On 12/23/2009 10:40 PM, retard wrote:
Wed, 23 Dec 2009 12:02:53 -0500, bearophile wrote:
Leandro Lucarella:
bearophile, el 23 de diciembre a las 00:13 me escribiste:
Compared to GCC LLVM lacks vectorization (this can be important for
certain heavy numerical computing code), profile-guided optimization
(this is usually less important, it's uncommon that it gives more
than 5-25% performance improvement)
I don't know if that are accurate numbers, but 5-25% looks like a *lot*
to me.
Vectorization can improve 2X or 3X+ the performance of certain code
(typical example: matrix multiplication done right).
Performance differences start to matter in practice when they are 2X or
more. In most situations users aren't able to appreciate a 20%
performance improvement of an application. (But small improvements are
important for the compiler devs because they are cumulative, so many
small improvements may eventually lead some a significant difference).
Aren't able to appreciate? Where are those numbers pulled from?
Autovectorization mostly deals with expression optimizations in loops.
You can easily calculate how much faster some code runs when it uses e.g.
SSE2 instructions instead of plain old x86 instructions.
I think you miss the point, he said vectorization was a big deal. The
numbers on profile guided optimization seem a bit odd though.
LLVM devs are also very nice people, they help me when I have a problem,
and they even implement large changes I ask them, often in a short
enough time. Helping them is fun. This means that probably the compiler
will keep improving for some more time, because in open source projects
the quality of the community is important.
And GCC devs aren't nice people? They won't help you if you have a
problem? Helping them isn't fun? GCC won't keep improving because it's
open source? You make no sense. How much do the LLVM devs pay you for
advertising them?
LLVM is way younger than GCC. In my experiments, I get mostly better
performance out of clang than out of gcc. Working with LLVM seems like
more fun to me.
