search for: reductive

Hi Y'all, I have some data in a table with 2 columns. There are two values: "Reduction" and "No Reduction. " I am trying to make a new variable change which recode the combinations from column 1 and 2 into a single number. Here is a snippet from the table: [1,] "NoReduction" "NoReduction" [2,] "Reduction"

Hi all, During the Nov 2016 dev meeting, we had a hackers’ lab session where we discussed some issues about loop idiom recognition, IR representation and cost modelling. I took an action to write up an RFC about introducing reduction intrinsics to LLVM to represent horizontal operations across vectors. Vector reductions have been discussed in the past before, notably here:

On 05/04/2019 09:37, Simon Pilgrim via llvm-dev wrote: > On 04/04/2019 14:11, Sander De Smalen wrote: >> Proposed change: >> >> ---------------------------- >> >> In this RFC I propose changing the intrinsics for >> llvm.experimental.vector.reduce.fadd and >> llvm.experimental.vector.reduce.fmul (see options A and B). I also >> propose renaming

Hello again, I've been meaning to follow up on this thread for the last couple of weeks, my apologies for the delay. To summarise the feedback on the proposal for vector.reduce.fadd/fmul: There seems to be consensus to keep the explicit start value to better accommodate chained reductions (as opposed to generating IR that performs the reduction of the first element using extract/fadd/insert

Hi When a reduction instruction is vectorized in a loop, it will be turned into an instruction with vector operands of the same operation type. This new instruction has a special property that can give us more flexibility during instruction selection later: this operation is valid as long as the reduction of all elements of the result vector is identical to the reduction of all elements of its

> On 8 Apr 2019, at 11:37, Simon Moll <moll at cs.uni-saarland.de> wrote: > > Hi, > > On 4/5/19 10:47 AM, Simon Pilgrim via llvm-dev wrote: >> On 05/04/2019 09:37, Simon Pilgrim via llvm-dev wrote: >>> On 04/04/2019 14:11, Sander De Smalen wrote: >>>> Proposed change: >>>> ---------------------------- >>>> In this RFC I

Hi Amara, We also had some discussions on the SVE side of reductions on the main SVE thread, but this description is much more detailed than we had before. I don't want to discuss specifically about SVE, as the spec is not out yet, but I think we can cover a lot of ground until very close to SVE and do the final step when we get there. On 31 January 2017 at 17:27, Amara Emerson via

----- Original Message ----- > From: "Xinliang David Li" <davidxl at google.com> > To: "Cong Hou" <congh at google.com> > Cc: "Hal Finkel" <hfinkel at anl.gov>, "llvm-dev" <llvm-dev at lists.llvm.org> > Sent: Wednesday, November 25, 2015 5:17:58 PM > Subject: Re: [llvm-dev] [RFC] Introducing a vector reduction add

Hi all, While working on a patch to improve codegen for fadd reductions on AArch64, I stumbled upon an outstanding issue with the experimental.vector.reduce.fadd/fmul intrinsics where the accumulator argument is ignored when fast-math is set on the intrinsic call. This behaviour is described in the LangRef (https://www.llvm.org/docs/LangRef.html#id1905) and is mentioned in

On Wed, Nov 25, 2015 at 2:32 PM, Hal Finkel <hfinkel at anl.gov> wrote: > Hi Cong, > > After reading the original RFC and this update, I'm still not entirely sure I understand the semantics of the flag you're proposing to add. Does it having something to do with the ordering of the reduction operations? The flag is only useful for vectorized reduction for now. I'll give

Hi Nadav, Arnold, I managed to find some time to work on the pointer reduction, and I got a patch that can make "canVectorize()" pass. Basically what I do is to teach AddReductionVar() about pointers, saying they don't really have an exit instructions, and that (maybe) the final store is a good candidate (is it?). This makes it recognize the writes and reads, but then

After some attempt to implement reduce-add in LLVM, I found out a easier way to detect reduce-add without introducing new IR operations. The basic idea is annotating phi node instead of add (so that it is easier to handle other reduction operations). In PHINode class, we can add a flag indicating if the phi node is a reduction one (the flag can be set in loop vectorizer for vectorized phi nodes).

+cc Simon who's also interested in reductions for the any_true, all_true predicate vectors. On 31 January 2017 at 20:19, Renato Golin via llvm-dev <llvm-dev at lists.llvm.org> wrote: > Hi Amara, > > We also had some discussions on the SVE side of reductions on the main > SVE thread, but this description is much more detailed than we had > before. > > I don't

Renato, can you post a hand-created vectorized IR of how a reduction would work on your example? I don’t think that recognizing this as a reduction is going to get you far. A reduction is beneficial if the value reduced is only truly needed outside of a loop. This is not the case here (we are storing/loading from the pointer). Your example is something like WRITEPTR = phi i8* [ outsideval,

On 21 October 2013 17:29, Arnold Schwaighofer <aschwaighofer at apple.com>wrote: > I don’t think that recognizing this as a reduction is going to get you > far. A reduction is beneficial if the value reduced is only truly needed > outside of a loop. > This is not the case here (we are storing/loading from the pointer). > Hi Arnold, Nadav, Let me resurrect this discussion a

> If you mean "patterns may not be matched, and reduction instructions will not be generated, making the code worse", then this is just a matter of making the patterns obvious and the back-ends robust enough to cope with it, no? The Back-end should be as robust as possible, I agree. The problem that I see is in adding another kind of complexity to the optimizer that works between the

The ivdep pragma is designed to do exactly what the name states - ignore vector dependencies.  Cray Research first implemented this in 1978 in their CFT compiler, and has supported it since. This pragma is typically used by application developers who want vectorized code when the compiler cannot automatically determine safety; it is not equivalent to the OpenMP SIMD pragma in that the compiler is

Hi All, Renato wrote: >As they say: if it's not broken, don't fix it. >Let's talk about the reductions that AVX512 and SVE can't handle with IR semantics, but let's not change the current IR semantics for no reason. Main problem for SVE: We can't write straight-line IR instruction sequence for reduction last value compute, without knowing #elements in vector to

I have a method: ? def reduceProuctInventoryBy(product_id, reduction) ? ? t=Product.find(:first, :conditions =>["id = ?", product_id]) ? ? t.qty=(t.qty-reduction) ? ? t.save ? end and the model: class Product < ActiveRecord::Base ? validates_presence_of :qty, :specialDescription ? validates_numericality_of :qty end but when i run my method, I get this: "can''t

On Oct 23, 2013, at 3:10 PM, Renato Golin <renato.golin at linaro.org> wrote: > On 23 October 2013 16:05, Arnold Schwaighofer <aschwaighofer at apple.com> wrote: > In the examples you gave there are no reduction variables in the loop vectorizer’s sense. But, they all have memory accesses that are strided. > > This is what I don't get. As far as I understood, a