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posted by Fnord666 on Sunday January 28 2018, @11:28AM   Printer-friendly
from the RIP dept.

Submitted via IRC for AndyTheAbsurd

Hammered by the finance of physics and the weaponisation of optimisation, Moore's Law has hit the wall, bounced off - and reversed direction. We're driving backwards now: all things IT will become slower, harder and more expensive.

That doesn't mean there won't some rare wins - GPUs and other dedicated hardware have a bit more life left in them. But for the mainstay of IT, general purpose computing, last month may be as good as it ever gets.

Going forward, the game changes from "cheaper and faster" to "sleeker and wiser". Software optimisations - despite their Spectre-like risks - will take the lead over the next decades, as Moore's Law fades into a dimly remembered age when the cornucopia of process engineering gave us everything we ever wanted.

From here on in, we're going to have to work for it.

It's well past the time that we move from improving performance by increasing clock speeds and transistor counts; it's been time to move on to increasing performance wherever possible by writing better parallel processing code.

Source: https://www.theregister.co.uk/2018/01/24/death_notice_for_moores_law/


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  • (Score: 2) by frojack on Sunday January 28 2018, @09:11PM

    by frojack (1554) on Sunday January 28 2018, @09:11PM (#629575) Journal

    There will be at least some amount of performance increase over the next 10 years, as well as a power consumption reduction

    I predict performance increases will continue, in spite of this story. We are simply in a developmental pause, as new technologies come on line.

    Did Moore's law apply to steam engines? They got bigger and faster (120mph) and then they disappeared. Poof.
    Yet the dog-slow Amtrak Acella Express attains 150 mph daily, and are laughed at by the Japanese and Germans and Chinese "bullet" trains.

    The path to more power does not rely ONLY on maintaining the same technology. But even if you do, you can use the same technology in totally different ways. Example: Field-programmable gate array (FPGA), can evolve so that the first thing that happens when a program is launched is that generic FPGA is allocated from a pool, and the software sets it up (programs the array), runs ts main functions on the (now custom) array, releases the array, and exits.

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