similar to: How to get optimization remarks while testing with lnt in llvm

I want to know all the optimization applied by the passes. I found two options in clang 1. -fsave-optimization-record 2. -Rpass-analysis=... However, they have nothing to do with the interaction btw IR files(.ll) Is there any tool that records all optimizations on IR file? -------------- next part -------------- An HTML attachment was scrubbed... URL:

Hi, I am trying to compare the loop vectorizers effectiveness for different targets relative to each other. That way, I am hoping to find loops that are not vectorized - but could be - on my target by finding other targets doing this successfully. With some luck, there might be something in the Target files that could be fixed with improved vectorization as a result... I would like to do

Adam, thanks for all the suggestions! One nice aspect of the `-Rpass` family of options is that I can filter based on what I want. If I only want to see which inlines I missed, I could use `clang -Rpass-missed="inline"`, for example. On the other hand, optimization remark YAML always include remarks from all passes (as far as I can tell), which increases the amount of time it takes

Hello all, During the compilation process, LLVM automatically derives various attributes about functions and values (for example that a pointer is nonnull, a function is constant, etc) that are used within a translation unit. I propose adding a pass to LLVM that allows front-ends to output derived attributes. Such a pass would be useful both for developers and end users to debug programs,

Hi Hal, > On May 10, 2016, at 5:39 PM, Hal Finkel <hfinkel at anl.gov> wrote: > > Hi Adam, > > I think would be a really useful feature to have. I don't think that the backend should be responsible for filtering, but should pass the relative hotness information to the frontend. Given that these diagnostics are not just going to be used for -Rpass and friends, but also

Hi, There was a recent discussion on generating non-temporal stores automatically[1]. This is a hard problem to get right. What seems like a much easier but still useful problem to solve is to provide diagnostics to the user where NT stores *may* help. Then the user can add the corresponding builtins and see if they are beneficial. My hope is that with the work to add profile-driven

> On May 11, 2016, at 3:37 AM, Hal Finkel <hfinkel at anl.gov> wrote: > > ----- Original Message ----- >> From: "Adam Nemet" <anemet at apple.com> >> To: "Hal Finkel" <hfinkel at anl.gov> >> Cc: "llvm-dev (llvm-dev at lists.llvm.org)" <llvm-dev at lists.llvm.org> >> Sent: Wednesday, May 11, 2016 1:15:42 AM

This idea came up a few times recently [1][2] so I’d like start prototyping it. To summarize, we can emit optimization remarks using the -Rpass* options. These are currently emitted by optimizations like vectorization[3], unrolling, inlining and since last week loop distribution. For large programs however this can amount to a lot of diagnostics output to sift through. Filtering this by the

Hi Alex, I think the changes you want are actually not vectorizer related. Vectorizer just uses data provided by other passes. What you probably might want is to look into routine Loop::getStartLoc() (see lib/Analysis/LoopInfo.cpp). If you find a way to improve it, patches are welcome:) Thanks, Michael > On Jun 3, 2016, at 6:13 PM, Alex Susu <alex.e.susu at gmail.com> wrote: >

Hi Alex, This has been very recently fixed by Hal. See http://reviews.llvm.org/rL270771 Adam > On Jun 4, 2016, at 3:13 AM, Alex Susu via llvm-dev <llvm-dev at lists.llvm.org> wrote: > > Hello. > Mikhail, I come back to this older thread. > I need to do a few changes to LoopVectorize.cpp. > > One of them is related to figuring out the exact C source line

Reduction Not Captured By LLVM CODE_1 ------------------------------------------------------------ ------------------------------------------------------------ -------------------- #include <stdio.h> int main() { int sum[1000]={1,2,3,4}; for (int i=1;i<1000;i++) { sum[0] +=sum[i-1]; } }

Hi -- I have found a bug in an HPC code where llvm is vectorizing a loop on Skylake that has an obvious recurrence. I derived a small test case based on the original benchmark below: /*****************************************************************/ static void __attribute__ ((always_inline)) one( const int *restrict in, const int *const end, const unsigned shift, int *const restrict index,

Hello, I m trying to set vector width using #pragma clang loop vectorize_width(32) but i m getting width 8 for the following kernel; #define M 128 #define N 128 #define SQRT_FUN(x) sqrtf(x) int main(int argc, char** argv) { /* Variable declaration/allocation. */ double float_n = (double)N; double data[N*M]; double corr[M*M]; double mean[M]; double stddev[M]; uint32_t

Hello, I'm learning how LLVM performs PGO (profile-guided optimizations) by using the instrumentation-based profile build (-fprofile-instr-generate and -fprofile-instr-use). However, I found there is no difference in inlining behaviors between with and without PGO for a few spec benchmarks by checking the emit optimization reports (-Rpass=inline -Rpass-missed=inline -Rpass-analysis=inline).

> On May 11, 2016, at 10:45 AM, Adam Nemet via llvm-dev <llvm-dev at lists.llvm.org> wrote: > >> >> On May 11, 2016, at 3:37 AM, Hal Finkel <hfinkel at anl.gov <mailto:hfinkel at anl.gov>> wrote: >> >> ----- Original Message ----- >>> From: "Adam Nemet" <anemet at apple.com <mailto:anemet at apple.com>> >>>

I've tried to do: clang++ -O3 -march=native -mtune=native \ -Rpass=loop-vectorize,slp-vectorize -Rpass-missed=loop-vectorize,slp-vectorize -Rpass-analysis=loop-vectorize,slp-vectorize \ -ffast-math -ffp-model=fast -ffp-exception-behavior=ignore -ffp-contract=fast \ -c -o vec.o vec.cc But I've got no feedback. -- Alexandre Bique

Dear community, Our team at IITH have been experimenting with loop-distribution pass in LLVM. We see the following results on few benchmarks. clang -O3 -mllvm -enable-loop-distribute -Rpass=loop-distribute file.c clang -O3 -mllvm -enable-loop-distribute -Rpass-analysis=loop-distribute file.c TORCH

Hi llvm-dev! We are doing some fuzzy testing using C program generators, and one question that came up when generating a program with both floating point arithmetic and loop pragmas was; Is the loop vectorizer really allowed to vectorize a loop when it can't prove that it is safe to reorder fp math, even if there is a loop pragma that hints about a preferred width. When reading here

Dear llvm-dev community, I am trying to analyze the optimization remarks generated through clang using -fsave-optimization-remark with -O3. --- !Analysis Pass: loop-vectorize Name: CFGNotUnderstood DebugLoc: { File: c-ray-mt.c, Line: 177, Column: 2 } Function: main Args: - String: 'loop not vectorized: ' - String: loop control flow is not understood by vectorizer I tried to look for

Hi Quentin, You are correct, I could manage to get clang to use vrcpps, but not in a satisfying way: clang++ -O3 -march=native -mtune=native \ -Rpass=loop-vectorize -Rpass-missed=loop-vectorize -Rpass-analysis=loop-vectorize \ -ffast-math -ffp-model=fast -ffp-exception-behavior=ignore -ffp-contract=fast \ -c -o vec.o vec.cc 0000000000000140 <_Z4fct4Dv4_f>: 140: c5 f8 53 c8