similar to: [RFC] Make LoopVectorize Aware of SLP Operations

Hi Florian! This proposal sounds pretty exciting! Integrating SLP-aware loop vectorization (or the other way around) and SLP into the VPlan framework is definitely aligned with the long term vision and we would prefer this approach to the LoopReroll and InstCombine alternatives that you mentioned. We prefer a generic implementation that can handle complicated cases to something ad-hoc for some

Hi, On 08/02/2018 04:22, Caballero, Diego wrote: > Hi Florian! > > This proposal sounds pretty exciting! Integrating SLP-aware loop vectorization (or the other way around) and SLP into the VPlan framework is definitely aligned with the long term vision and we would prefer this approach to the LoopReroll and InstCombine alternatives that you mentioned. We prefer a generic implementation

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

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   ===========

Hi all, At the Barcelona Supercomputing Center, we have been working on an end-to-end vectorizer using scalable vectors for RISC-V Vector extension in context of the EPI Project <https://www.european-processor-initiative.eu/accelerator/>. We earlier shared a demo of our prototype implementation  (https://repo.hca.bsc.es/epic/z/9eYRIF, see below) with the folks involved with LLVM

>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.

The BB vectorizer has an option 'bb-vectorizer-search-limit'. Is there a similar option for the SLP vectorizer? Maybe an analysis pass' scope that can be widen? I have large basic blocks with instructions that should be merged into packed versions. However, the blocks are optimized independently from each other. Now, if the instructions to be merged aren't too far apart the

Revision 190916 Commit message: "Lift alignment restrictions for load/store folding on VINSERTF128/VEXTRACTF128. Fixes PR17268." Actual contents of the commit includes Index: tools/opt/opt.cpp =================================================================== --- tools/opt/opt.cpp (revision 190915) +++ tools/opt/opt.cpp (revision 190916) @@ -462,6 +462,7 @@

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

>it cannot afford large size masks for large vectors So, even a standard way of vectorizing remainder in masked or unmasked fashion wouldn’t work, I suppose. Ouch. I suppose VPlan should be able to model this kind of gigantic remainder vector code (when the time comes). Not pretty at all, though. Now, be fully aware that Direction #2 is really a poor (or rather extremely poor) person’s

Am Fr., 10. Jan. 2020 um 16:10 Uhr schrieb Renato Golin <rengolin at gmail.com>: > On Fri, 3 Jan 2020 at 11:27, Michael Kruse via llvm-dev > <llvm-dev at lists.llvm.org> wrote: > > 1. Candidate selection through cost function > > -------------------------------------------- > > Instead of needing to know which transformation is profitable before > >

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

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

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

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

> 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

Michael, [Sorry that I don't have you in To:. I don't have your addr that I can use since I'm replying through digest.] I'm also sorry that I'm not commenting on the main part of your RFC in this reply. I just want to focus on one thing here. Proposed Loop Optimization Framework ------------------------------------

Hi Arnold, To sum up my intentions, I want to understand how the reduction/induction variable detection works in LLVM, so that I can know better how to detect different patterns in memory, not just the stride vectorization. For instance, even if the relationship between each loop would be complicated, I know that in each loop, all three reads are sequential. So, at least, I could use a

Hi, I have been discussing a bit with Sanjay on how to handle the poor sequences of shufflevector instructions produced by the loop vectorizer and he suggested we bring this up on llvm-dev. I have run into this in the past also and it surprised me to again see (on SystemZ) that the vectorized loop did many seemingly unnecessary shuffles. In this case (see