similar to: [LLVMdev] noalias and alias.scope metadata producers

Hal, Johannes, Thanks for the feedback. I have been digging into this a little bit more and was able to have some of this metadata being generated. Nevertheless, I am confused about the semantics of this metadata. Let me explain: I was expecting the alias metadata to complement the information that alias analysis passes compute. However, it seems that the alias information of the pointers used

Hi there! Greetings! I am wondering how I may be able get these annotations !noalias and !alias.scope to show up- I have a function with restrict added to the arguments but I do not see these intrinsics with clang -emit-llvm. Which pass inserts them? Best, Ram -------------- next part -------------- An HTML attachment was scrubbed... URL:

----- Original Message ----- > From: "Hal Finkel" <hfinkel at anl.gov> > To: "Chandler Carruth" <chandlerc at google.com> > Cc: llvmdev at cs.uiuc.edu > Sent: Thursday, July 16, 2015 1:58:02 AM > Subject: Re: [LLVMdev] Improving loop vectorizer support for loops > with a volatile iteration variable > ----- Original Message ----- > >

".... the problem Mehdi pointed out regarding the missed initializations of array elements, did you comment on that one yet?" What is the initializations of array elements question? I don't remember this question. Please refresh my memory. Thanks. I thought Mehdi's question is more about what are attributes needed for these IR-annotation for other LLVM pass to understand and

<mehdi.amini at apple.com>, Bcc: Subject: Re: [llvm-dev] [RFC][PIR] Parallel LLVM IR -- Stage 0 -- IR extension Reply-To: In-Reply-To: <20170224221713.GA931 at arch-linux-jd.home> Ping. PS. Are there actually people interested in this? We will continue working anyway but it might not make sense to put it on reviews and announce it on the ML if nobody cares. On 02/24,

I assume the referring case is something like below, right? #pragma omp parallel num_threads(n) { #pragma omp critical { x = x + 1; } } If that is the case, the programmer is already writing the code that is not "serial equivalent". Our representation for parallelizer is %t = @llvm.region.entry()["omp.parallel"(),

A quick update, we have been looking through all LLVM passes to identify the impact of "IR-region annotation", and interaction issues with the rest of LoopOpt and scalarOpt, e.g. interaction with vectorization when you have schedule(simd:guided: 64). What are the common properties for optimizer to know on IR-region annotations. We have our implementation working from O0, O1, O2 to O3.

On 03/08/2017 12:44 PM, Johannes Doerfert wrote: > I don't know who pointed it out first but Mehdi made me aware of it at > CGO. I try to explain it shortly. > > Given the following situation (in pseudo code): > > alloc A[100]; > parallel_for(i = 0; i < 100; i++) > A[i] = f(i); > > acc = 1; > for(i = 0; i < 100; i++) > acc = acc *

The IR-region annotation we proposed is as below, there is no @llvm.parallel.for.iterator()..... There is no change to loop CFG. alloc A[100]; %t = call token @llvm.region.entry()["parallel.for"()] for(i = 0; i < 100; i++) { a[i] = f(i); } @llvm.region.exit(%t)() ["end.parallel.for"()] Xinmin -----Original Message----- From: Johannes Doerfert

> On Mar 8, 2017, at 10:55 AM, Mehdi Amini <mehdi.amini at apple.com> wrote: > >> >> On Mar 8, 2017, at 5:36 AM, Johannes Doerfert <doerfert at cs.uni-saarland.de> wrote: >> >> <mehdi.amini at apple.com>, >> Bcc: >> Subject: Re: [llvm-dev] [RFC][PIR] Parallel LLVM IR -- Stage 0 -- IR extension >> Reply-To: >>

On 12 August 2014 18:49, Johannes Doerfert <doerfert at cs.uni-saarland.de> wrote: > I recently submitted a patch to the list [1] which would allow Polly to > extract the dependency distance for each analyzable loop. While the > distance is often not constant but parametric we would also need to > version the vectorized loop based on the actual runtime values. Since this is a

Hi Gerolf, I think we have several (perhaps separable) issues here: 1. Do we have a canonical form for loops, preserved through the optimizer, that allows naturally-constructed loop nests to remain separable? 2. Do we forbid non-lowering transformations that turn vectorizable loops into non-vectorizable loops? 3. How do we detect cases where transformations cause a negative answer to either

This is an RFC to add analyses and transformation passes into LLVM to optimize programs based on an abstract notion of a parallel region. == this is _not_ a proposal to add a new encoding of parallelism == We currently perform poorly when it comes to optimizations for parallel codes. In fact, parallelizing your loops might actually prevent various optimizations that would have been applied

> On Mar 8, 2017, at 11:50 AM, Hal Finkel <hfinkel at anl.gov> wrote: > > > On 03/08/2017 01:24 PM, Tian, Xinmin wrote: >> I assume the referring case is something like below, right? >> >> #pragma omp parallel num_threads(n) >> { >> #pragma omp critical >> { >> x = x + 1; >> } >> }

On 01/11, Daniel Berlin via llvm-dev wrote: > > > > def int_experimental_directive : Intrinsic<[], [llvm_metadata_ty], > > [IntrArgMemOnly], > > "llvm.experimental.directive">; > > > > def int_experimental_dir_qual : Intrinsic<[], [llvm_metadata_ty], > > [IntrArgMemOnly], > >

Dear all, This RFC proposes three new LLVM IR instructions to express high-level parallel constructs in a simple, low-level fashion. For this first stage we prepared two commits that add the proposed instructions and a pass to lower them to obtain sequential IR. Both patches have be uploaded for review [1, 2]. The latter patch is very simple and the former consists of almost only mechanical

Hello, Is there a analysis pass which calculates the ModRefBehaviours OnlyReadsPointerArguments and OnlyAccessesPointerArguments? I tried to find one but so far I only saw that different AA's return OnlyReadsMemory and DoesNotAccessMemory if the readonly and readnone attributes are set. Best regards and thanks in advance, Johannes -- Johannes Doerfert Researcher / PhD Student

After I spend some time working with the function attribute* deduction pass** [1,3], I would like to propose a "proper" organization***. Why? Because we do not derive nearly as many attributes as we could****, while we do maintain various (separate and diffently organized) "data-flow-like analyses" to do so. What else? I propose a single optimistic data-flow

Hi Johannes, Actually, I'm working in the same scenario, i.e. configure + make of a benchmark/program/library like you said. I've got your point of using this script as a replacement to generate .bc files instead of a executable. That's truly helpful and has already answered my original question. Now I'm actually moving a step further. Take the same example in your reply, say, if

Ok, I'll put a patch together to fix this later today. I'll probably do what Reid was suggesting and use what is already in there for Windows. Thanks, Samuel Bill Schmidt <wschmidt at linux.vnet.ibm.com> wrote on 11/04/2014 12:11:08 PM: > From: Bill Schmidt <wschmidt at linux.vnet.ibm.com> > To: Samuel F Antao/Watson/IBM at IBMUS > Cc: azanella at