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January 11, 2008
Dan's Cloudy Crystal Ball
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Research and Infrastructure Funding
As I write this, there is no joy in Mudville (U.S. science funding), as Casey (the university, national laboratory and technology industry community) has struck out in securing a substantive budget increase for the sciences. After the America COMPETES Act authorized major increases in 2007, with strong bipartisan support, we had high hopes for a corresponding appropriation. Alas, the omnibus appropriation bill includes little new money for science.
With a few notable exceptions, research and infrastructure funding will (at best) just keep pace with inflation. This does not bode well for computational and computer science. If you really want to feel depressed, read Norm Augustine's new essay, Is America Falling Off the Flat Earth? This is a successor to the earlier Rising Storm report, and it is very sobering.
What can you do? First, don't whine -- that rarely impresses people in Washington. Rather, continue to make the case, via the venues and organizations where you are a member, that science and computing are critical enablers of economic growth, national innovation and education. Finally, it is especially important that we speak with a unified voice. A cacophony of confused messages will further delay the outcome we seek, for there are more supplicants and deserving ideas than available funding. As one Office of Management and Budget (OMB) examiner once remarked to me, "Rarely do I encounter people who say, 'I'm dumb and I have too much money. Can you help me?'" We are definitely not dumb, and we absolutely have great ideas; we must keep doggedly pushing our message.
Coordinating Strategy and Spending
In addition to seeking new funding, we also face challenges in supporting our existing capabilities. As our HPC systems and software infrastructures have grown, so have our operations and maintenance costs. Gone are the days when a large system was 64 processors and an application was developed by a small research team. Today we are deploying systems with hundreds of thousands of processors and many petabytes of storage, executing software frameworks containing tens to hundreds of millions of lines of code. The research agendas of entire disciplines now depend on the long-term sustenance of this infrastructure. Simply put, computational science has become big science, with correspondingly large staffs and rising power, cooling and capital costs.
The National Science Foundation (NSF) and the NSF Office of Cyberinfrastructure (OCI) are struggling to balance community demands for new investments against infrastructure sustenance. For example, I believe over 80 percent of OCI's budget is committed to extant projects, leaving little opportunity for new investment. Because so much of science now depends on computing, we must take a more holistic view of investment, examining scientific and technology priorities across all of the U.S. Federal agency portfolio and coordinating budgets accordingly. This is one of the key recommendations of the recent PCAST report on computing and a topic I discussed recently with Chris Greer, the new head of the National Coordination Office (NCO).
Outsourcing: Perhaps It Is Time?
In late November, I briefed the NSF OCI advisory committee on the PCAST report. The ensuing discussion centered on the rising academic cost of operating research computing infrastructure. The combination of rising power densities in racks and declining costs for blades means computing and storage clusters are multiplying across campuses at a stunning rate. Consequently, every academic CIO and chief research officer (CRO) I know is scrambling to coordinate and consolidate server closets and machine rooms for reasons of efficiency, security and simple economics.
This prompted an extended discussion with the OCI advisory committee about possible solutions, including outsourcing research infrastructure and data management to industrial partners. Lest this seem like a heretical notion, remember that some universities have already outsourced email, the lifeblood of any knowledge-driven organization. To be sure, there are serious privacy and security issues, as well as provisioning, quality of service and pricing considerations. However, I believe the idea deserves exploration.
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