[test][NewPM] Use -passes=loop-vectorize instead of -loop-vectorize

Update a bunch of loop-vectorize regression tests to use the new PM
syntax (opt -passes=loop-vectorize) instead of the deprecated

[test][NewPM] Use -passes=loop-vectorize instead of -loop-vectorize

Update a bunch of loop-vectorize regression tests to use the new PM
syntax (opt -passes=loop-vectorize) instead of the deprecated legacy
PM syntax (opt -loop-vectorize).

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Recommit "[VPlan] Introduce recipe to build scalar steps."

This reverts the revert commit ff93260bf6bddfbad1fa65c4d5184988885b900f.

The underlying issue causing the PPC bot failures has been fixed

Recommit "[VPlan] Introduce recipe to build scalar steps."

This reverts the revert commit ff93260bf6bddfbad1fa65c4d5184988885b900f.

The underlying issue causing the PPC bot failures has been fixed in
cbaac1473403 and a corresponding test case has been added in
ad2cad1c521c.

Original message:

This patch adds a new VPScalarIVStepsRecipe to handle building scalar
steps.

In the first patch, it only handles the case where there is no vector
induction variable needed.

Reviewed By: Ayal

Differential Revision: https://reviews.llvm.org/D115953

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Revert "[VPlan] Introduce recipe to build scalar steps."

This reverts commit 49b23f451cf713036c99573a35daed308d2ac894.

This appears to break some PPC build bots. Revert while I investigate.

[VPlan] Introduce recipe to build scalar steps.

This patch adds a new VPScalarIVStepsRecipe to handle building scalar
steps.

In the first patch, it only handles the case where there is no vector
in

[VPlan] Introduce recipe to build scalar steps.

This patch adds a new VPScalarIVStepsRecipe to handle building scalar
steps.

In the first patch, it only handles the case where there is no vector
induction variable needed.

Reviewed By: Ayal

Differential Revision: https://reviews.llvm.org/D115953

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[LV] Add real uses in some tests, to make them more robust.

Add real uses to some tests, to ensure dead instructions cannot be directly
removed.

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

The reversion apparently deleted the test/Transforms directory.

Will be re-reverting again.

llvm-svn: 358552

[LV] Don't emit unused scalars for uniform instructions

If we identify an instruction as uniform after vectorization, we know that we
should only use the value corresponding to the first vector lane

[LV] Don't emit unused scalars for uniform instructions

If we identify an instruction as uniform after vectorization, we know that we
should only use the value corresponding to the first vector lane of each unroll
iteration. However, when scalarizing such instructions, we still produce values
for the other vector lanes. This patch prevents us from generating the unused
scalars.

Differential Revision: https://reviews.llvm.org/D24275

llvm-svn: 282087

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Recommit the patch "Use uniforms set to populate VecValuesToIgnore".

For instructions in uniform set, they will not have vector versions so
add them to VecValuesToIgnore.
For induction vars, those o

Recommit the patch "Use uniforms set to populate VecValuesToIgnore".

For instructions in uniform set, they will not have vector versions so
add them to VecValuesToIgnore.
For induction vars, those only used in uniform instructions or consecutive
ptrs instructions have already been added to VecValuesToIgnore above. For
those induction vars which are only used in uniform instructions or
non-consecutive/non-gather scatter ptr instructions, the related phi and
update will also be added into VecValuesToIgnore set.

The change will make the vector RegUsages estimation less conservative.

Differential Revision: https://reviews.llvm.org/D20474

The recommit fixed the testcase global_alias.ll.

llvm-svn: 275936

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Revert rL275912.

llvm-svn: 275915

Use uniforms set to populate VecValuesToIgnore.

For instructions in uniform set, they will not have vector versions so
add them to VecValuesToIgnore.
For induction vars, those only used in uniform i

Use uniforms set to populate VecValuesToIgnore.

For instructions in uniform set, they will not have vector versions so
add them to VecValuesToIgnore.
For induction vars, those only used in uniform instructions or consecutive
ptrs instructions have already been added to VecValuesToIgnore above. For
those induction vars which are only used in uniform instructions or
non-consecutive/non-gather scatter ptr instructions, the related phi and
update will also be added into VecValuesToIgnore set.

The change will make the vector RegUsages estimation less conservative.

Differential Revision: https://reviews.llvm.org/D20474

llvm-svn: 275912

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[LV] Avoid unnecessary IV scalar-to-vector-to-scalar conversions

This patch prevents increases in the number of instructions, pre-instcombine,
due to induction variable scalarization. An increase in

[LV] Avoid unnecessary IV scalar-to-vector-to-scalar conversions

This patch prevents increases in the number of instructions, pre-instcombine,
due to induction variable scalarization. An increase in instructions can lead
to an increase in the compile-time required to simplify the induction
variables. We now maintain a new map for scalarized induction variables to
prevent us from converting between the scalar and vector forms.

This patch should resolve compile-time regressions seen after r274627.

llvm-svn: 275419

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[LV] Don't widen trivial induction variables

We currently always vectorize induction variables. However, if an induction
variable is only used for counting loop iterations or computing addresses wit

[LV] Don't widen trivial induction variables

We currently always vectorize induction variables. However, if an induction
variable is only used for counting loop iterations or computing addresses with
getelementptr instructions, we don't need to do this. Vectorizing these trivial
induction variables can create vector code that is difficult to simplify later
on. This is especially true when the unroll factor is greater than one, and we
create vector arithmetic when computing step vectors. With this patch, we check
if an induction variable is only used for counting iterations or computing
addresses, and if so, scalarize the arithmetic when computing step vectors
instead. This allows for greater simplification.

This patch addresses the suboptimal pointer arithmetic sequence seen in
PR27881.

Reference: https://llvm.org/bugs/show_bug.cgi?id=27881
Differential Revision: http://reviews.llvm.org/D21620

llvm-svn: 274627

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[LV] Use vector phis for some secondary induction variables

Previously, we materialized secondary vector IVs from the primary scalar IV,
by offseting the primary to match the correct start value, an

[LV] Use vector phis for some secondary induction variables

Previously, we materialized secondary vector IVs from the primary scalar IV,
by offseting the primary to match the correct start value, and then broadcasting
it - inside the loop body. Instead, we can use a real vector IV, like we do for
the primary.

This enables using vector IVs for secondary integer IVs whose type matches the
type of the primary.

Differential Revision: http://reviews.llvm.org/D20932

llvm-svn: 272283

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[LV] Switch to using canonical induction variables.

Vectorized loops only ever have one induction variable. All induction PHIs from the scalar loop are rewritten to be in terms of this single indvar

[LV] Switch to using canonical induction variables.

Vectorized loops only ever have one induction variable. All induction PHIs from the scalar loop are rewritten to be in terms of this single indvar.

We were trying very hard to pick an indvar that already existed, even if that indvar wasn't canonical (didn't start at zero). But trying so hard is really fruitless - creating a new, canonical, indvar only results in one extra add in the worst case and that add is trivially easy to push through the PHI out of the loop by instcombine.

If we try and be less clever here and instead let instcombine clean up our mess (as we do in many other places in LV), we can remove unneeded complexity.

llvm-svn: 246630

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[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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[LoopVectorize] Induction variables: support arbitrary constant step.
Previously, only -1 and +1 step values are supported for induction variables. This patch extends LV to support
arbitrary constant

[LoopVectorize] Induction variables: support arbitrary constant step.
Previously, only -1 and +1 step values are supported for induction variables. This patch extends LV to support
arbitrary constant steps.
Initial patch by Alexey Volkov. Some bug fixes are added in the following version.

Differential Revision: http://reviews.llvm.org/D6051 and http://reviews.llvm.org/D7193

llvm-svn: 227557

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Rename getMaximumUnrollFactor -> getMaxInterleaveFactor; also rename option names controlling this variable.

"Unroll" is not the appropriate name for this variable. Clang already uses
the term "int

Rename getMaximumUnrollFactor -> getMaxInterleaveFactor; also rename option names controlling this variable.

"Unroll" is not the appropriate name for this variable. Clang already uses
the term "interleave" in pragmas and metadata for this.

Differential Revision: http://reviews.llvm.org/D5066

llvm-svn: 217528

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Fix missing CHECK-LABELs

llvm-svn: 191853

LoopVectorize: Use the widest induction variable type

Use the widest induction type encountered for the cannonical induction variable.

We used to turn the following loop into an empty loop because

LoopVectorize: Use the widest induction variable type

Use the widest induction type encountered for the cannonical induction variable.

We used to turn the following loop into an empty loop because we used i8 as
induction variable type and truncated 1024 to 0 as trip count.

int a[1024];
void fail() {
int reverse_induction = 1023;
unsigned char forward_induction = 0;
while ((reverse_induction) >= 0) {
forward_induction++;
a[reverse_induction] = forward_induction;
--reverse_induction;
}
}

radar://13862901

llvm-svn: 181667

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LoopVectorize: getConsecutiveVector must respect signed arithmetic

We were passing an i32 to ConstantInt::get where an i64 was needed and we must
also pass the sign if we pass negatives numbers. The

LoopVectorize: getConsecutiveVector must respect signed arithmetic

We were passing an i32 to ConstantInt::get where an i64 was needed and we must
also pass the sign if we pass negatives numbers. The start index passed to
getConsecutiveVector must also be signed.

Should fix PR15882.

llvm-svn: 181286

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