similar to: [LLVMdev] LLVM loop vectorizer

Hi Alex, I'm not aware of efforts on loop coalescing in LLVM, but probably polly can do something like this. Also, one related thought: it might be worth making it a separate pass, not a part of loop vectorizer. LLVM already has several 'utility' passes (e.g. loop rotation), which primarily aims at enabling other passes. Thanks, Michael > On Feb 15, 2016, at 6:44 AM, RCU

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

Proposal for extending the Loop Vectorizer to handle Outer Loops ================================================================ Goal: ----- We propose to extend the innermost Loop Vectorizer to also handle outerloops (cf.[1]). Our aim is to best leverage the efforts already invested in the existing innermost Loop Vectorizer rather than introduce a separate pass dedicated to outerloop

Hello, Anton, I'd like to add a small reply regarding this GSoC project that I would like to mentor and I discussed also with Andrei. A good part of our GSoC project is indeed related to this Connex back end that it's not yet part of the LLVM source repository - an important thing proposed in the project is that we plan to perform efficient realignment for this Connex vector

Amara, >I support this direction Thanks for the support. >but are there actually any real world workloads where gather/scatter scalarisation would be worth it, on any micro-architecture? If we don’t have examples and the compile time cost is non-negligible then I think we’d still like to keep the early >bailouts in some form.’ It's not like I have specific application code in

>Another might be to introduce changes under feature flags to ease the revert/reintroduce/revert cycle. This is essentially the first guard. We plan to have flags/settings to control which types of outer loops are handled. The new code path is initially exclusive to outer loop vectorization. If we disable all types of outer loops (and that's the initial default), LV continues to be good

To revive the discussion around vectorizer testing, here's a quick sample of a few of the issues hit recently in the loop vectorizer.  I want to be careful to say that I am not stating these are the result of any recent work, just that they're issues that have been triaged down to the loop vectorizer doing something incorrect or questionable from a performance perspective.

Hi This looks like a bug in ActiveRecord. I am messing with eager loading (on 12.1) and all of a sudden records started disappearing from a table (and I am not doing anything delete related)!! The following line works OK:- @todos = Todo.find(:all, :include => [ :whens],:order => "position ASC") The following line is mysteriously deleteing :where rows from the DB after

On 01/05/2018 06:28 PM, Saito, Hideki wrote: > Amara, > >> I support this direction > Thanks for the support. > >> but are there actually any real world workloads where gather/scatter scalarisation would be worth it, on any micro-architecture? If we don’t have examples and the compile time cost is non-negligible then I think we’d still like to keep the early >bailouts in

Thanks, Hal. I plan to post a patch w/o HW Legality early bailout first. That should enable further discussion on where the initial very high cost for "illegal masked load/store/gather/scatter" should be coming from --- like should LoopVectorize provide it? Or should it be provided by TTI? I prefer the latter (TTI) but the first revision of the patch will intentionally do the former

Proposal for Outer Loop Vectorization Implementation Plan ============================================= ===== Goal: ===== Extending Loop Vectorizer (LV) such that it can handle outer loops, via VPlan infrastructure enhancements. Understand the trade-offs in trying to make concurrent progress with moving remaining inner loop vectorization functionality to VPlan infrastructure   ===========

Hello. I am trying to create my own LoopVectorize.cpp pass as a separate pass from the LLVM trunk, as described in http://llvm.org/docs/CMake.html#embedding-llvm-in-your-project. Did anybody try something like this? I added close to the end of the .cpp file: /* this line seems to be required - it allows to run this pass as an embedded pass by giving opt -my-loop-vectorize

Hello. Mikhail, with the more recent version of the LoopVectorize.cpp code (retrieved at the beginning of July 2016) I ran the following piece of C code: void foo(long *A, long *B, long *C, long N) { for (long i = 0; i < N; ++i) { C[i] = A[i] + B[i]; } } The vectorized LLVM program I obtain contains 2 vector.body blocks - one named

Hello. My target architecture supports natively 16 bit integers (i16). Whenever I write in C programs using only short types, clang compiles the program to LLVM and converts the i16 data to i32 to perform arithmetic operations and then truncates the results to i16. Then, the InstructionCombining (INSTCOMBINE or IC) pass removes these conversions back and forth from i16, except for

> On 5 Jan 2018, at 21:01, Saito, Hideki via llvm-dev <llvm-dev at lists.llvm.org> wrote: > > > All, > > I'm trying to refactor LoopVectorize such that it has better conformance to VPlan vision going forward > (http://www.llvm.org/docs/Proposals/VectorizationPlan.html). All VP*Recipe class definitions are now > moved to VPlan.h, and I have a patch under review

All, I'm trying to refactor LoopVectorize such that it has better conformance to VPlan vision going forward (http://www.llvm.org/docs/Proposals/VectorizationPlan.html). All VP*Recipe class definitions are now moved to VPlan.h, and I have a patch under review to move LoopVectorizationPlanner class out of LoopVectorize.cpp (https://reviews.llvm.org/D41420). Next thing I'm working on is

Status Update on VPlan ---- where we are currently, and what's ahead of us ==========================================================   Goal: ----- Extending Loop Vectorizer (LV) such that it can handle outer loops, via uplifting its infrastructure with VPlan. The goal of this status update is to summarize the progress and the future steps needed.   Background: ----------- This is related to

Hello. I'm not able to vectorize this simple C loop doing basically what could be called predicated sum-reduction: #define NMAX 1000 int colOccupied[NMAX]; void Func(int N) { int numSol = 0; for (int c = 0; c < N; c++) { if (colOccupied[c] == 0) numSol++; } return numSol; } The compiler

Hi Dave, >> We generate xEXT nodes in many cases. Unlike GCC which vectorizes >> inner loops, we vectorize the implicit outermost loop of data-parallel >> workloads (also called whole function vectorization). We vectorize >> code even if the user uses xEXT instructions, uses mixed types, etc. >> We choose a vectorization factor which is likely to generate more