The Supercomputer Race
CWmike writes "Every June and November a new list of the world's fastest supercomputers is revealed. The latest Top 500 list marked the scaling of computing's Mount Everest — the petaflops barrier. IBM's 'Roadrunner' topped the list, burning up the bytes at 1.026 petaflops. A computer to die for if you are a supercomputer user for whom no machine ever seems fast enough? Maybe not, says Richard Loft, director of supercomputing research at the National Center for Atmospheric Research in Boulder, Colo. The Top 500 list is only useful in telling you the absolute upper bound of the capabilities of the computers ... It's not useful in terms of telling you their utility in real scientific calculations. The problem with the rankings: a decades-old benchmark called Linpack, which is Fortran code that measures the speed of processors on floating-point math operations. One possible fix: Invoking specialization. Loft says of petaflops, peak performance, benchmark results, positions on a list — 'it's a little shell game that everybody plays. ... All we care about is the number of years of climate we can simulate in one day of wall-clock computer time. That tells you what kinds of experiments you can do.' State-of-the-art systems today can simulate about five years per day of computer time, he says, but some climatologists yearn to simulate 100 years in a day."
But.. The whole point is to test the model, and the models change, don't they? Surely we're not just simulating more "years" of climate with the current batch, but improving resolution, making fewer simplifying assumptions, and hopefully, finding ways to do the exact same operations with fewer cycles.
How can you possibly evaluate supercomputers in any other way except how many mathematical operations can be performed in some reference time? And.. some serial metric if the math is highly parallel, since just reducing the size of vectors in those cases wouldn't actually result in those flops being useful for other tasks.
Can you be Even More Awesome?!
A quality HPC vendor will give you the opportunity to benchmark your application before you buy a system or cluster. Most will have standard codes installed, but you should also be able to arrange for a login to build and run your own code on their test clusters. This is the only way to guarantee you're getting the best bang per buck, because the bottleneck in your particular applications may be memory, IO, interconnect, CPU, chipset, libraries, OS... An HPC cluster can be a big purchase, and it performance and reliability can make or break careers. Don't trust generalized benchmarks unless you know that they accurately reflect your workload on the hardware you'll be purchasing.
I just threw away a couple of mod points to bring you this announcement: Climate != weather, climate is the long term statistics of weather. Two different numerical analysis models, both computationally expensive.
And did you exchange a walk on part in the war for a lead role in a cage? - Pink Floyd.