Top scientist urges 'ambitious' U.S. exascale supercomputer plan

Peter Beckman, head of the DOE's new exascale institute, says international rivals are working hard to displace U.S. as No. 1

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How far along is this? What stage are you at? We've been doing it for a better part of a decade in less formal venues. IBM is a partner with Argonne and Lawrence Livermore Lab, and together we designed Blue Gene/P and Blue Gene/Q. In that partnership, we paid money to IBM to design the prototype for Blue Gene/P and Q and then all of our scientists did constant evaluation and discussion about trade-offs. For example, would we rather have a memory management unit than another core? But it was sort of, what I would say, in the small. We didn't take it out to the broader community.

In the exascale thrust, the DOE has said we're going to launch a series of co-design centers that will cover several applications areas, fusion, materials, chemistry, climate, etc., and those communities will then have a voice in speaking with the companies designing the platforms.

Is this a national or international effort? The DOE piece is a national effort, but Jack Dongarra and I also lead the International Exascale Software Project (IESP). In it, we bring together representatives from Asia, Europe and the U.S. to focus on software. That's something that transcends national boundaries at this point. People work on codes from open source.

Because software is ubiquitous in that way and is really shared and improved inter-globally, the IESP has organized a road map for what the software for exascale needs. We have spent the last year and half developing that road map and have now turned our attention to co-design. That's mostly a collaborative effort.

The DOE has funded a very specific program to start the planning for exascale. They have been given planning funding. But until there is a congressional budget that funds it, it is still just in planning mode.

Is there concern about getting funding for exascale development? There is. Budgets are tight, and the change in politics, in representation in Washington, means that things that were sort of in the plan now have to be looked at a second time. There is a concern that this initiative has to be pushed forward and has to get funded or we're going to lose our leadership position. The DOE has been planning this for the last couple of years, so this is not a new thing.

Is exascale development as predictable as people believe? Will exascale systems arrive in the 2018 time frame? In some sense, we've become so predictable, but that's only because we invested in a particular goal. If we don't have an exascale push in the country, it's not going to happen.

Is there any comparison between what's involved in reaching petascale with what's involved in reaching exascale? There was a period of time of about 15 years where the maximum level of parallelism in the biggest systems in the world really didn't change much. The biggest systems had tens of thousands of processors. We are now on an exponential ... like this [he points up], where Blue Gene has 200,000 [or] 300,000 cores now; the next version is going to have a million cores as we go up. The application codes need to be radically improved in order to take advantage of all this parallelism.

Are the programming languages developed for it? That is a big issue. If you were to go to 10 different big application folks and ask, "What's your programming model for the future?" you will see a lot of concern in their expression and maybe not a lot of certainty in their answer. The path to harvest all this parallelism and put it to use is not clear yet.

What can exascale systems accomplish? The key thing that people are looking at is moving from simulating and sort of understanding basic behavior to predictive simulation. What we want to be able to do is not just characterize a jet engine and understand how its combustion works but move aggressively to be able to predict the design of an engine that would get 20% better fuel efficiency and reduce our carbon emissions.

As we look to electric vehicles, all the technology hinges on the battery. If we can move from a basic manipulating of chemistry to predicting the optimal new battery designs, we could change to an electric vehicle economy. The single biggest impact on how we can change our everyday life is if we could move to eliminate the need for burning fossil fuels.

What can this do for national economic development? We are a country that loves to invent its way out of problems. When we see a problem, we like to find a solution that's inventive, that's creative, that's new. When I look at healthcare, transportation, generating power, basic materials, chemistry -- we want to be the country that invents solutions for these problems.

All those things require government funding because they involve basic sciences, more so than say 100 years ago, correct? This is something that many people don't understand. [At an earlier time] one guy could actually invent and do a bunch of stuff. Nowadays, it still can be one guy but he's on a pyramid that has millions of community-developed components and other pieces of technology that he is relying on.

To get really far advanced, to really push that state of the art, you are on top of a collaborative community of scientists. Science has done more and more in a partnership with other people at universities, laboratories and industries and other countries, and it really requires the government to keep invested.

The education piece is also key. Finding the postdocs and finding the students that come to work in our laboratories is becoming increasingly difficult.

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