On Sat, 02 May 2009 04:17:29 -0400, Don <nos...@nospam.com> wrote:
Bill Baxter wrote:
On Fri, May 1, 2009 at 5:36 PM, bearophile <bearophileh...@lycos.com>
wrote:
Bill Baxter:
Much more often the discussion on the numpy list takes the form of
"how do I make this loop faster" becuase loops are slow in Python so
you have to come up with clever transformations to turn your loop into
array ops. This is thankfully a problem that D array libs do not
have. If you think of it as a loop, go ahead and implement it as a
loop.
Sigh! Already today, and even more tomorrow, this is often false for D
too. In my computer I have a cheap GPU that is sleeping while my D
code runs. Even my other core sleeps. And I am using one core at 32
bits only.
You will need ways to data-parallelize and other forms of parallel
processing. So maybe nornmal loops will not cuti it.
Yeh. If you want to use multiple cores you've got a whole 'nother can
o worms. But at least I find that today most apps seem get by just
fine using a single core. Strange though, aren't you the guy always
telling us how being able to express your algorithm clearly is often
more important than raw performance?
--bb
I confess to being mighty skeptical about the whole multi-threaded,
multi-core thing. I think we're going to find that there's only two
practical uses of multi-core:
(1) embarressingly-parallel operations; and
(2) process-level concurrency.
I just don't believe that apps have as much opportunity for parallelism
as people seem to think. There's just too many dependencies.
Sure, you can (say) with a game, split your AI into a seperate core from
your graphics stuff, but that's only applicable for 2-4 cores. It
doesn't work for 100+ cores.
(Which is why I think that broadening the opportunity for case (1) is
the most promising avenue for actually using a host of cores).
Actually, AI is mostly embarrassingly-parallel. The issue is the mostly
part of that statement, which is why optimized reader/writer locks and STM
are showing up in game engines. And really, >90% of the CPU time has been
physics, which is both embarrassingly-parallel and being off-loaded onto
the GPU/multi-cores.
