similar to: Android kernel PGO with LLVM

Hello, When I try to use -fprofile-instr-generate with clang (which is built from source) I am getting following error : ld: file not found: /Users/Mr.Pandya/My_Stuff/Active/llvm/build/bin/../lib/clang/3.9.0/lib/darwin/libclang_rt.profile_osx.a clang-3.9: error: linker command failed with exit code 1 (use -v to see invocation) I am not building compiler RT with LLVM. Am I missing any thing

I was trying to build llvm + clang with cmake cache PGO.cmake and ninja stage2. I used the 4.0.0 final tag vfrom svn. This seems to work for me. I added libcxx, libcxxabi, llld etc. And now I get the following cmake error. -- Performing Test LIBCXX_SUPPORTS_STD_EQ_CXX11_FLAG -- Performing Test LIBCXX_SUPPORTS_STD_EQ_CXX11_FLAG - Failed CMake Error at projects/libcxx/CMakeLists.txt:396

Thank you So it does not seem to be relevant for what I’m trying to do. I’m doing something unconventional. The objective is to implement PGO and code coverage on a system that does not exit and does not have any file io, or any of stdc libraries that libclang-profile is using. (more like a kernel) So what I’m trying to do is instead of calling __llvm_profile_write_file () from the application,

I think this is the same underlying issue as https://bugs.llvm.org/show_bug.cgi?id=40320. CCing Reid, who's had a bunch of thoughts on this in the past. On 1/11/20, 10:25 AM, "llvm-dev on behalf of Chrulski, Christopher M via llvm-dev" <llvm-dev-bounces at lists.llvm.org on behalf of llvm-dev at lists.llvm.org> wrote: Hi, I've run into a bug with the LLVM

Hi This array is defined in compiler-rt: InstrProfilingValue.c but I can’t find where it is used? And the comment on it does not say much about why we need it either. Can someone explain why we need this and where it is used? /* A shared static pool in addition to the vnodes statically * allocated by the compiler. */ COMPILER_RT_VISIBILITY ValueProfNode

I think the simplest, most complete, short term fix, would be to call llvm::colorEHFunclets, and to have the relevant instrumentation passes apply the appropriate funclet bundle when inserting function calls. It's not elegant because it means every simple instrumentation pass that inserts regular function calls (ASan, TSan, MSan, instrprof, etc) needs to be funclet-aware. But, it will work,

What Vedant said -- the profiler runtime provides buffer API for profile dumping. Note that value profiling dumping is not yet supported for buffer API, but since you are using Front-end based instrumentation/profile-use, value profiler is not turned on by default anyway. David On Tue, Dec 19, 2017 at 5:29 PM, Vedant Kumar <vsk at apple.com> wrote: > > On Dec 19, 2017, at 5:16 PM,

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 . 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

On Sun, Feb 4, 2018 at 9:59 PM, Victor Leschuk <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 . Here you > posted a nice list of optimizations that use profiling and of those > which could be using but

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

Hi, all Recently I'm trying to use LLVM PGO and autoFDO. However I have some problems in the process. LLVM source code is updated on April 9th. Operating system is SUSE x86_64 1. Problems in instrumentation based PGO: clang -O2 -fprofile-instr-generate test.c -o a.out ./a.out (then default.profraw is generated) clang -O2 -fprofile-instr-use=default.profraw test.c -o a.out

Victor, thanks for the experiment. My suspicion is it is due to the remaining issues with block layout -- especially with loop rotation (with PGO). Another problem is that tail dup is not happening after loop rotation which can limit the effectiveness of loop rotation. I tried the internal option -mllvm -force-precise-rotation-cost and there is about 10% speedup with -fprofile-use. This option

Hi, I have a question regarding PGO. I collected profile data with the instrumentation build (-fprofile-instr-generate) and provided for PGO optimization in the second build (with -fprofile-instr-use=xxx.profdata). This works fine. Then I tried to provide the profile data to opt using the option -pgo-instr-use, but this causes an error with the message: "Not an IR level instrumentation

David, could you please clarify on which code did you gain 10% improvement? I have run numerous tests with and w/o this option and it looks like it has no effect on performance (I am talking of the old 2016 sample to be concrete). Maybe we could investigate it together? Just tell me where to start? On 02/07/2018 02:11 AM, Xinliang David Li wrote: > Victor, thanks for the experiment. > >

Victor, please file a bug tracking the issue. We can put relevant information there including test cases used in the experiment etc. thanks, David On Wed, Feb 7, 2018 at 2:15 PM, Victor Leschuk <vleschuk at accesssoftek.com> wrote: > David, could you please clarify on which code did you gain 10% > improvement? I have run numerous tests with and w/o this option and it > looks

Yes, that was it! Now that I took a closer look, the guide also states that I should use the stage2 build. Silly me. Thanks! On Tue, 3 Sep 2019 at 19:31, David Blaikie <dblaikie at gmail.com> wrote: > I /guess/ you actually want /path/to/release_build/llvm-profdata because > the profiles are generated from binaries compiled with the release build, > so it's the release build

Hello - I'm an Engineer in Microsoft Office after looking into possible advantages of using PGO for our Android Applications. We at Microsoft have deep experience with Visual C++'s Profile Guided Optimization<https://msdn.microsoft.com/en-us/library/e7k32f4k.aspx> and often see 10% or more reduction in the size of application code loaded after using PGO for key scenarios (e.g.

Hi everyone, As part of my work for Mozilla's Low Level Tools team I've implemented PGO in the Rust compiler. The feature is available since Rust 1.37 [1]. However, so far we have not seen any actual performance gains from enabling PGO for Rust code. Performance even seems to drop 1-3% with PGO enabled. I wonder why that is and I'm hoping that someone here might have experience

> On 2015 May 27, at 07:42, Diego Novillo <dnovillo at google.com> wrote: > > On Tue, May 26, 2015 at 11:47 PM, Lee Hunt <leehu at exchange.microsoft.com> wrote: > >> For example, from reading different pages on how Clang PGO, it’s unclear if >> it does “block reordering” (i.e. moving unexecuted code blocks to a distant >> code page, leaving only ‘hot’

Thanks for testing out LLVM PGO and evaluated the performance. We are currently still more focused on infrastructure improvement which is the foundation for performance improvement. We are making great progress in this direction, but there are still some key missing pieces such as profile data in inliner etc. We are working on that. Once those are done, more focus will be on making more passes