Hello David, thanks for detailed response!
Do you have any tests that you use to measure the PGO effectiveness? I
have tested clang version 6.0 with the same sample that Jie Chen used in
2016 and actually both frontend-based PGO and IR-based make code run
slower, see the average time:
clang++ -O3: 3.15 sec
clang++ -O3 and -fprofile-instr-use: 3.160 sec
clang++ -O3 and -fprofile-use: 3.180 sec
g++ (7.3.0) -O3: 3.640 sec
g++ (7.3.0) -O3 and -fprofile-use: 2.92 sec
Do you have any idea what can be wrong? Maybe there are some
recommendations in which cases one should use PGO with clang and when it
is better not to do it?
Thanks!
On 02/05/2018 09:38 AM, Xinliang David Li wrote:>
>
> On Sun, Feb 4, 2018 at 9:59 PM, Victor Leschuk
> <vleschuk at accesssoftek.com <mailto:vleschuk at
accesssoftek.com>> wrote:
>
> Hello David!
>
> I have recently started acquaintance with PGO in LLVM/clang and found
> your e-mail thread:
> http://lists.llvm.org/pipermail/llvm-dev/2016-May/099395.html
> <http://lists.llvm.org/pipermail/llvm-dev/2016-May/099395.html> .
> Here you
> posted a nice list of optimizations that use profiling and of those
> which could be using but don't. However that thread is about 2
years
> old. Could you please kindly let me know if there were any significant
> changes in this area since that time?
>
>
>
> Yes, there were quite some changes since then. Here are some of the
> new features:
>
> * LLVM IR based PGO -- this is designed to maximize program
> performance. The option to turn it on is -fprofile-generate/-fprofile-use
> * value profiling support in PGO -- currently support indirect call
> target profiling and memcpy/memset size profiling and optimizations
> * Profile data is made available for inliner to use (enabled only for
> the new pass manager: -fexperimental-new-pass-manager)
> * Profile aware LICM is available -- implemented via a profile driven
> code sinking pass
> * Partial inlining is made profile aware; Graham Yu also added
> support for multiple region function outlining (with PGO)
> * BB layout heuristics are tuned with PGO
> * hotness driven function layout optimization
>
> There are pending work in the following area:
> * profile aware loop vectorization, etc
> * control heigh reduction optimization (Hiroshi is working on this)
>
> ThinLTO also works well with PGO.
>
> Hope this helps.
>
> David
>
> >/What I can tell you is that there are many missing ones (that can
> benefit /from profile): such as profile aware LICM (patch pending),
speculative PRE,
> loop unrolling, loop peeling, auto vectorization, inlining, function
> splitting, function layout, function outlinling, profile driven size
> optimization, induction variable optimization/strength reduction, stringOp
> specialization/optimization/inlining, switch peeling/lowering etc. The
> biggest profile user today include ralloc, BB layout, ifcvt, shrinkwrapping
> etc, but there should be rooms to be improvement there too.
>
>
> Thanks in advance!
>
> --
> Best Regards,
>
> Victor Leschuk | Software Engineer | Access Softek
>
>
--
Best Regards,
Victor Leschuk | Software Engineer | Access Softek
-------------- next part --------------
An HTML attachment was scrubbed...
URL:
<http://lists.llvm.org/pipermail/llvm-dev/attachments/20180207/0be7ebe7/attachment.html>