search for: vectorise

...[[4]] [1] "D1" "4" etc I am now struggling to work with the prefix identifiers (D1, F1, DDC) because the only way I have figured out to access them is with splitIDs[[i]][1] i.e. it seems like I have to use a loop to get the identifiers into a factor and counted. Is there a vectorised solution someone can suggest? Or an alternative strategy .. these are early days using R for me! Thanks regards M -- View this message in context: http://r.789695.n4.nabble.com/vectorised-recovery-of-strsplit-value-tp3161254p3161254.html Sent from the R help mailing list archive at Nabble....

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...

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

...tion/Loop, and pass those to the Transformation pass as >> part of Analysis's internal data? We've been operating under the assumption that such Analysis pass behavior is unacceptable. > > Hi Saito, > > First let me say, impressive work you guys are planning for the > vectoriser. Outer loop vectorisation is not an easy task, so feel free > to share your ideas early and often, as that would probably mean a lot > less work for you guys, too. > > Regarding generation of dead code, I don't remember any pass doing > this (though I haven't looked at many...

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: We would like the loop vectoriser to emit a new IR intrinsic for certain loops: void @llvm.set.loop.elements.i32(i32 ) This represents th...

...and how good C would be to write masked conditionals. I'm not familiar enough with modern CPUs to judge if this really needs to be addressed or not. I would not doubt that hardware chaining is worth all the efforts the engineers put so the hardware recognises and activates it on the fly. Vectorised chaining implemented in software as a way to spare memory, may be much of a challenge, as it requires sort of half-compilation. One one hand, it might alleviate memory problems which are often the subject of discussions on R-help; through thrashing, going over real memory and into paging may...

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 missed anything here or in another pass I haven't yet considered. I was perhaps also expecti...

...mits it. A warning would be a good thing, though. Now, since it's a warning, I *have* to output something. What? Even considering one compiler, you'll have to convince *most* <compilerX> engineers to agree on something, and that's not trivial. Moreover, this loop is very easy to vectorise, and that would give me 4x speed improvements for 4-way vectorization. That's too much for compilers to pass. If I create a vectorised loop that goes all the way to 92, I'll have to create a tail loop. If I don't want to create a tail loop, I have to override 'b' (and probably...

....58508 > The fold values is calculated from the M column which is a log2 value. The calculation is different depending on whether the M value is negative or positive. That is if the gene is down regulated the reciprocal value has to be used to calculate a fold value. Here is my clunky, not vectorised code : # Function to add a fold column to the toptable ttfold<-function(tt) { fold<-NULL for (i in 1:length(tt$M)) { if (tt$M[i] < 0 ) { fold[i]<-1/(2^tt$M[i]) } else { fold[i]<-2^tt$M[i] } } tt<-cbind(tt, fold) } # Add fold column to top tables topa1<-ttfo...

...uck 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 loop transformations and some stupid vectorization, but having a really good vectoriser is a lot of work. I personally think that the biggest difference is the number of people that have contributed over the years on very specific optimizations. There are as many corner cases as there are particles in the universe (maybe more), and implementing each one of them requires time and peo...

>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

...ed.load/store instructions in the loop. This is what we are currently doing and works excellent for simpler cases. For the more complicated cases that we now what to handle as well, the pattern matching just becomes a bit too horrible, and it is fragile too. All we need is the information that the vectoriser already has, and pass this on somehow. As I am really keen to simply our backend pass, would there be another way to pass this information on? If emitting an intrinsic is a blocker, could this be done with a loop annotation? Cheers, Sjoerd. ________________________________ From: Eli Friedman &lt...

...xity in the back-end to match long patterns for >>> complexity in optimisation passes to know about the new intrinsics. >>> >>> The arguments were: >>> >>> Pro intrinsic: >>> * Simpler and shorter IR >>> * Easier to read, easier for the vectorisers to generate >>> * Easier for the back-end to match >>> * Easier transition towards scalable vectors in the future >> Also want to re-iterate that reductions are useful for testing bits of >> predicate vectors, which can be applicable to other targets than SVE >&gt...