen major universities plus other organizations. In addition, NCSA formed the Private Sector Program that I’m in charge of, so we could make our HPC resources and the best research minds at the University of Illinois available to industry.

HPCwire: What prompted the new study?

Giles: Industrial users were telling us they needed better simulation-based science and engineering. They said the performance of some of their key applications in HPC environments was stuck and they needed better solutions so they could develop higher-quality, more competitive products in shorter timeframes. Industry has a time scale for innovation that the academic world often doesn’t. We need both ends of this time scale.

Scientific researchers may need years or decades to advance the frontiers of knowledge in their fields. The industrial community, on the other hand, is driven by more immediate competitive pressures to build higher-quality products sooner. So, this study was prompted by industry’s urgent need to know what is limiting the performance and realism of their simulations and what can be done to address the limitations.

HPCwire: Can you give me an example of an industrial user facing limitations?

Giles: Sure. One auto company said they’ve been pushing up against the limits of single-domain CFD and now need multi-domain simulations. We felt we owed it to users like this to document what’s limiting the realism. We’ve learned a lot in this process.

Collaboration with academia will be crucial for advancing the applications. In many cases, the academics know how to do this but industry doesn’t necessarily. There’s a clear need for academia and industry to work together to address these limitations, and that will help both camps because academic scientists and industrial scientists have many of the same issues.

HPCwire: Who conducted the new study and what methodology did they use?

Giles: We hired IDC to carry it out. They conducted extensive interviews in person and in writing. They also organized a focus group to probe some of the issues more deeply.

HPCwire: For those that aren’t getting the HPC performance they need today, did the study show how are they dealing with this inadequacy?

Giles: Yes. 30 percent of the organizations named specific ways in which they now have to dumb down their problems to complete the runs in reasonable amounts of time. The most popular strategies are using coarser meshes, employing fewer elements, not fully exploiting the known science, and employing fewer time steps or reducing the length of the investigated timeframe.

Industry uses HPC to test to a spec, but they don’t have enough time to test to see where the point of failure is. They dumb the problem down to validate the spec. But without testing to failure, they can’t see how much a product may be over-engineered. Over-engineering can cost a lot of money and reduce product efficiency and competitiveness. Advances in the HPC simulations could let them test to failure within the design window.

HPCwire: Who was interviewed?

Giles: We started earlier on with NCSA partners and IDC expanded from that base. Of the surveyed organizations, 17 percent were in government, 7 percent were academic, and the large majority of 76 percent came from industry or from organizations closely allied with industry.

The organizations ranged from a small business with 22 employees to one with 164,000 people. Revenue ranged from $240 million to $129 billion, and profits varied from $15 million to $5 billion. R&D investments ranged from $515 million to $5 billion. On average, the responding companies invested about 6.5 times more in R&D, as a percentage of their revenue, than all U.S. companies did as a group.

HPCwire: What do you think were the most important findings?

Giles: It haunts me that only about one in six organizations said that their applications as now written would meet their requirements for the next five years. As I said earlier, 30 percent said they have to dumb down their problems today. Another important finding is that users are okay with today’s HPC systems but many need retraining for next-generation systems. It will take more hands-on training and education to move industry forward.

HPCwire: What was the most surprising finding?

Giles: The similarity of responses regardless of company size. There’s a mistaken impression that the small and medium-sized companies have fewer challenges. The study confirmed that companies of all sizes need to reduce uncertainty. This is often due to the limitations of the science embedded into the applications today. To increase their confidence levels, they need more HPC capacity and capability.

HPCwire: You asked the surveyed organizations what they could do with unlimited computing power applicable to their problems. What did they say?

Giles: Some organizations provided very specific examples. An aerospace company said they could simulate the complete turbine assembly of a jet engine or optimize an entire new engine design. A life sciences firm would be able to predict the function of an ensemble of living things in a sample of soil based entirely on the DNA sequences found in that soil sample. That’s called metagenomics. A manufacturer said they could gain knowledge faster and sooner in the product development cycle, and ultimately be able to design by analysis and validate the designs prior to first build and use first build to further validate the simulation model.

HPCwire: Did they give you a wish list of high-priority things they needed?

Giles: Yes. We asked about improvements that could be accomplished in one to two years. Most of these near-term improvements fell into a few categories. These included higher-resolution meshes, improved mathematical models and algorithms, improvements to the underlying physics, and better methods for data integration and analysis.

Another frequent desire is to be able to do multi-disciplinary, multi-scale simulations. Large-scale data integration is related to this challenge and is also on the wish list. In fact, multi-disciplinary, multi-scale simulations would be helped by every other item on the wish list.

HPCwire: If they got the items on their wish list, what difference could it make?

Giles: The wish list is needed to exploit the science we already know today. A large majority of the respondents believe that today’s known science could support a moderate or a large amount of additional realism in the applications. More than a third of the respondents said that taking the next step, advancing the known science, could add even more realism to their key applications.

HPCwire: Could NSF and NCSA play a role in advancing applications capabilities for industrial organizations? Would industry want to work with you on this?

Giles: About two-thirds of the organizations said yes to having NCSA and/or NSF heavily involved in the process of advancing their important applications. The respondents were saying that we have really good tools out there and today’s science is good, but NCSA and NSF can help the user community to exploit the tools better and to advance the science and the models underlying the applications.

This confirms what we’ve been hearing separately from this study. Companies are looking for expert organizations like NSF and NCSA to play a more consultative role in helping them to use advanced science and engineering tools. More than one-third of Fortune 50 companies have chosen to work with NCSA’s Private Sector Program.

HPCwire: Is this study publicly available?

Giles: It will be publicly available in a few months.

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!

Glimpses of Today’s Total Solar Eclipse

August 21, 2017

Here are a few arresting images posted by NASA of today’s total solar eclipse. Such astronomical events have always captured our imagination and it’s not hard to understand why such occurrences were often greeted wit Read more…

By John Russell

Tech Giants Outline Battle Plans for Future HPC Market

August 21, 2017

Four companies engaged in a cage fight for leadership in the emerging HPC market of the 2020s are, despite deep differences in some areas, in violent agreement on at least one thing: the power consumption and latency pen Read more…

By Doug Black

Geospatial Data Research Leverages GPUs

August 17, 2017

MapD Technologies, the GPU-accelerated database specialist, said it is working with university researchers on leveraging graphics processors to advance geospatial analytics. The San Francisco-based company is collabor Read more…

By George Leopold

HPE Extreme Performance Solutions

Leveraging Deep Learning for Fraud Detection

Advancements in computing technologies and the expanding use of e-commerce platforms have dramatically increased the risk of fraud for financial services companies and their customers. Read more…

Intel, NERSC and University Partners Launch New Big Data Center

August 17, 2017

A collaboration between the Department of Energy’s National Energy Research Scientific Computing Center (NERSC), Intel and five Intel Parallel Computing Centers (IPCCs) has resulted in a new Big Data Center (BDC) that Read more…

By Linda Barney

Tech Giants Outline Battle Plans for Future HPC Market

August 21, 2017

Four companies engaged in a cage fight for leadership in the emerging HPC market of the 2020s are, despite deep differences in some areas, in violent agreement Read more…

By Doug Black

Microsoft Bolsters Azure With Cloud HPC Deal

August 15, 2017

Microsoft has acquired cloud computing software vendor Cycle Computing in a move designed to bring orchestration tools along with high-end computing access capabilities to the cloud. Terms of the acquisition were not disclosed. Read more…

By George Leopold

HPE Ships Supercomputer to Space Station, Final Destination Mars

August 14, 2017

With a manned mission to Mars on the horizon, the demand for space-based supercomputing is at hand. Today HPE and NASA sent the first off-the-shelf HPC system i Read more…

By Tiffany Trader

AMD EPYC Video Takes Aim at Intel’s Broadwell

August 14, 2017

Let the benchmarking begin. Last week, AMD posted a YouTube video in which one of its EPYC-based systems outperformed a ‘comparable’ Intel Broadwell-based s Read more…

By John Russell

Deep Learning Thrives in Cancer Moonshot

August 8, 2017

The U.S. War on Cancer, certainly a worthy cause, is a collection of programs stretching back more than 40 years and abiding under many banners. The latest is t Read more…

By John Russell

IBM Raises the Bar for Distributed Deep Learning

August 8, 2017

IBM is announcing today an enhancement to its PowerAI software platform aimed at facilitating the practical scaling of AI models on today’s fastest GPUs. Scal Read more…

By Tiffany Trader

IBM Storage Breakthrough Paves Way for 330TB Tape Cartridges

August 3, 2017

IBM announced yesterday a new record for magnetic tape storage that it says will keep tape storage density on a Moore's law-like path far into the next decade. Read more…

By Tiffany Trader

AMD Stuffs a Petaflops of Machine Intelligence into 20-Node Rack

August 1, 2017

With its Radeon “Vega” Instinct datacenter GPUs and EPYC “Naples” server chips entering the market this summer, AMD has positioned itself for a two-head Read more…

By Tiffany Trader

How ‘Knights Mill’ Gets Its Deep Learning Flops

June 22, 2017

Intel, the subject of much speculation regarding the delayed, rewritten or potentially canceled “Aurora” contract (the Argonne Lab part of the CORAL “ Read more…

By Tiffany Trader

Nvidia’s Mammoth Volta GPU Aims High for AI, HPC

May 10, 2017

At Nvidia's GPU Technology Conference (GTC17) in San Jose, Calif., this morning, CEO Jensen Huang announced the company's much-anticipated Volta architecture a Read more…

By Tiffany Trader

Reinders: “AVX-512 May Be a Hidden Gem” in Intel Xeon Scalable Processors

June 29, 2017

Imagine if we could use vector processing on something other than just floating point problems.  Today, GPUs and CPUs work tirelessly to accelerate algorithms Read more…

By James Reinders

Russian Researchers Claim First Quantum-Safe Blockchain

May 25, 2017

The Russian Quantum Center today announced it has overcome the threat of quantum cryptography by creating the first quantum-safe blockchain, securing cryptocurrencies like Bitcoin, along with classified government communications and other sensitive digital transfers. Read more…

By Doug Black

Quantum Bits: D-Wave and VW; Google Quantum Lab; IBM Expands Access

March 21, 2017

For a technology that’s usually characterized as far off and in a distant galaxy, quantum computing has been steadily picking up steam. Just how close real-wo Read more…

By John Russell

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Nvidia highlights strengths of its newest GPU silicon in response to Google's report on the performance and energy advantages of its custom tensor processor. Read more…

By Tiffany Trader

Groq This: New AI Chips to Give GPUs a Run for Deep Learning Money

April 24, 2017

CPUs and GPUs, move over. Thanks to recent revelations surrounding Google’s new Tensor Processing Unit (TPU), the computing world appears to be on the cusp of Read more…

By Alex Woodie

HPC Compiler Company PathScale Seeks Life Raft

March 23, 2017

HPCwire has learned that HPC compiler company PathScale has fallen on difficult times and is asking the community for help or actively seeking a buyer for its a Read more…

By Tiffany Trader

Leading Solution Providers

Trump Budget Targets NIH, DOE, and EPA; No Mention of NSF

March 16, 2017

President Trump’s proposed U.S. fiscal 2018 budget issued today sharply cuts science spending while bolstering military spending as he promised during the cam Read more…

By John Russell

Google Debuts TPU v2 and will Add to Google Cloud

May 25, 2017

Not long after stirring attention in the deep learning/AI community by revealing the details of its Tensor Processing Unit (TPU), Google last week announced the Read more…

By John Russell

CPU-based Visualization Positions for Exascale Supercomputing

March 16, 2017

In this contributed perspective piece, Intel’s Jim Jeffers makes the case that CPU-based visualization is now widely adopted and as such is no longer a contrarian view, but is rather an exascale requirement. Read more…

By Jim Jeffers, Principal Engineer and Engineering Leader, Intel

Six Exascale PathForward Vendors Selected; DoE Providing $258M

June 15, 2017

The much-anticipated PathForward awards for hardware R&D in support of the Exascale Computing Project were announced today with six vendors selected – AMD Read more…

By John Russell

Top500 Results: Latest List Trends and What’s in Store

June 19, 2017

Greetings from Frankfurt and the 2017 International Supercomputing Conference where the latest Top500 list has just been revealed. Although there were no major Read more…

By Tiffany Trader

IBM Clears Path to 5nm with Silicon Nanosheets

June 5, 2017

Two years since announcing the industry’s first 7nm node test chip, IBM and its research alliance partners GlobalFoundries and Samsung have developed a proces Read more…

By Tiffany Trader

Messina Update: The US Path to Exascale in 16 Slides

April 26, 2017

Paul Messina, director of the U.S. Exascale Computing Project, provided a wide-ranging review of ECP’s evolving plans last week at the HPC User Forum. Read more…

By John Russell

Graphcore Readies Launch of 16nm Colossus-IPU Chip

July 20, 2017

A second $30 million funding round for U.K. AI chip developer Graphcore sets up the company to go to market with its “intelligent processing unit” (IPU) in Read more…

By Tiffany Trader

  • arrow
  • Click Here for More Headlines
  • arrow
Share This