11 Commits

Author SHA1 Message Date
Philip Reames
2c7786e94a
Prefer use of 0.0 over -0.0 for fadd reductions w/nsz (in IR) (#106770)
This is a follow up to 924907bc6, and is mostly motivated by consistency
but does include one additional optimization. In general, we prefer 0.0
over -0.0 as the identity value for an fadd. We use that value in
several places, but don't in others. So, let's be consistent and use the
same identity (when nsz allows) everywhere.

This creates a bunch of test churn, but due to 924907bc6, most of that
churn doesn't actually indicate a change in codegen. The exception is
that this change enables the use of 0.0 for nsz, but *not* reasoc, fadd
reductions. Or said differently, it allows the neutral value of an
ordered fadd reduction to be 0.0.
2024-09-03 09:16:37 -07:00
Alexey Bataev
70a54bca6f
[SLP]Improve/fix extracts calculations for non-power-of-2 elements.
One of the previous patches introduced initial support for non-power-of-2
number of elements but some parts of the SLP vectorizer still were not
adjusted to handle the costs correctly. Patch fixes it by improving
analysis of the non-power-of-2 number of elements and fixes in the cost
of the extractelements instructions.

Reviewers: RKSimon

Reviewed By: RKSimon

Pull Request: https://github.com/llvm/llvm-project/pull/93213
2024-05-24 09:33:36 -04:00
Jeffrey Byrnes
ea43a30899
[AMDGPU] Vectorize more 16 bit shuffles (#90648)
In the case of larger vectors, we should still prefer the vectorized
version (i.e. shufflevector vs extract/insert chains).

In arithmetic chains, vectorization results in chains of packed math
instructions (as opposed to unpack/repack & scalarized arithmetic):
https://godbolt.org/z/c5onaf6G5

In chains with PHIs, vectorization again removes the unnecessary pack /
repack code around BBs: https://godbolt.org/z/vz7zYzvhs
2024-05-21 09:21:36 -07:00
Roman Lebedev
6697140ba1
[NFC] Port all SLPVectorizer tests to -passes= syntax 2022-12-07 21:44:09 +03:00
Sanjay Patel
79b1b4a581 [Vectorizers][TTI] remove option to bypass creation of vector reduction intrinsics
The vector reduction intrinsics started life as experimental ops, so backend support
was lacking. As part of promoting them to 1st-class intrinsics, however, codegen
support was added/improved:
D58015
D90247

So I think it is safe to now remove this complication from IR.

Note that we still have an IR-level codegen expansion pass for these as discussed
in D95690. Removing that is another step in simplifying the logic. Also note that
x86 was already unconditionally forming reductions in IR, so there should be no
difference for x86.

I spot checked a couple of the tests here by running them through opt+llc and did
not see any asm diffs.

If we do find functional differences for other targets, it should be possible
to (at least temporarily) restore the shuffle IR with the ExpandReductions IR
pass.

Differential Revision: https://reviews.llvm.org/D96552
2021-02-12 08:13:50 -05:00
Juneyoung Lee
9b29610228 Use unary CreateShuffleVector if possible
As mentioned in D93793, there are quite a few places where unary `IRBuilder::CreateShuffleVector(X, Mask)` can be used
instead of `IRBuilder::CreateShuffleVector(X, Undef, Mask)`.
Let's update them.

Actually, it would have been more natural if the patches were made in this order:
(1) let them use unary CreateShuffleVector first
(2) update IRBuilder::CreateShuffleVector to use poison as a placeholder value (D93793)

The order is swapped, but in terms of correctness it is still fine.

Reviewed By: spatel

Differential Revision: https://reviews.llvm.org/D93923
2020-12-30 22:36:08 +09:00
Craig Topper
c195ae2f00 [SLPVectorizer][X86][AMDGPU] Remove fcmp+select to fmin/fmax reduction support.
Previously we could match fcmp+select to a reduction if the fcmp had
the nonans fast math flag. But if the select had the nonans fast
math flag, InstCombine would turn it into a fminnum/fmaxnum intrinsic
before SLP gets to it. Seems fairly likely that if one of the
fcmp+select pair have the fast math flag, they both would.

My plan is to start vectorizing the fmaxnum/fminnum version soon,
but I wanted to get this code out as it had some of the strangest
fast math flag behaviors.
2020-09-10 11:49:19 -07:00
Eric Christopher
cee313d288 Revert "Temporarily Revert "Add basic loop fusion pass.""
The reversion apparently deleted the test/Transforms directory.

Will be re-reverting again.

llvm-svn: 358552
2019-04-17 04:52:47 +00:00
Eric Christopher
a863435128 Temporarily Revert "Add basic loop fusion pass."
As it's causing some bot failures (and per request from kbarton).

This reverts commit r358543/ab70da07286e618016e78247e4a24fcb84077fda.

llvm-svn: 358546
2019-04-17 02:12:23 +00:00
Farhana Aleen
e24f3ff8de [AMDGPU] Support horizontal vectorization of min/max.
Author: FarhanaAleen

Reviewed By: rampitec

Subscribers: AMDGPU

Differential Revision: https://reviews.llvm.org/D46604

llvm-svn: 331920
2018-05-09 21:18:34 +00:00
Farhana Aleen
e2dfe8a853 [AMDGPU] Support horizontal vectorization.
Author: FarhanaAleen

Reviewed By: rampitec, arsenm

Subscribers: llvm-commits, AMDGPU

Differential Revision: https://reviews.llvm.org/D46213

llvm-svn: 331313
2018-05-01 21:41:12 +00:00