[CalChris]

Umm, Amdahl's law is actually a negative result. It's saying that if you infinitely improve some magical hotspot that is 1% of your workload, the best you can only ever get to is 99%. If anything, Amdahl is telling us not to grind on trivialities.

[bitwiseand]

If a system performance is profiled as being dominated by 80% A , 19% B and 1 % C. I'd focus on working on A first to get maximum gains. Amdahl's law gives you the backing as to why you should do this.

As a real world example, if an operation involves a network call and you see the RTT dominating the time. You may want to think of ways to avoid the call (caching etc..) if possible to get really good gains.

[analognoise]

That's not how I understood it - I thought it was about the upper limit of theoretical parallelism.

But I'm an EE, so maybe I misunderstood some finer points?

[CalChris]

An upper limit on the benefits. To me, an upper limit is a negative result. When Leon (in Blade Runner) finds out that he only has 4 years to live (an upper bound) he takes it pretty hard.

Amdahl:

  A fairly obvious conclusion which can be drawn at this
  point is that the effort expended on achieving high
  parallel processing rates is wasted unless it is
  accompanied by achievements in sequential processing
  rates of very nearly the same magnitude.

http://www-inst.eecs.berkeley.edu/~n252/paper/Amdahl.pdf

A point made when we read the paper was that Seymour Cray always made sure that his computers were also the fastest scalar computers even though they were sold as vector processors.

[analognoise]

Thank you for the excellent explanation; I will consider it more thoroughly.

I think mathematicians consider an upper limit a positive bound - positive, in the sense of being well defined; you're using negative in the other sense? I actually like that quite a bit.