Steven Chu’s DOE Legacy: Big Science, Grand Challenges and Solyndra

By Tiffany Trader

February 5, 2013

US Energy Secretary Steven Chu oversaw the nation’s energy policy at one of the most politically divisive times in recent history. Last Friday he announced that he would step down from the job. As a big champion of Big Science and its potential to change the country’s economic and environmental landscape – with government aid – many people welcome the change while others are sad to see him go.

Both views are based on one fact: During his four-year term, Chu emphasized the role of science and technology funding in national innovation and competitiveness.

In many people’s view, his greatest achievement was bringing science back to the forefront of energy policy after years of neglect under previous administrations.

To others, his decision to provide $535 million in federal loan guarantees to Solyndra, a solar energy company that later went bankrupt, makes him the poster child for government misspending.

A physics professor, Nobel Prize winner, and Bell Labs investigator, Chu has always been a huge proponent of the transformative power of research.

President Obama praised Chu for his efforts to bring about that transformation. “Over the past four years we have doubled the use of renewable energy, reduced our dependence on foreign oil and put our country on a path to win the global race for clean-energy jobs,” the President said.

Chu pushed the idea that high performance computing should play a key role in overcoming today’s difficult energy challenges. As head of the DOE, he was responsible for some of the most powerful supercomputers in the world. DOE’s Office of Science makes supercomputers available to researchers who use them to simulate everything from the components of a proton to the mechanisms of an exploding star. At a 2010 summit in Washington, D.C., he asserted that the “the DOE strategy should be to make simulation part of everyone’s toolbox.”

In 1997, Chu, along with several Bell Lab colleagues, won the Nobel Prize in Physics for their work on laser cooling. An article at Quartz by Steve LeVine examines how Chu set out to recreate the prolific Bell Laboratory model in Washington using focused funding streams and strategic innovation centers.

Chu’s approach was multi-pronged. First, he created 46 Energy Frontier Research Centers (EFRCs), funded at $2-5 million per year per center for an initial five-year year. These integrated, multi-investigator centers, operated by the DOE Office of Science, target “grand challenge” problems in order to transform “the way we generate, supply, transmit, store, and use energy.”

“The EFRCs neatly fit the Bell mantra,” writes LeVine. “Give a group of talented scientists a specific objective, the freedom to solve it how they see fit, a reasonable sum to work with, and let them go to the task. They might fail spectacularly, but Bell thought that was also how they may succeed.”

Next >>

The second piece of Chu’s plan was to establish five Energy Innovation Hubs, each of which receive up to $125 million in funding over five years. Their mission, according to the DOE, is “to shorten the path from laboratory innovation to technological development, and lead the way toward American competitiveness, economic growth and energy security.” Researchers from different labs are simulating nuclear reactors, developing biofuels from sunlight, designing energy efficient buildings, advancing electrochemical energy storage, and enhancing the supply of critical energy materials.

Chu also oversaw the development of Advanced Research Projects Agency-Energy (ARPA-E), a DOE incubator project that was modeled after the Defense Department’s DARPA program. As Chu explains, “ARPA-E was designed to support high-risk, high reward technology development; to swing for game-changing home runs that can fundamentally transform energy technologies.”

Many people in science and industry have praised the program. In his ARPA-E Summit Keynote, FedEx founder and CEO Fred Smith characterized it as “the best government funding program” he had ever seen.

But not everybody was so happy with Chu’s approach to government/industry collaboration. Republicans launched withering attacks against his handling of the Solyndra loan program after the solar panel maker and four other government-funded energy companies went belly-up on his watch. Some of the comments upon his resignation have not been so kind.

“While many will remember Secretary Chu for his comments about the need to raise gas prices on American consumers and the high grades he publicly bestowed on himself,” said House Oversight and Government Reform Committee Chairman Darrell Issa in a statement, “I found taxpayer losses on projects like Solyndra and the department’s deeply misguided effort to use taxpayer dollars as an investment bank for unproven technologies to be the most problematic aspects of his legacy.”

Chu takes responsibility for these “failures” in his resignation letter, but insists there is a larger context. Innovation, he says, requires risk:

The test for America’s policy makers will be whether they are willing to accept a few failures in exchange for many successes. America’s entrepreneurs and innovators who are leaders in global clean energy race understand that not every risk can – or should – be avoided. Michelangelo said, “The greater danger for most of us lies not in setting our aim too high and falling short; but in setting our aim too low, and achieving our mark.”

It’s true the research beds that Chu established are still in their early years, but he believes that they will give life to the same kind of game-changing advances associated with Bell Labs and other legendary institutions. “Some of those goals have been realized, and we have planted many seeds together,” he said in his resignation letter. “Just as today’s boom in shale gas production was made possible by Department of Energy research from 1978 to 1991, some of [our] most significant work may not be known for decades. What matters is that our country will reap the benefits of what we have started.”

His final legacy will have to wait for those decades to pass and demonstrate whether or not his words prove true.

Related Articles

US Energy Secretary Talks Supercomputing

Steven Chu Announces the Scalable Data Management, Analysis, and Visualization Institute

Three DOE Labs Now Connected with Ultra-High Speed Network

Supercomputing Key to US Leadership

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!

AI in the News: Rao in at Intel, Ng out at Baidu, Nvidia on at Tencent Cloud

March 26, 2017

Just as AI has become the leitmotif of the advanced scale computing market, infusing much of the conversation about HPC in commercial and industrial spheres, it also is impacting high-level management changes in the industry. Read more…

By Doug Black

Scalable Informatics Ceases Operations

March 23, 2017

On the same day we reported on the uncertain future for HPC compiler company PathScale, we are sad to learn that another HPC vendor, Scalable Informatics, is closing its doors. Read more…

By Tiffany Trader

‘Strategies in Biomedical Data Science’ Advances IT-Research Synergies

March 23, 2017

“Strategies in Biomedical Data Science: Driving Force for Innovation” by Jay A. Etchings is both an introductory text and a field guide for anyone working with biomedical data. Read more…

By Tiffany Trader

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 assets. Read more…

By Tiffany Trader

HPE Extreme Performance Solutions

HFT Firms Turn to Co-Location to Gain Competitive Advantage

High-frequency trading (HFT) is a high-speed, high-stakes world where every millisecond matters. Finding ways to execute trades faster than the competition translates directly to greater revenue for firms, brokerages, and exchanges. Read more…

Google Launches New Machine Learning Journal

March 22, 2017

On Monday, Google announced plans to launch a new peer review journal and “ecosystem” Read more…

By John Russell

Swiss Researchers Peer Inside Chips with Improved X-Ray Imaging

March 22, 2017

Peering inside semiconductor chips using x-ray imaging isn’t new, but the technique hasn’t been especially good or easy to accomplish. Read more…

By John Russell

LANL Simulation Shows Massive Black Holes Break ‘Speed Limit’

March 21, 2017

A new computer simulation based on codes developed at Los Alamos National Laboratory (LANL) is shedding light on how supermassive black holes could have formed in the early universe contrary to most prior models which impose a limit on how fast these massive ‘objects’ can form. Read more…

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. Read more…

By John Russell

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 assets. 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. Read more…

By John Russell

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 campaign. 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

US Supercomputing Leaders Tackle the China Question

March 15, 2017

Joint DOE-NSA report responds to the increased global pressures impacting the competitiveness of U.S. supercomputing. Read more…

By Tiffany Trader

New Japanese Supercomputing Project Targets Exascale

March 14, 2017

Another Japanese supercomputing project was revealed this week, this one from emerging supercomputer maker, ExaScaler Inc., and Keio University. The partners are working on an original supercomputer design with exascale aspirations. Read more…

By Tiffany Trader

Nvidia Debuts HGX-1 for Cloud; Announces Fujitsu AI Deal

March 9, 2017

On Monday Nvidia announced a major deal with Fujitsu to help build an AI supercomputer for RIKEN using 24 DGX-1 servers. Read more…

By John Russell

HPC4Mfg Advances State-of-the-Art for American Manufacturing

March 9, 2017

Last Friday (March 3, 2017), the High Performance Computing for Manufacturing (HPC4Mfg) program held an industry engagement day workshop in San Diego, bringing together members of the US manufacturing community, national laboratories and universities to discuss the role of high-performance computing as an innovation engine for American manufacturing. Read more…

By Tiffany Trader

For IBM/OpenPOWER: Success in 2017 = (Volume) Sales

January 11, 2017

To a large degree IBM and the OpenPOWER Foundation have done what they said they would – assembling a substantial and growing ecosystem and bringing Power-based products to market, all in about three years. Read more…

By John Russell

TSUBAME3.0 Points to Future HPE Pascal-NVLink-OPA Server

February 17, 2017

Since our initial coverage of the TSUBAME3.0 supercomputer yesterday, more details have come to light on this innovative project. Of particular interest is a new board design for NVLink-equipped Pascal P100 GPUs that will create another entrant to the space currently occupied by Nvidia's DGX-1 system, IBM's "Minsky" platform and the Supermicro SuperServer (1028GQ-TXR). Read more…

By Tiffany Trader

Tokyo Tech’s TSUBAME3.0 Will Be First HPE-SGI Super

February 16, 2017

In a press event Friday afternoon local time in Japan, Tokyo Institute of Technology (Tokyo Tech) announced its plans for the TSUBAME3.0 supercomputer, which will be Japan’s “fastest AI supercomputer,” Read more…

By Tiffany Trader

IBM Wants to be “Red Hat” of Deep Learning

January 26, 2017

IBM today announced the addition of TensorFlow and Chainer deep learning frameworks to its PowerAI suite of deep learning tools, which already includes popular offerings such as Caffe, Theano, and Torch. Read more…

By John Russell

Lighting up Aurora: Behind the Scenes at the Creation of the DOE’s Upcoming 200 Petaflops Supercomputer

December 1, 2016

In April 2015, U.S. Department of Energy Undersecretary Franklin Orr announced that Intel would be the prime contractor for Aurora: Read more…

By Jan Rowell

Is Liquid Cooling Ready to Go Mainstream?

February 13, 2017

Lost in the frenzy of SC16 was a substantial rise in the number of vendors showing server oriented liquid cooling technologies. Three decades ago liquid cooling was pretty much the exclusive realm of the Cray-2 and IBM mainframe class products. That’s changing. We are now seeing an emergence of x86 class server products with exotic plumbing technology ranging from Direct-to-Chip to servers and storage completely immersed in a dielectric fluid. Read more…

By Steve Campbell

Enlisting Deep Learning in the War on Cancer

December 7, 2016

Sometime in Q2 2017 the first ‘results’ of the Joint Design of Advanced Computing Solutions for Cancer (JDACS4C) will become publicly available according to Rick Stevens. He leads one of three JDACS4C pilot projects pressing deep learning (DL) into service in the War on Cancer. Read more…

By John Russell

BioTeam’s Berman Charts 2017 HPC Trends in Life Sciences

January 4, 2017

Twenty years ago high performance computing was nearly absent from life sciences. Today it’s used throughout life sciences and biomedical research. Genomics and the data deluge from modern lab instruments are the main drivers, but so is the longer-term desire to perform predictive simulation in support of Precision Medicine (PM). There’s even a specialized life sciences supercomputer, ‘Anton’ from D.E. Shaw Research, and the Pittsburgh Supercomputing Center is standing up its second Anton 2 and actively soliciting project proposals. There’s a lot going on. Read more…

By John Russell

Leading Solution Providers

HPC Startup Advances Auto-Parallelization’s Promise

January 23, 2017

The shift from single core to multicore hardware has made finding parallelism in codes more important than ever, but that hasn’t made the task of parallel programming any easier. Read more…

By Tiffany Trader

HPC Technique Propels Deep Learning at Scale

February 21, 2017

Researchers from Baidu’s Silicon Valley AI Lab (SVAIL) have adapted a well-known HPC communication technique to boost the speed and scale of their neural network training and now they are sharing their implementation with the larger deep learning community. Read more…

By Tiffany Trader

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 campaign. Read more…

By John Russell

CPU Benchmarking: Haswell Versus POWER8

June 2, 2015

With OpenPOWER activity ramping up and IBM’s prominent role in the upcoming DOE machines Summit and Sierra, it’s a good time to look at how the IBM POWER CPU stacks up against the x86 Xeon Haswell CPU from Intel. Read more…

By Tiffany Trader

IDG to Be Bought by Chinese Investors; IDC to Spin Out HPC Group

January 19, 2017

US-based publishing and investment firm International Data Group, Inc. (IDG) will be acquired by a pair of Chinese investors, China Oceanwide Holdings Group Co., Ltd. Read more…

By Tiffany Trader

US Supercomputing Leaders Tackle the China Question

March 15, 2017

Joint DOE-NSA report responds to the increased global pressures impacting the competitiveness of U.S. supercomputing. 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. Read more…

By John Russell

Intel and Trump Announce $7B for Fab 42 Targeting 7nm

February 8, 2017

In what may be an attempt by President Trump to reset his turbulent relationship with the high tech industry, he and Intel CEO Brian Krzanich today announced plans to invest more than $7 billion to complete Fab 42. Read more…

By John Russell

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