Information technology needs fundamental shift to continue rapid advances in computing and help drive US competitiveness

December 16, 2010

WASHINGTON -- The rapid advances in information technology that drive many sectors of the U.S. economy could stall unless the nation aggressively pursues fundamental research and development of parallel computing -- hardware and software that enable multiple computing activities to process simultaneously, says a new report by the National Research Council. Better options for managing power consumption in computers will also be essential for continued improvements in IT performance.

For many decades, advances in single-processor, sequential computer microprocessors have enabled computing performance to increase dramatically -- on the order of 10,000 times in the last 20 years alone. However, power management and other technological limitations have made it impractical to continue improving computer performance in this way much longer. Parallel computing, therefore, is the only known alternative for improving computer performance without significantly increasing costs and energy usage, the report says.

"The societal and economic impact of computer technology is undeniable, increasing productivity and efficiency and fostering innovation in medicine, defense, entertainment, and communications," said Samuel H. Fuller, chief technology officer and vice president of research and development for Analog Devices Inc., Norwood, Mass., and chair of the committee that wrote the report. "To ensure that computing systems continue to double in performance every few years, we need to make significant changes in computer software and hardware. Investing in research and development of parallel computing offers a clear path forward."

Despite some mainstream successes in parallel computing -- such as the MapReduce programming framework used by Google to process large data sets using thousands of computers -- most parallel computing in use now is limited to comparatively narrow scientific and engineering applications. To enable parallel computing for broader use, new algorithms, programming models, operating systems, and computer architectures will be required, the report says, and research and development in these areas should be pursued.

In particular, advances are necessary to develop new parallel programming methods and supporting computing systems. Although computing hardware such as semiconductor chips that contain eight or more microprocessors have already been developed, software that can keep that many or more processors busy in parallel is not available for most computing applications.

Research and development should also focus on making computer systems more energy efficient, the report says. Power constraints now affect systems ranging from handheld devices to the largest computing data centers. Most computer chips are designed with silicon-based complementary metal oxide semiconductor (CMOS) technology. While the number of devices per CMOS chip continues to double every few years, the technology has essentially reached its limits with regard to power efficiency. Even as new parallel computing models and solutions are found, most future performance will ultimately be limited by energy constraints, the report notes.

It cautions that while parallel computing is the best alternative for improving future performance, there is no guarantee that it will bring rapid advances like those experienced in recent decades, and a number of uncertainties still need to be addressed. Therefore, research and development should also explore fundamentally different alternatives to today's CMOS technology.

The report also recommends developing open interface standards for parallel programming to promote cooperation and innovation in the industry, designing tools and methods for transferring today's sequential computing to parallel applications, and emphasizing parallel computing as part of computer science education.
-end-
The study was sponsored by the National Science Foundation. The National Academy of Sciences, National Academy of Engineering, Institute of Medicine, and National Research Council make up the National Academies. They are private, nonprofit institutions that provide science, technology, and health policy advice under a congressional charter. The Research Council is the principal operating agency of the National Academy of Sciences and the National Academy of Engineering. For more information, visit http://national-academies.org. A committee roster follows.

Contacts:
Molly Galvin, Media Relations Officer
Christopher White, Media Relations Assistant
Office of News and Public Information
202-334-2138; e-mail news@nas.edu

Pre-publication copies of The Future of Computing Performance: Game Over or Next Level? are available from the National Academies Press; tel. 202-334-3313 or 1-800-624-6242 or on the Internet at http://www.nap.edu. Reporters may obtain a copy from the Office of News and Public Information (contacts listed above).

NATIONAL RESEARCH COUNCIL
Division on Engineering and Physical Sciences
Computer Science and Telecommunications Board

Committee on Sustaining Growth in Computing Performance

Samuel H. Fuller (chair)*
Chief Technology Officer, and
Vice President of Research and Development
Analog Devices Inc.
Norwood, Mass.

Luiz Andre Barroso
Distinguished Engineer
Google Inc.
Mountain View, Calif.

Robert P. Colwell*
Independent Consultant
R&E Colwell and Associates
Portland, Ore.

William J. Dally*
Chief Scientist
NVIDIA, and
Willard R. and Inez Kerr Bell Professor of Computer Science and Electrical Engineering
Computer Science Department
Stanford University
Stanford, Calif.

Daniel W. Dobberpuhl*
Independent Consultant
Monterey, Calif.

Pradeep Dubey
Senior Principal Engineer and Director of Parallel Computing Lab
Intel Labs
Intel Corp.
Santa Clara, Calif.

Mark D. Hill
Professor
Computer Sciences Department
Electrical and Computer Engineering Department
University of Wisconsin
Madison

Mark A. Horowitz*
Chair and Yahoo! Founders Professor
Department of Electrical Engineering
Stanford University
Stanford, Calif.

David B. Kirk*
Fellow
NVIDIA
Santa Clara, Calif.

Monica S. Lam
Professor of Computer Science
Stanford University
Stanford, Calif.

Kathryn S. McKinley
Endowed Professor of Computer Science
University of Texas
Austin

Charles Moore
Corporate Fellow and Chief Technology Officer for Technology Group
Advanced Micro Devices Inc.
Sunnyvale, Calif.

Katherine A. Yelick
Professor
Department of Electrical Engineering and Computer Sciences
University of California, and
Associate Laboratory Director for Computing Sciences
Lawrence Berkeley National Laboratory
Berkeley

STAFF
Lynette I. Millett
Study Director and Senior Program Officer

* Member, National Academy of Engineering

National Academies of Sciences, Engineering, and Medicine

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