The HPC Gap in US Manufacturing

By Michael Feldman

February 24, 2011

Using high performance computing to help modernize US manufacturing is one of those good ideas that seems inevitable but always just out of reach. A recent study confirms this, and provides a framework for strengthening the HPC landscape in this sector.

Of course some might ask what’s the point of trying to boost manufacturing in the US when the sector only employs about 10 percent of the workforce, a figure that is projected to decline further in the coming years. Also, the use of HPC to make manufacturing more efficient is not likely help the downward employment trend. Employing virtual product design and development and automating other manufacturing processes will probably eliminate more jobs than it creates.

By world standards, the US manufacturing market is already fairly efficient. Despite the relatively few workers employed in the segment, because of its sheer size, US manufacturing dominates world production. Output in 2009 was $2.15 trillion (expressed in 2005 dollars), besting China’s contribution of $1.48 trillion and representing about 20 percent of the world’s manufacturing output.

But the real value of the US manufacturing sector is that it’s at the heart of much of the science and engineering innovation on which the remainder of the economy rests. Today US manufacturers employ more than a third of the country’s engineers and account for 60 percent of all private sector R&D. As such, it creates products that are used by the more lucrative service industries. Think, for example, of all the myriad services that are dependent on the production of computer chips and other electronic devices. Manufacturing, like agriculture before it, is a foundational activity that acts as a catalyst to other business sectors.

Furthermore, according to a recent article in The Atlantic, there is no realistic way to balance US foreign trade that relies exclusively on the service sector. Nor is there a feasible way to employ existing (and future) blue-collar workers without a healthy manufacturing sector.

And healthy it is not — at least from a global perspective. Based on a survey of CEOs conducted by Deloitte and the Council on Competitiveness released in June 2010, the US is ranked fourth in manufacturing competitiveness, behind China, India, and South Korea, and is expected to drop to fifth place, behind Brazil, by 2015. A National Institute of Standards and Technology factsheet recounts the need for the industry to focus on developing technologically-advanced products that can compete in the global marketplace. “There is widespread agreement that rather than engage in a ‘race to the bottom’ for low-wage production facilities, the United States should aim for high-value-added manufacturing opportunities,” says the factsheet.

Moving up the manufacturing foodchain often leads to a much better bottom line, and in some cases, extra jobs. For example, Frank van Mierlo, CEO of 1366 Technologies, claims that the US is in a good position to build a silicon chip industry for solar cells. According to Mierlo, the nation produces around 40 percent of the world’s high grade silicon for both chips and solar cells, which is worth about $1.7 billion. He says if US-based companies turned that silicon into wafers, it would become a $7 billion business and add 50,000 jobs.

That kind of thinking is being embraced by non-profit groups as well. US government agencies, the Council on Competitiveness, and the National Center for Manufacturing Sciences (NCMS) are all big proponents of high-tech solutions. HPC, in particular, is seen as a key driver in upgrading the nation’s manufacturing capabilities. The use of such technology allows engineers and designers to perform prototyping, product design and analysis, product lifecycle management, and product optimization/validation, with much less reliance on physical mockups and testing.

But despite better access to HPC than is generally available in other countries, in the US fewer than 10 percent of manufacturers use this technology — that according to a recent study conducted by InterSect360 Research in conjunction with NCMS. The report surveyed 323 respondents across industry, academic, government and trade organizations in July 2010 to gather a snapshot of digital manufacturing practices and attitudes in the US.

Source: http://www.nas.nasa.gov/SC08/HPT.htmlNot surprisingly it found that top manufacturers were already major users of high performance computing. Based on the survey, 61 percent of companies with over 10,000 employees are using HPC today to model everything from engine parts to product packaging. The numerous case studies of digitally-engineered products at companies like Boeing, Procter & Gamble, and General Motors attest to the acceptance of HPC at these large firms.

Meanwhile, small manufacturers, which by number represent the vast majority of the companies in this sector, have barely touched the surface of high performance computing. Here only 8 percent of businesses with under 100 employees are using such technology. Where modeling and simulation tools are being employed, they’re mostly restricted to desktop systems, representing a sort of poor man’s HPC.

The study found the most significant barriers to adoption were the lack of internal expertise, the cost of software, and to a lesser extent, the cost of hardware. To some degree, though, cost concerns may be a misconception. Over 80 percent of companies that currently use HPC report they spent less than one-third of their IT budgets on HPC — not an insignificant amount, but not an overwhelming expense either.

Importantly, 72 percent of desktop-bound CAE users did see a competitive advantage in adopting more advanced computational technology. In such environments, long simulation times and other software issues (compatibility, robustness, data management) were cited as major limitations.

When asked about the importance of different business drivers — production efficiency, time to market, product novelty, product quality, industry leadership, etc. — the survey takers said all were important, but it was product quality that garnered the most intense response. Since HPC enables iterative product refinement in a virtual design and test environment, that could turn out to be a big selling point for the technology.

In manufacturing, as in most verticals, smaller companies tend to be at a disadvantage when it comes to adopting HPC, and this is certainly reflected by the InterSect360 study. But costs, at least of hardware, are coming down. And software costs, while more worrisome, would likely be no more expensive (or at least not substantially more) on an eight-node cluster than on eight standalone workstations.

What most of these manufacturers require is a low-risk path that allows them to segue into high performance computing. Whether that turns out to be partnerships with HPC-savvy organizations, system vendors who can understand and cater to low-end HPC users, or something else remains to be seen. What seems much more certain is the need for manufacturers in the US to be able to compete at the high end of the market with superior quality products. To do that, companies will need to accept HPC as a foundational technology for their businesses.

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!

Dell EMC will Build OzStar – Swinburne’s New Supercomputer to Study Gravity

August 16, 2017

Dell EMC announced yesterday it is building a new supercomputer – the OzStar – for the Swinburne University of Technology (Australia) in support the ARC Centre of Excellence for Gravitational Wave Discovery (OzGrav) Read more…

By John Russell

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 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 into space aboard the SpaceX Dragon Spacecraft to explore if Read more…

By Tiffany Trader

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…

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 system on the STREAM benchmark and on a test case running ANS Read more…

By John Russell

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 capa 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

Cray Moves to Acquire the Seagate ClusterStor Line

July 28, 2017

This week Cray announced that it is picking up Seagate's ClusterStor HPC storage array business for an undisclosed sum. "In short we're effectively transitioning the bulk of the ClusterStor product line to Cray," said CEO Peter Ungaro. 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

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 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

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

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

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

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

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

Leading Solution Providers

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

Facebook Open Sources Caffe2; Nvidia, Intel Rush to Optimize

April 18, 2017

From its F8 developer conference in San Jose, Calif., today, Facebook announced Caffe2, a new open-source, cross-platform framework for deep learning. Caffe2 is the successor to Caffe, the deep learning framework developed by Berkeley AI Research and community contributors. 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

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

MIT Mathematician Spins Up 220,000-Core Google Compute Cluster

April 21, 2017

On Thursday, Google announced that MIT math professor and computational number theorist Andrew V. Sutherland had set a record for the largest Google Compute Engine (GCE) job. Sutherland ran the massive mathematics workload on 220,000 GCE cores using preemptible virtual machine instances. Read more…

By Tiffany Trader

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

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