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September 22, 2006
Horst Simon Talks Petascale
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At the HPC User Forum meeting in Denver this week, Horst Simon was one of two industry experts asked to provide a larger perspective as representatives of organizations in China, Japan and the U.S. discussed their petascale initiatives. In this Q&A, Simon offers his views about the challenges of achieving usable petascale systems within the next five years.
HPCwire: The U.S. and several other countries have petascale initiatives in play. How realistic is the dual goal of achieving sustained petaflops speed and substantially boosting productivity by 2010?
Simon: There have been multiple announcements of plans for petascale machines in that timeframe, so I'm fairly confident that the sustained petaflop goal will be attained by 2010, meaning that by then there will be a Gordon Bell Prize for a sustained petaflop on a real application on a real platform. I'd be even more comfortable predicting that this will happen by 2011.
As for part two of your question, it depends on your definition of productivity. If productivity means the economic output of a country, then I think 2010 is too early for petascale computing to affect that. If productivity means making efficient use of petascale systems in industry, for example to routinely create better products at lower costs through the use of simulation, this implies that the petascale systems would have good scalability, reliable application and system software, and so on, and I think 2010 will also be too soon for this. There will be many technical challenges, because we're entering a completely new arena of scalability. Getting to productive petaflop performance will be as difficult as it has been getting to productive teraflop performance.
But if productivity means running codes faster and at higher resolution, which can enables scientific breakthroughs, then I'm confident this will happen because of the continued dramatic advances in computational technology based on commodity clusters. Ten years ago, few people thought PC clusters would have the big impact they have had. The same thing will happen with petascale systems in the future. They will become common.
HPCwire: Can anyone really afford a general-purpose sustained petaflop system in the 2009-11 timeframe that several countries are targeting? By general purpose, I mean a system that can sustain petaflop performance on a reasonably broad spectrum of codes.
Simon: Yes, to the part about affording petaflop systems in that timeframe. Petaflop systems are expensive, but not super-expensive if you look at them in relation to other large-scale scientific projects, like particle accelerators or the next-generation space telescope. It costs about $200 million to fund a petascale system today, which is not outrageously high. The bigger question is, what is the optimal time to make that investment? The Earth Simulator was a huge investment of about $400 million and made a big, immediate impact when it went live in 2002. Now, four years later, a 40-teraflop machine is much less expensive. It's important to produce significant results in the first one to two years, so Moore's Law doesn't catch up with the machine. It must be productive quickly.
As for general-purpose, if we look at the ratios of memory and disk that would be needed, and the I/O rates, then a general-purpose petascale system could become much more expensive. But we're approaching an era when the whole notion of general-purpose HPC systems may no longer apply. Instead, there will be commodity clusters for most things, along with opportunities to leverage special-purpose technologies like Blue Gene, which can run specific applications very successfully, or MDGRAPE3 from RIKEN, which arguably is the first petascale system and is highly specialized. In 2010-11, I would expect an increasing trend toward more highly specialized systems.
HPCwire: Can anything be done to alleviate the costs of petascale systems while maintaining their usefulness?
Simon: One big issue for the future is that operational costs have been increasing significantly. We're approaching the point where computers can cost more to operate than their acquisition cost. One big potential area for cost reduction is less power-consuming components to reduce overall cost of ownership. Another one is facility construction. Construction costs have also gone up substantially, and you can save a lot of money if you don't have to build a new facility or heavily modify an existing one.
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