similar to: Query on unswitching + vectorization

On 5/10/2018 10:44 PM, Gopalasubramanian, Ganesh via llvm-dev wrote: > > Hi, > > I am going through analysis on unswitching + vectorization. > > For the below test, llvm unswitches successfully but fails to > vectorize the loop after unswitching. > > Llvm bails out saying “Found an outside user” apparently which is the > value of ‘tmp’. > > int i, w, x[1000],

* Looks like some sort of pass ordering issue; it will vectorize if indvars runs sometime between loop unswitch and the vectorizer. That insight is helpful. I scheduled Canonicalization of induction variable before loop vectorization and could get the loop vectorized. The indvars are heavily dependent on SCEV. If there a scalar like tmp which is of real type, we may not be able to get the

Is there any written description of what "non trivialness" is there? On Sun, Apr 29, 2018, 2:49 PM Chandler Carruth via llvm-dev < llvm-dev at lists.llvm.org> wrote: > One of the last big missing pieces for the new PM is enabling non-trivial > loop unswitch at O3. > > The pass is now working well and passing all the testing I have done as > well as some others'

One of the last big missing pieces for the new PM is enabling non-trivial loop unswitch at O3. The pass is now working well and passing all the testing I have done as well as some others' testing (thanks Fedor!) so it should be ready to be enabled. I've done preliminary benchmarking on the test suite and SPEC and haven't seen any interesting regressions and quite a few improvements.

Cool, thanks for debugging this issue and letting us know. We have a few patches to fix this issue: - Introduce freeze in IR: https://reviews.llvm.org/D29011 - Lowering freeze: https://reviews.llvm.org/D29014 - Fix loop unswitch: https://reviews.llvm.org/D29015 Bonus patches to recover perf: - Be less conservative in loop unswitching: https://reviews.llvm.org/D29016 - Instcombine support

The issue blocks another optimization patch and Wei has spent huge amount of effort isolating the the bootstrap failure to this same problem. I agree with Wei that other developers may also get hit by the same issue and the cost of leaving this issue open for long can be very high to the community. David On Mon, Jul 17, 2017 at 10:01 AM, Wei Mi <wmi at google.com> wrote: > Sanjoy and

> cmpq %rbx, %r14 > jne .LBB0_1 > > LLVM can perform compare-jump fusion, it already does in certain cases, but > not in the case above. We can remove the cmp above if we were to perform > the following transformation: Do you mean branch-fusion (https://en.wikichip.org/wiki/macro-operation_fusion)? Is there any more limitation why these two or not fused? > -----Original

Hello, Recently I've come across two instances where Induction Variable Simplification lead to noticable performance regressions. In one case, the removal of extra IV lead to the inability to reschedule instructions in a tight loop to reduce stalls. In that case, there were enough registers to spare, so using extra register for extra induction variable was preferable since it reduced

Hi, I'm surprised by the result of compiling the following lines of code: for (int i = 0; i < RANDOM_CHUNKS; i++) { for (int j = 0; j < RANDOM_CHUNK_SIZE; j++) { random_text[i][j] = (int)(ran()*256); } } The problem happens when -fsanitize=undefined, -fno-sanitize-recover and -O3 are enabled. In this case, UndefinedBehaviorSanitizer inserts check for array index out of

Hi all, I would like to propose an improvement of the “almost dead” block elimination in Transforms/Local.cpp so that it will preserve the canonical loop form for loops with a volatile iteration variable. *** Problem statement Nested loops in LCALS Subset B (https://codesign.llnl.gov/LCALS.php) are not vectorized with LLVM -O3 because the LLVM loop vectorizer fails the test whether the loop

Hi all, In light of recent discussions regarding updating passes to respect convergent semantics, and whether or not it is sufficient for barriers, I would like to propose a change in convergent semantics that should resolve a lot of the identified problems regarding loop unrolling, loop unswitching, etc. Credit to John McCall for talking this over with me and seeding the core ideas. Today,

----- Original Message ----- > From: "Chandler Carruth" <chandlerc at google.com> > To: "Hyojin Sung" <hsung at us.ibm.com>, llvmdev at cs.uiuc.edu > Sent: Wednesday, July 15, 2015 7:34:54 PM > Subject: Re: [LLVMdev] Improving loop vectorizer support for loops > with a volatile iteration variable > On Wed, Jul 15, 2015 at 12:55 PM Hyojin Sung

> On Sep 14, 2015, at 12:15 PM, Philip Reames <listmail at philipreames.com> wrote: > > On 09/04/2015 01:25 PM, Owen Anderson via llvm-dev wrote: >> Hi all, >> >> In light of recent discussions regarding updating passes to respect convergent semantics, and whether or not it is sufficient for barriers, I would like to propose a change in convergent semantics that

----- Original Message ----- > From: "Chandler Carruth" <chandlerc at google.com> > To: "Hal Finkel" <hfinkel at anl.gov> > Cc: "Hyojin Sung" <hsung at us.ibm.com>, llvmdev at cs.uiuc.edu > Sent: Thursday, July 16, 2015 1:06:03 AM > Subject: Re: [LLVMdev] Improving loop vectorizer support for loops > with a volatile iteration

I am attempting to implement a minor loop strength reduction optimization for targets that support compare and jump fusion, specifically TTI::canMacroFuseCmp(). My approach might be wrong; however, I am soliciting the idea for feedback, so that I can implement this correctly. My plan is to add a Supplemental LSR formula to LoopStrengthReduce.cpp that optimizes the following case, but perhaps

On Mon, Jul 17, 2017 at 5:11 PM, Wei Mi <wmi at google.com> wrote: > On Mon, Jul 17, 2017 at 2:09 PM, Sanjoy Das > <sanjoy at playingwithpointers.com> wrote: >> Hi, >> >> On Mon, Jul 17, 2017 at 1:56 PM, Daniel Berlin via llvm-dev >> <llvm-dev at lists.llvm.org> wrote: >>> >>> >>> On Mon, Jul 17, 2017 at 1:53 PM, Wei Mi

Hi Hal, I see. So LSR could theoretically counteract undesirable Ind Var transformations but it's not implemented at the moment? I think I've managed to come up with a small reproducer that can also exhibit similar problem on x86, here it is: https://godbolt.org/z/_wxzut As you can see, when rewriteLoopExitValues is not disabled Clang generates worse code due to additional spills,

Hi Jingyue, I consider it a very important element of the design of convergent that it does not require baseline LLVM to contain a definition of uniformity, which would itself pull in a definition of SIMT/SPMD, warps, threads, etc. The intention is that it should be a conservative (but hopefully not too conservative) approximation, and that implementations of specific GPU programming models

On Jul 29, 2013, at 9:05 AM, Krzysztof Parzyszek <kparzysz at codeaurora.org> wrote: > On 7/16/2013 11:38 PM, Andrew Trick wrote: >> Since introducing the new TargetTransformInfo analysis, there has been some confusion over the role of target heuristics in IR passes. A few patches have led to interesting discussions. >> >> To centralize the discussion, until we get

For the example code below, int L = M + 10; for (k = 1 ; k <=L; k++) { dummy(); if (k < M) dummy2(); } , we can split the loop into two parts like : for (k = 1 ; k != M; k++) { dummy(); dummy2(); } for (; k <=L; k++) { dummy(); } By splitting the loop, we can remove the conditional block in the loop and indirectly increase vectorization