By: Gabriele Svelto (gabriele.svelto.delete@this.gmail.com), January 23, 2017 4:23 am
Room: Moderated Discussions
RichardC (tich.delete@this.pobox.com) on January 22, 2017 7:54 am wrote:
> I think there's a usefully large class of scientific-computing applications where the Amdahl's
> Law CPU-to-GPU constraint is relaxed as the scale of the problem increases. CFD for weather
> prediction is probably one of them: in that case, you don't build a new supercomputer to solve the
> same scale of problem in a shorter elapsed time - you build a new supercomputer so that you can use a
> finer grid and thus deal with a much larger computational problem in the same elapsed time.
> If the amount of scalar/CPU work scales up less then the amount of vector/GPGPU work, then this
> allows you to sidestep Amdahl's Law.
That's called Gustafson's law
> I think there's a usefully large class of scientific-computing applications where the Amdahl's
> Law CPU-to-GPU constraint is relaxed as the scale of the problem increases. CFD for weather
> prediction is probably one of them: in that case, you don't build a new supercomputer to solve the
> same scale of problem in a shorter elapsed time - you build a new supercomputer so that you can use a
> finer grid and thus deal with a much larger computational problem in the same elapsed time.
> If the amount of scalar/CPU work scales up less then the amount of vector/GPGPU work, then this
> allows you to sidestep Amdahl's Law.
That's called Gustafson's law