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To expand on that, this is my understanding: process shrinks used to lead to faster clocks AND more transistors, but a wall was hit and since then they only lea
by Joeri 7y ago
To expand on that, this is my understanding: process shrinks used to lead to faster clocks AND more transistors, but a wall was hit and since then they only lead to more transistors. GPU's can use those extra transistors because their workload is embarrassingly parallel (thousands of parallel things), but CPU's can't because their workload is mostly sequential (developers have to explicitly write code for every thread to do something useful, and find this hard to do). You can see the clock rates peaking with the Pentium 4, crashing when that design proved a dead end, and then plateauing: https://i.stack.imgur.com/z94Of.png https://i.stack.imgur.com/z94Of.png
IPC improvements are still happening, which is why Intel has been on 14nm for years and still makes CPU's every year that are a little bit faster, but they are hard to do and you only get incremental improvements.
If someone could figure out a way to write regular software that easily parallelized to hundreds of cores, CPU's could also get the same leaps in performance that GPU's have been enjoying. It's a software problem more than it is a hardware problem.
- ksec 7y ago>If someone could figure out a way to write regular software that easily parallelized to hundreds of cores, CPU's could also get the same leaps in performance that GPU's have been enjoying. It's a software problem more than it is a hardware problem. Amdahl's law [1] , and while we have demonstrate parallelised code can speed things up, generally speaking Software performance still have lots of low hanging fruit without even going deep into parallel and concurrency world, it is just a matter of cost whether it is worthwhile to improve or fix it. [1] https://en.wikipedia.org/wiki/Amdahl%27s_law https://en.wikipedia.org/wiki/Amdahl%27s_law