27 Commits

Author SHA1 Message Date
Nikita Popov
580210a0c9 [SLP] Convert some tests to opaque pointers (NFC) 2022-12-23 10:02:57 +01:00
Roman Lebedev
6697140ba1
[NFC] Port all SLPVectorizer tests to -passes= syntax 2022-12-07 21:44:09 +03:00
Alexey Bataev
2ec51f1c75 [SLP]Improve analysis of same/alternate code ops and scheduling.
Should improve compile time for analysis and vectorization.

Metric: SLP.NumVectorInstructions

Program                                                                                       SLP.NumVectorInstructions
test-suite :: External/SPEC/CINT2017speed/623.xalancbmk_s/623.xalancbmk_s.test  6380.00                   6378.00 -0.0%
test-suite :: External/SPEC/CINT2017rate/523.xalancbmk_r/523.xalancbmk_r.test   6380.00                   6378.00 -0.0%
test-suite :: External/SPEC/CINT2006/483.xalancbmk/483.xalancbmk.test           2023.00                   2022.00 -0.0%
test-suite :: External/SPEC/CINT2006/471.omnetpp/471.omnetpp.test               148.00                    146.00 -1.4%

Generated more vector instructions.

Differential Revision: https://reviews.llvm.org/D127531
2022-10-27 16:29:16 -07:00
Alexey Bataev
8ce0c7b1c9 Revert "[SLP]Improve analysis of same/alternate code ops and scheduling."
This reverts commit dad64448c66975054d3d968232652a56eb93b451 to fix
a crash in https://lab.llvm.org/buildbot/#/builders/74/builds/14584
2022-10-27 15:21:35 -07:00
Alexey Bataev
dad64448c6 [SLP]Improve analysis of same/alternate code ops and scheduling.
Should improve compile time for analysis and vectorization.

Metric: SLP.NumVectorInstructions

Program                                                                                       SLP.NumVectorInstructions
test-suite :: External/SPEC/CINT2017speed/623.xalancbmk_s/623.xalancbmk_s.test  6380.00                   6378.00 -0.0%
test-suite :: External/SPEC/CINT2017rate/523.xalancbmk_r/523.xalancbmk_r.test   6380.00                   6378.00 -0.0%
test-suite :: External/SPEC/CINT2006/483.xalancbmk/483.xalancbmk.test           2023.00                   2022.00 -0.0%
test-suite :: External/SPEC/CINT2006/471.omnetpp/471.omnetpp.test               148.00                    146.00 -1.4%

Generated more vector instructions.

Differential Revision: https://reviews.llvm.org/D127531
2022-10-27 11:31:18 -07:00
Arthur Eubanks
f3a928e233 [opt] Don't translate legacy -analysis flag to require<analysis>
Tests relying on this should explicitly use -passes='require<analysis>,foo'.
2022-10-07 14:54:34 -07:00
Philip Reames
48cc9287f5 Reapply "[SLP] Schedule only sub-graph of vectorizable instructions"" (try 3)
The original commit exposed several missing dependencies (e.g. latent bugs in SLP scheduling).  Most of these were fixed over the weekend and have had several days to bake.  The last was fixed this morning after being noticed in manual review of test changes yesterday.  See the review thread for links to each change.

Original commit message follows:

SLP currently schedules all instructions within a scheduling window which stretches from the first instruction potentially vectorized to the last. This window can include a very large number of unrelated instructions which are not being considered for vectorization. This change switches the code to only schedule the sub-graph consisting of the instructions being vectorized and their transitive users.

This has the effect of greatly reducing the amount of work performed in large basic blocks, and thus greatly improves compile time on degenerate examples. To understand the effects, I added some statistics (not planned for upstream contribution). Here's an illustration from my motivating example:

   Before this patch:

   704357 SLP                          - Number of calcDeps actions
   699021 SLP                          - Number of schedule calls
   5598 SLP                          - Number of ReSchedule actions
   59 SLP                          - Number of ReScheduleOnFail actions
   10084 SLP                          - Number of schedule resets
   8523 SLP                          - Number of vector instructions generated

   After this patch:

   102895 SLP                          - Number of calcDeps actions
   161916 SLP                          - Number of schedule calls
   5637 SLP                          - Number of ReSchedule actions
   55 SLP                          - Number of ReScheduleOnFail actions
   10083 SLP                          - Number of schedule resets
   8403 SLP                          - Number of vector instructions generated

I do want to highlight that there is a small difference in number of generated vector instructions. This example is hitting the bailout due to maximum window size, and the change in scheduling is slightly perturbing when and how we hit it. This can be seen in the RescheduleOnFail counter change. Given that, I think we can safely ignore.

The downside of this change can be seen in the large test diff. We group all vectorizable instructions together at the bottom of the scheduling region. This means that vector instructions can move quite far from their original point in code. While maybe undesirable, I don't see this as being a major problem as this pass is not intended to be a general scheduling pass.

For context, it's worth noting that the pre-scheduling that SLP does while building the vector tree is exactly the sub-graph scheduling implemented by this patch.

Differential Revision: https://reviews.llvm.org/D118538
2022-03-25 10:39:23 -07:00
Philip Reames
deae979a2c Revert "Reapply "[SLP] Schedule only sub-graph of vectorizable instructions"""
This reverts commit 738042711bc08cde9135873200b1d088e6cf11c3. A second, apparently separate, issue has been reported on the original review.
2022-03-03 11:35:34 -08:00
Philip Reames
738042711b Reapply "[SLP] Schedule only sub-graph of vectorizable instructions""
Root issue which triggered the revert was fixed in 689bab.  No changes in the reapplied patch.

Original commit message follows:

SLP currently schedules all instructions within a scheduling window which stretches from the first instr
uction potentially vectorized to the last. This window can include a very large number of unrelated instruct
ions which are not being considered for vectorization. This change switches the code to only schedule the su
b-graph consisting of the instructions being vectorized and their transitive users.

This has the effect of greatly reducing the amount of work performed in large basic blocks, and thus greatly improves compile time on degenerate examples. To understand the effects, I added some statistics (not planned for upstream contribution). Here's an illustration from my motivating example:

    Before this patch:

    704357 SLP                          - Number of calcDeps actions
     699021 SLP                          - Number of schedule calls
       5598 SLP                          - Number of ReSchedule actions
         59 SLP                          - Number of ReScheduleOnFail actions
      10084 SLP                          - Number of schedule resets
       8523 SLP                          - Number of vector instructions generated

    After this patch:

    102895 SLP                          - Number of calcDeps actions
     161916 SLP                          - Number of schedule calls
       5637 SLP                          - Number of ReSchedule actions
         55 SLP                          - Number of ReScheduleOnFail actions
      10083 SLP                          - Number of schedule resets
       8403 SLP                          - Number of vector instructions generated

I do want to highlight that there is a small difference in number of generated vector instructions. This example is hitting the bailout due to maximum window size, and the change in scheduling is slightly perturbing when and how we hit it. This can be seen in the RescheduleOnFail counter change. Given that, I think we can safely ignore.

The downside of this change can be seen in the large test diff. We group all vectorizable instructions together at the bottom of the scheduling region. This means that vector instructions can move quite far from their original point in code. While maybe undesirable, I don't see this as being a major problem as this pass is not intended to be a general scheduling pass.

For context, it's worth noting that the pre-scheduling that SLP does while building the vector tree is exactly the sub-graph scheduling implemented by this patch.

Differential Revision: https://reviews.llvm.org/D118538
2022-03-02 10:47:20 -08:00
Arthur Eubanks
9c6250ee41 Revert "[SLP] Schedule only sub-graph of vectorizable instructions"
This reverts commit 0539a26d91a1b7c74022fa9cf33bd7faca87544d.

Causes a miscompile, see comments on D118538.

Required updating bottom-to-top-reorder.ll.
2022-03-01 17:31:16 -08:00
Philip Reames
0539a26d91 [SLP] Schedule only sub-graph of vectorizable instructions
SLP currently schedules all instructions within a scheduling window which stretches from the first instruction potentially vectorized to the last. This window can include a very large number of unrelated instructions which are not being considered for vectorization. This change switches the code to only schedule the sub-graph consisting of the instructions being vectorized and their transitive users.

This has the effect of greatly reducing the amount of work performed in large basic blocks, and thus greatly improves compile time on degenerate examples. To understand the effects, I added some statistics (not planned for upstream contribution). Here's an illustration from my motivating example:

Before this patch:

704357 SLP                          - Number of calcDeps actions
 699021 SLP                          - Number of schedule calls
   5598 SLP                          - Number of ReSchedule actions
     59 SLP                          - Number of ReScheduleOnFail actions
  10084 SLP                          - Number of schedule resets
   8523 SLP                          - Number of vector instructions generated

After this patch:

102895 SLP                          - Number of calcDeps actions
 161916 SLP                          - Number of schedule calls
   5637 SLP                          - Number of ReSchedule actions
     55 SLP                          - Number of ReScheduleOnFail actions
  10083 SLP                          - Number of schedule resets
   8403 SLP                          - Number of vector instructions generated

I do want to highlight that there is a small difference in number of generated vector instructions. This example is hitting the bailout due to maximum window size, and the change in scheduling is slightly perturbing when and how we hit it. This can be seen in the RescheduleOnFail counter change. Given that, I think we can safely ignore.

The downside of this change can be seen in the large test diff. We group all vectorizable instructions together at the bottom of the scheduling region. This means that vector instructions can move quite far from their original point in code. While maybe undesirable, I don't see this as being a major problem as this pass is not intended to be a general scheduling pass.

For context, it's worth noting that the pre-scheduling that SLP does while building the vector tree is exactly the sub-graph scheduling implemented by this patch.

Differential Revision: https://reviews.llvm.org/D118538
2022-02-22 10:15:55 -08:00
Simon Pilgrim
fe6c11c571 [CostModel][X86] Improve f64/v2f64/v4f64 FMUL costs on AVX1 targets to account for slower btver2
BTVER2 has a weaker f64 multiplier that other AVX1-era targets, so we need to bump the worst case cost slightly - llvm-mca reports the new vectorization in simplebb is beneficial on btver2, bdver2 and sandybridge AVX1 targets
2021-05-21 18:12:13 +01:00
Arthur Eubanks
691c086d15 [NewPM][BasicAA] basicaa -> basic-aa in Transforms/SLPVectorizer
Following https://reviews.llvm.org/D82607.

Reviewed By: ychen

Differential Revision: https://reviews.llvm.org/D82681
2020-06-26 14:58:41 -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
Simon Pilgrim
9929f90740 [X86][SSE] Reduce FADD/FSUB/FMUL costs on later targets (PR36280)
Agner's tables indicate that for SSE42+ targets (Core2 and later) we can reduce the FADD/FSUB/FMUL costs down to 1, which should fix the Himeno benchmark.

Note: the AVX512 FDIV costs look rather dodgy, but this isn't part of this patch.

Differential Revision: https://reviews.llvm.org/D43733

llvm-svn: 326133
2018-02-26 22:10:17 +00:00
Sanjay Patel
e6143904b9 revert r325515: [TTI CostModel] change default cost of FP ops to 1 (PR36280)
There are too many perf regressions resulting from this, so we need to 
investigate (and add tests for) targets like ARM and AArch64 before 
trying to reinstate.

llvm-svn: 325658
2018-02-21 01:42:52 +00:00
Sanjay Patel
3e8a76abfd [TTI CostModel] change default cost of FP ops to 1 (PR36280)
This change was mentioned at least as far back as:
https://bugs.llvm.org/show_bug.cgi?id=26837#c26
...and I found a real program that is harmed by this: 
Himeno running on AMD Jaguar gets 6% slower with SLP vectorization:
https://bugs.llvm.org/show_bug.cgi?id=36280
...but the change here appears to solve that bug only accidentally.

The div/rem costs for x86 look very wrong in some cases, but that's already true, 
so we can fix those in follow-up patches. There's also evidence that more cost model
changes are needed to solve SLP problems as shown in D42981, but that's an independent 
problem (though the solution may be adjusted after this change is made).

Differential Revision: https://reviews.llvm.org/D43079

llvm-svn: 325515
2018-02-19 16:11:44 +00:00
Sanjay Patel
574fb73c89 [SLPVectorizer] auto-generate complete checks; NFC
llvm-svn: 324616
2018-02-08 15:32:28 +00:00
David Blaikie
a79ac14fa6 [opaque pointer type] Add textual IR support for explicit type parameter to load instruction
Essentially the same as the GEP change in r230786.

A similar migration script can be used to update test cases, though a few more
test case improvements/changes were required this time around: (r229269-r229278)

import fileinput
import sys
import re

pat = re.compile(r"((?:=|:|^)\s*load (?:atomic )?(?:volatile )?(.*?))(| addrspace\(\d+\) *)\*($| *(?:%|@|null|undef|blockaddress|getelementptr|addrspacecast|bitcast|inttoptr|\[\[[a-zA-Z]|\{\{).*$)")

for line in sys.stdin:
  sys.stdout.write(re.sub(pat, r"\1, \2\3*\4", line))

Reviewers: rafael, dexonsmith, grosser

Differential Revision: http://reviews.llvm.org/D7649

llvm-svn: 230794
2015-02-27 21:17:42 +00:00
David Blaikie
79e6c74981 [opaque pointer type] Add textual IR support for explicit type parameter to getelementptr instruction
One of several parallel first steps to remove the target type of pointers,
replacing them with a single opaque pointer type.

This adds an explicit type parameter to the gep instruction so that when the
first parameter becomes an opaque pointer type, the type to gep through is
still available to the instructions.

* This doesn't modify gep operators, only instructions (operators will be
  handled separately)

* Textual IR changes only. Bitcode (including upgrade) and changing the
  in-memory representation will be in separate changes.

* geps of vectors are transformed as:
    getelementptr <4 x float*> %x, ...
  ->getelementptr float, <4 x float*> %x, ...
  Then, once the opaque pointer type is introduced, this will ultimately look
  like:
    getelementptr float, <4 x ptr> %x
  with the unambiguous interpretation that it is a vector of pointers to float.

* address spaces remain on the pointer, not the type:
    getelementptr float addrspace(1)* %x
  ->getelementptr float, float addrspace(1)* %x
  Then, eventually:
    getelementptr float, ptr addrspace(1) %x

Importantly, the massive amount of test case churn has been automated by
same crappy python code. I had to manually update a few test cases that
wouldn't fit the script's model (r228970,r229196,r229197,r229198). The
python script just massages stdin and writes the result to stdout, I
then wrapped that in a shell script to handle replacing files, then
using the usual find+xargs to migrate all the files.

update.py:
import fileinput
import sys
import re

ibrep = re.compile(r"(^.*?[^%\w]getelementptr inbounds )(((?:<\d* x )?)(.*?)(| addrspace\(\d\)) *\*(|>)(?:$| *(?:%|@|null|undef|blockaddress|getelementptr|addrspacecast|bitcast|inttoptr|\[\[[a-zA-Z]|\{\{).*$))")
normrep = re.compile(       r"(^.*?[^%\w]getelementptr )(((?:<\d* x )?)(.*?)(| addrspace\(\d\)) *\*(|>)(?:$| *(?:%|@|null|undef|blockaddress|getelementptr|addrspacecast|bitcast|inttoptr|\[\[[a-zA-Z]|\{\{).*$))")

def conv(match, line):
  if not match:
    return line
  line = match.groups()[0]
  if len(match.groups()[5]) == 0:
    line += match.groups()[2]
  line += match.groups()[3]
  line += ", "
  line += match.groups()[1]
  line += "\n"
  return line

for line in sys.stdin:
  if line.find("getelementptr ") == line.find("getelementptr inbounds"):
    if line.find("getelementptr inbounds") != line.find("getelementptr inbounds ("):
      line = conv(re.match(ibrep, line), line)
  elif line.find("getelementptr ") != line.find("getelementptr ("):
    line = conv(re.match(normrep, line), line)
  sys.stdout.write(line)

apply.sh:
for name in "$@"
do
  python3 `dirname "$0"`/update.py < "$name" > "$name.tmp" && mv "$name.tmp" "$name"
  rm -f "$name.tmp"
done

The actual commands:
From llvm/src:
find test/ -name *.ll | xargs ./apply.sh
From llvm/src/tools/clang:
find test/ -name *.mm -o -name *.m -o -name *.cpp -o -name *.c | xargs -I '{}' ../../apply.sh "{}"
From llvm/src/tools/polly:
find test/ -name *.ll | xargs ./apply.sh

After that, check-all (with llvm, clang, clang-tools-extra, lld,
compiler-rt, and polly all checked out).

The extra 'rm' in the apply.sh script is due to a few files in clang's test
suite using interesting unicode stuff that my python script was throwing
exceptions on. None of those files needed to be migrated, so it seemed
sufficient to ignore those cases.

Reviewers: rafael, dexonsmith, grosser

Differential Revision: http://reviews.llvm.org/D7636

llvm-svn: 230786
2015-02-27 19:29:02 +00:00
Arnold Schwaighofer
a66582470b SLPVectorizer: Don't vectorize volatile memory operations
radar://15231682

Reapply r192799,
  http://lab.llvm.org:8011/builders/lldb-x86_64-debian-clang/builds/8226
showed that the bot is still broken even with this out.

llvm-svn: 192820
2013-10-16 17:52:40 +00:00
Arnold Schwaighofer
06a0324f6a Revert "SLPVectorizer: Don't vectorize volatile memory operations"
This speculatively reverts commit 192799. It might have broken a linux buildbot.

llvm-svn: 192816
2013-10-16 17:19:40 +00:00
Arnold Schwaighofer
5078ea2bd9 SLPVectorizer: Don't vectorize volatile memory operations
radar://15231682

llvm-svn: 192799
2013-10-16 16:09:00 +00:00
Benjamin Kramer
b9add84ef6 SLPVectorizer: Make store chain finding more aggressive with GetUnderlyingObject.
This recursively strips all GEPs like the existing code. It also handles bitcasts and
other operations that do not change the pointer value.

llvm-svn: 191847
2013-10-02 19:06:06 +00:00
Nadav Rotem
029208ceeb Remove unused function attributes.
llvm-svn: 179476
2013-04-14 05:47:04 +00:00
Nadav Rotem
2d9dec322e Add support for bottom-up SLP vectorization infrastructure.
This commit adds the infrastructure for performing bottom-up SLP vectorization (and other optimizations) on parallel computations.
The infrastructure has three potential users:

  1. The loop vectorizer needs to be able to vectorize AOS data structures such as (sum += A[i] + A[i+1]).

  2. The BB-vectorizer needs this infrastructure for bottom-up SLP vectorization, because bottom-up vectorization is faster to compute.

  3. A loop-roller needs to be able to analyze consecutive chains and roll them into a loop, in order to reduce code size. A loop roller does not need to create vector instructions, and this infrastructure separates the chain analysis from the vectorization.

This patch also includes a simple (100 LOC) bottom up SLP vectorizer that uses the infrastructure, and can vectorize this code:

void SAXPY(int *x, int *y, int a, int i) {
  x[i]   = a * x[i]   + y[i];
  x[i+1] = a * x[i+1] + y[i+1];
  x[i+2] = a * x[i+2] + y[i+2];
  x[i+3] = a * x[i+3] + y[i+3];
}

llvm-svn: 179117
2013-04-09 19:44:35 +00:00