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tons of algorithms and software don't run any faster with more cores. Plus each core has a n+1 cost associated with it, whereas with how scaling worked previous

by throwaway2048 9y ago

tons of algorithms and software don't run any faster with more cores. Plus each core has a n+1 cost associated with it, whereas with how scaling worked previously you got better performance for cheaper because of size decreases. The most significant cost in making an ASIC is the silicon wafer, which is extremely expensive, so anything that uses it more efficiently [ less space] makes things cheaper, faster (easier to keep a faster clock synced over a small area), and use less power (less power means you can go faster too, because you have more power/head headroom for cranking clock speeds). Scaling by going smaller is extremely synergistic, and has super exponential performance impact, whereas in the very best case adding more cores is linear, and in almost every real world case, sub linear. It also costs more, not less. The fact is baring major breakthroughs, we are stuck with roughly today's level of performance for the foreseeable future.

carlmr 9y ago
>The fact is baring major breakthroughs, we are stuck with roughly today's level of performance for the foreseeable future. Maybe finally we stop wasting hardware and use the supercomputers we have in our pockets for greater things. Another thing to consider is that memory access is still the most prevalent speed problem. If we can work on these bottlenecks we can still get significant performance increases without actually increasing CPU performance that much.
pcwalton 9y ago
> tons of algorithms and software don't run any faster with more cores. > The fact is baring major breakthroughs, we are stuck with roughly today's level of performance for the foreseeable future. That's obviously false. Otherwise graphics wouldn't get any faster when you add more GPU cores, to name one common embarrassingly parallel problem. Our software is just really bad at making use of those extra cores. Measure real-world use cases with a well-tuned work stealing engine and you'll see how much performance we're leaving on the table. (Source: I wrote the first version of possibly the largest consumer deployment of a major software component backed by a work stealing engine.)

carlmr 9y ago

>The fact is baring major breakthroughs, we are stuck with roughly today's level of performance for the foreseeable future. Maybe finally we stop wasting hardware and use the supercomputers we have in our pockets for greater things. Another thing to consider is that memory access is still the most prevalent speed problem. If we can work on these bottlenecks we can still get significant performance increases without actually increasing CPU performance that much.

pcwalton 9y ago

> tons of algorithms and software don't run any faster with more cores. > The fact is baring major breakthroughs, we are stuck with roughly today's level of performance for the foreseeable future. That's obviously false. Otherwise graphics wouldn't get any faster when you add more GPU cores, to name one common embarrassingly parallel problem. Our software is just really bad at making use of those extra cores. Measure real-world use cases with a well-tuned work stealing engine and you'll see how much performance we're leaving on the table. (Source: I wrote the first version of possibly the largest consumer deployment of a major software component backed by a work stealing engine.)