Flexing US muscle in supercomputing
Published: 29 Jan 2008 15:55 GMT
the cream rises and people are going to try to make use of the best technology they can, as opposed to engaging in a very speculative endeavour of trying to embrace these other policies and practices to build an unrelated indigenous industry that's going to serve some nebulous goal under the "partisan state commissar". That may happen, but I think the likelihood is fairly low.
The US employs so many first-rank computer scientists from both China and India, and yet both of those countries still have relatively small shares in the supercomputer field. When do you expect that to change?
I think they are still some way away from having the robust spread of industries that can effectively make use of this technology.
There is a peculiarity about American industry and its ability to give birth to new industry that I think is different than what you see in some of these other places at least today. I am not saying it's in perpetuity or anything intrinsic; it is just the way it is today.
What about five to 10 years from now in China and India?
China has been a little bit more forthcoming about their national strategy and they've talked about the need to build an indigenous industry. That effort is under way and we'll see what happens.
India has been somewhat different. I'm not particularly aware of any dramatic effort on the part of the government to drive anything as major as an Indian supercomputing industry. I think it's still in the hands of the private sector.
What about Russia, [which is] not just making but buying supercomputers? You've got the announcement of the first Blue Gene supercomputer in Russia, but what about their abilities to actually make their own supercomputers?
There is no evidence that there is anything material going on in Russia to build the industry. There is, of course, a lot of interest in acquiring the technology to use it and that dichotomy is pretty stark. So the question is: what does it take to actually create an industry to do this kind of stuff? In the year 2001, the answer would have been easy and the answer [was]: "It doesn't take much at all." You just get some off-the-shelf Intel or AMD servers and you assemble them, and you get some open-source software and you deploy, and you're ready to go.
You just get some off-the-shelf Intel or AMD servers and you assemble them, and you get some open-source software and you deploy, and you're ready to go.
Dave Turek, IBM
We know that's true because that's where a lot of universities were deploying Linux clusters in the early part of this decade. What's happened differently now, and what I think constitutes a progressively greater and greater degree of challenge for people who wanted to get into this space, is the whole consequence of the limits that we're coming into contact with in respect to overall microprocessor system design.
I think it was January of 2004 that marked the point in time where Intel abandoned their megahertz-or-gigahertz-is-better approach. And they did that because, pretty soon, we are going to require a nuclear power plant to run your laptop. That was just the consequence of the arithmetic of Moore's Law, but physics has this nasty way of intruding and the industry finds itself working up against a lot of limits that are pretty daunting right now.
Such as?
It's what's given rise to this whole push on multicore and radical multithreading [et cetera]. But all of that stuff implies greater and greater complexity. It requires greater and greater sophistication of systems design, utilisation approach et cetera, and so there's been a de facto rise of barriers to entry that have not been caused by any economic or political thing. It's been caused by science and engineering barriers that are proving to be progressively more daunting to overcome.
Look at the Blue Gene system for example. That project was begun in December of 1999 when the world was a radically different place and when nobody was thinking about the green computer room or any of that stuff. But to the everlasting credit of a fairly significant number of people in our own research division, we started building a massively scaled parallel system with the kinds of chips you would use in a mobile phone. Everybody thought we were lunatics. And what happened? Not only is it the most powerful system in the world, but it's the greenest system at the same time.
Green meaning more energy efficient?
Green being the smallest consumer of energy on a per-unit amount of computation. So Blue Gene has an advantage over the next closest competitor by probably a factor of five or six in terms of energy efficiency. When you think about what energy costs these days and how much energy some of these systems require, that's a hugely important factor to include.
That's a big obstacle to entry to overcome.
You have to have some pretty serious engineering skills, because the future design of these computers does not get easier. It gets harder as you try to accommodate the constraints of power, cooling and space, and programmability.
You can say there is a lot of brainpower in China, there is a lot of brainpower in India, there is a lot of brainpower in Russia that's all true and nothing is forever. There may come a point in the future where [they] get organised and pursue these things and come up with some really terrific insights. The only obstacle is brain power, some money, vision and hard work that's all.
Credit: Newsmaker: Flexing a super (computing) muscle from CNET News.com
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