search for: vectorisability

Dear Guru's My first steps with R have ground to a halt! I have a vector of sample identifiers > sampleIDs [1] "D1_1" "D1_2" "D1_3" "D1_4" "D1_5" "D1_6" "D1_7" "D1_8" [9] "D1_9" "D1_10" "D1_11" "D1_12" "F1_13" "F1_14"

I have matrix multiplication and stencil code. I vectorise it through the following command. opt -S -O3 -force-vector-width=2048 stencil.ll -o stencil_o3.ll in both the examples of matrix mult and stencil it vectorises fine when my loop iterations >2048. but if i keep both iterations and vector width=2048. it produces scalar code IR not vectorizes it. Is it llvm bug? Please help me.

Yes, it looks like passing ‘EnableVec’ and ‘EnableSLPVec’ to ‘Args.hasFlag’ should be replaced with ‘false’ and then it has the expected behaviour. MartinO From: cfe-dev [mailto:cfe-dev-bounces at lists.llvm.org] On Behalf Of Martin J. O'Riordan via cfe-dev Sent: 01 March 2018 18:02 To: 'Richard Smith' <richard at metafoo.co.uk> Cc: 'Clang Dev'

Dear all, is there any function to calculate the center of a polygon mass in R? Actually I need to find the best location within polygons to place labels. Thanks for any hint Jens Oehlschl?gel -- COMPUTERBILD 15/03: Premium-e-mail-Dienste im Test\ --------...{{dropped}}

Hi, I have been analyzing the LLVM vectorizer by running some benchmarks. For vectorization, I have used the following flags: -O3 -ffast-math -mavx2 Am I missing any other flags which will improve vectorizer performance? Thanks, Santanu Das IIT Hyd -------------- next part -------------- An HTML attachment was scrubbed... URL:

Please ignore this thread - I got myself confused, the code is fine - too many long days and nights staring at code. There is an issue, but it is different to what I thought. My command line is not: clang -S -O3 -fno-vectorize -fno-slp-vectorize foo.c but: clang -S -fno-vectorize -fno-slp-vectorize -O3 foo.c The difference was subtly hidden in a much longer argument list

Hi Hideki, Thanks for the interesting writeup! > On Aug 27, 2016, at 7:15 AM, Renato Golin via llvm-dev <llvm-dev at lists.llvm.org> wrote: > > On 25 August 2016 at 05:46, Saito, Hideki via llvm-dev > <llvm-dev at lists.llvm.org> wrote: >> Now, I have one question. Suppose we'd like to split the vectorization decision as an Analysis pass and vectorization

No, I’m wrong. I think that bug is actually in ‘hasFlag’ itself. In ‘llvm/lib/Option/ArgList.cpp’ line #70: bool ArgList::hasFlag(OptSpecifier Pos, OptSpecifier PosAlias, OptSpecifier Neg, bool Default) const { if (Arg *A = getLastArg(Pos, PosAlias, Neg)) return A->getOption().matches(Pos) || A->getOption().matches(PosAlias); return

Hello, We are working on predication for our vector extension (MVE). Since quite a few people are working on predication and different forms of it (e.g. SVE, RISC-V, NEC), I thought I would share what we would like to add to the loop vectoriser. Hopefully it's just a minor one and not intrusive, but could be interesting and useful for others, and feedback on this is welcome of course. TL;DR:

Hi, people. Allow me to chat a tiny bit on two vectorisation-related matters, in the context of R. I'm curious about if the following ideas have ever been considered, and rejected already. First is about using the so-called Duff's device for partially unrolling loops. I did not overly check in R sources, and am not familiar with them anyway, but the only usage I saw is within

Hi All, is there any chance of vectorising the two ifelse() statements in the following code: for(i in gp){ new[i,1] = ifelse(srow[i]>0, new[srow[i],zippo[i]], sample(1:100, 1, prob =Y1, rep = T)) new[i,2] = ifelse(drow[i]>0, new[drow[i]>0,zappo[i]], sample(1:100, 1, prob =Y1, rep = T)) } Where I am forced to check if the value of drow and srow are >0 for each line... in

Xinmin, > Tom, your understanding is correct per OpenMP SIMD model. Our implementation behaves as you stated. > Which is not part of LLVM main trunk yet. Is that the implementation that is based on the intrinsics in the RFC you and Hal Finkel had sent out to the list? Or is it a different implementation (and if so, is there some plan to merge the two)? Thanks, --Vikram Adve //

Hello, Quick question to see if I haven't missed anything: I would like convert counting down loops, i.e. loops with a constant -1 step value, to counting up loops, because the vectoriser is able to better deal with these loops (see e.g. D76838 that I was discussing today with Ayal). It looks like LoopSimplifyCFG and IndVarSimplify don't do this. So was just curious if I haven't

On 1 July 2015 at 17:15, Russell Wallace <russell.wallace at gmail.com> wrote: > I'm proposing that LLVM unilaterally replace most undefined behaviour with > implementation-defined behaviour. That's precisely the problem. Which behaviour? Let's have an example: struct Foo { long a[95]; char b[4]; double c[2]; }; void fuzz(Foo &F) { for (int i=0; i<100;

Hi R guru coders I wrote a bit of code to add a new column onto a "topTable" dataframe. That is a list of genes processed using the limma package. I used a for loop but I kept feeling there was a better way using a more vector oriented approach. I looked at several commands such as "apply", "by" etc but could not find a good way to do it. I have this feeling there

On 11 March 2011 14:53, Duncan Sands <baldrick at free.fr> wrote: > There's no magic bullet.  The things to improve that would give you the most > bang for your buck are probably the code generator and auto-vectorization. > Increasing the number of developers would be helpful. I'm not a GCC expert, but their auto-vectorization is not that great. It may be simple to do basic

>From: Sundar Dorai-Raj <sundar.dorai-raj at PDF.COM> >Reply-To: sundar.dorai-raj at PDF.COM >To: Zhen Pang <nusbj at hotmail.com> >CC: r-help at stat.math.ethz.ch >Subject: Vectorising and loop (was Re: [R] optim "a log-likelihood >function") >Date: Wed, 29 Sep 2004 18:21:17 -0700 > > > >Zhen Pang wrote: > >> >>I also use

Hi, Gerolf. We've been a bit quiet for some time. After listening to feedback on the project internally and externally, we decided to take a more generally accepted community development model ---- building up through a collection of small incremental changes ---- than trying to make a big step forward. That change of course took a bit of time, but we are getting close to the first NFC patch

Hi Eli, > The problem with your proposal, as written, is that the vectorizer is producing the intrinsic. Because we don’t impose any ordering on optimizations before codegen, every optimization pass in LLVM would have to be taught to preserve any @llvm.set.loop.elements.i32 whenever it makes any change. This is completely impractical because the intrinsic isn’t related to anything

Yes, SVE can vectorize early exit loops by using speculative (first-faulting) loads, which essentially give a predicate of the lanes loaded successfully. For uncounted loops with these special loads, the loop predicate tests can be done using a 'ptest' instruction, checking if the last element is active. Amara On 3 February 2017 at 10:15, Simon Pilgrim <llvm-dev at redking.me.uk>