The Onrushing Wave

Douglas_Reay

The Onrushing Wave — LessWrong

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exponential growth in chip processing speed

In terms of raw speed, Moore's Law has broken down for at least six or eight years. Chips have continued to advance in terms of transistors per area and other metrics, but their clock speed now is roughly what it was in 2005; and while parallelisation is nice, it is much more difficult to take advantage of than plain speed advances. Take an algorithm written in 1984 and run it on the hardware of 2004, and you will get an enormous speedup with zero work; but to get a further speedup from the hardware of 2014, you have to think about how to parallelise, and that's hard work even when it's possible - and not every algorithm can be usefully parallelised.

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passive_fist12y80

Taking advantage of new hardware has always required changing programs to make better use of the hardware. A Pentium 4 wasn't just a faster Pentium Pro. It had a different architecture, new instructions, different latencies and throughputs for various instructions, and vector processing extensions. To make full use of the P4's power, people definitely had to modify their code, all the way down to the assembly level. In fact early in the release cycle there were reports of many programs actually running slower on P4s than P3s under certain conditions. Softw... (read more)

0ThisSpaceAvailable12y

The benefits of parallelization are highly depended on the task, but there are quite a lot of tasks that are very amenable to it. It's difficult to rewrite a system from the ground up to take advantage of parallelization, but systems are designed with it in mind from the beginning, they can simply be scaled up as a larger number of processors becomes economically feasible. For quite a few algorithms, setting up parallelization is quite easy. Creating a new bitcoin block, for instance, is already a highly parallel task. As far as society-changing applications, there's a wide variety of tasks that are very susceptible to parallelization. Certainly, human-level intelligence does not appear to require huge serial power; human neurons have a firing rate in at most a few hundred hertz. Self-driving cars, wearable computers, drones, database integration ... I don't see a need for super-fast processors for any of these.

2DanArmak12y

Moore's Law is precisely about transistors per area, not about clock speed. So it hasn't broken down.

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