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Why Aren't Supercomputers Getting Faster Like They Used To?

posted by cmn32480 on Monday July 20 2015, @07:33PM   Printer-friendly
from the does-it-run-windows? dept.

Phoenix666 writes:

Currently, the world's most powerful supercomputers can ramp up to more than a thousand trillion operations per second, or a petaflop. But computing power is not growing as fast as it has in the past. On Monday, the June 2015 listing of the Top 500 most powerful supercomputers in the world revealed the beginnings of a plateau in performance growth.
...
The development rate began tapering off around 2008. Between 2010 and 2013, aggregate increases ranged between 26 percent and 66 percent. And on this June's list, there was a mere 17 percent increase from last November.
...
Despite the slowdown, many computational scientists expect performance to reach exascale, or more than a billion billion operations per second, by 2020.

Hmm, if they reach exascale computing will the weatherman finally be able to predict if it's going to rain this afternoon? Because he sucks at that now.

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  • (Score: 2) by TheRaven on Tuesday July 21 2015, @08:21AM

    by TheRaven (270) on Tuesday July 21 2015, @08:21AM (#211833) Journal
    The problem I have with weather forecasts is that they never provide a confidence. If you look at the satellite maps, then you can often get a pretty good idea of how accurate the forecast is. If you're in a stable patch of atmosphere, they're going to be pretty good. If there's a single front moving across then the times may be off, but they're likely to still be pretty good. If your weather is determined by two or more fronts colliding then all bets are off. The people doing the weather models know to a pretty high degree how accurate their predictions are, but never include this information when they send forecasts out to the public.
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  • (Score: 2) by kurenai.tsubasa on Tuesday July 21 2015, @01:50PM

    by kurenai.tsubasa (5227) on Tuesday July 21 2015, @01:50PM (#211905) Journal

    Go to NOAA [noaa.gov] and read the forecast discussion link (example [weather.gov]). Sure, it's not an actual confidence interval like you're probably looking for, but they will throw out hints here and there about how they're interpreting the models and how confident they feel about the published forecast. Be prepared to click on all kinds of obscure abbreviations and acronyms until you get used to the jargon (when they're kind enough to turn the shorthand jargon into a link anyway).