[SLP]Try partial store vectorization if supported by target.

We can try to vectorize number of stores less than MinVecRegSize
/ scalar_value_size, if it is allowed by target. Gives an extra
opportun

[SLP]Try partial store vectorization if supported by target.

We can try to vectorize number of stores less than MinVecRegSize
/ scalar_value_size, if it is allowed by target. Gives an extra
opportunity for the vectorization.

Fixes PR54985.

Differential Revision: https://reviews.llvm.org/D124284

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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

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

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Revert "Reapply "[SLP] Schedule only sub-graph of vectorizable instructions"""

This reverts commit 738042711bc08cde9135873200b1d088e6cf11c3. A second, apparently separate, issue has been reported on

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.

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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:

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

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Revert "[SLP] Schedule only sub-graph of vectorizable instructions"

This reverts commit 0539a26d91a1b7c74022fa9cf33bd7faca87544d.

Causes a miscompile, see comments on D118538.

Required updating bo

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.

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[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 th

[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

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[NewPM][BasicAA] basicaa -> basic-aa in Transforms/SLPVectorizer

Following https://reviews.llvm.org/D82607.

Reviewed By: ychen

Differential Revision: https://reviews.llvm.org/D82681

Revert "Temporarily Revert "Add basic loop fusion pass.""

The reversion apparently deleted the test/Transforms directory.

Will be re-reverting again.

llvm-svn: 358552

[SLPVectorizer] reorderInputsAccordingToOpcode - remove non-Instruction canonicalization

Remove attempts to commute non-Instructions to the LHS - the codegen changes appear to rely on chance more th

[SLPVectorizer] reorderInputsAccordingToOpcode - remove non-Instruction canonicalization

Remove attempts to commute non-Instructions to the LHS - the codegen changes appear to rely on chance more than anything else and also have a tendency to fight existing instcombine canonicalization which moves constants to the RHS of commutable binary ops.

This is prep work towards:
(a) reusing reorderInputsAccordingToOpcode for alt-shuffles and removing the similar reorderAltShuffleOperands
(b) improving reordering to optimized cases with commutable and non-commutable instructions to still find splat/consecutive ops.

Differential Revision: https://reviews.llvm.org/D59738

llvm-svn: 356913

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[SLP]Update test checks for the SPL vectorizer, NFC.

llvm-svn: 350967

[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

[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

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[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

[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

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Remove unused function attributes.

llvm-svn: 179476

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 inf

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

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