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IEEE Says Multicore is Bad News For Supercomputers
Richard Kelleher writes "It seems the current design of multi-core processors is
not good for the design of supercomputers. According to IEEE: 'Engineers at Sandia National Laboratories, in New Mexico, have simulated future high-performance computers containing the 8-core, 16-core, and 32-core microprocessors that chip makers say are the future of the industry. The results are distressing. Because of limited memory bandwidth and memory-management schemes that are poorly suited to supercomputers, the performance of these machines would level off or even decline with more cores.'"
I've always felt there was something odd about the recent trend of Super Computers using common hardware. components. They have really loss their way in super computing by just making a beefed up PC and running a version of a common OS which could handle it. Or Clustering a bunch of PC's togeter. Multi-Core technology is good for desktop systems as it is meant to run a lot of relatively small apps Rarely taking advantage of more then 1 or 2 cores. per app.In other-words it allows Multi-Tasking without a penalty. We don't use super computers that way. We use them to to perform 1 app that takes huge resources that would take hours or years on your PC and spit out results in seconds or days. Back in the early-mid 90's we had different processors for Desktop and Super Computers. Yes it was more expensive for the super computers but if you were going to pay millions of dollars for a super computer what the difference if you need to pay an additional $80,000 for more custom processors.
If something is so important that you feel the need to post it on the internet... It probably isn't that important.
A related problem to the speed of memory access is the energy efficiency of it. In an IEEE Spectrum Radio piece interviewing Peter Kogge, current supercomputers can spend many times more energy shuffling bits around than operating on them. Today's computer can do a double-precision (64-bit) floating point operation using about 100 picojoules. However, it takes upwards of 30 pJ per bit to get the 128 bits of data loaded into the floating point math unit of the CPU, and then moving the 64-bit result elsewhere.
Actual math operations consume 5-10% of a supercomputer's total power, moving data from A to B is approaching 50%. Most optimization and innovation in the past few decades has gone into compute algorithms in the CPU core, and very little has gone into memory.
It may be true that "That market simply isn't large enough to support an R&D which will consistently outperform commodity hardware at a price people are willing to pay," that's not quite tantamount to saying "there is no possible rational justification for a larger supercomputer budget." There are considerable inflection points and external factors to consider.
The market doesn't allocate funds the way a central planner does. A central planner says, "there isn't room in this budget to add to supercomputer R&D." The way the market works is that commodity hardware vendors beat each other down until everybody is earning roughly similar normal profits. Then somebody comes a long with a set of ideas that could double the rate at which supercomputer power is increasing. If that person is credible, he is a standout investment, not just despite the fact that there is so much money being poured into commodity hardware, but because of that.
There may also be reasons for public investment in R&D. Naturally the public has no reason to invest in commodity hardware research, but it may have reason to look at exotic computing research. Suppose that you expected to have a certain maximum practical supercomputer capability in twenty years' time. Suppose you figure that once you have that capability you could predict a hurricane's track with several times the precision you could today. It'd be quite reasonable to put a fair amount of public research funds into supercomputing in order to have the that ability in five to ten years' time.
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