Commit Graph

12 Commits

Author SHA1 Message Date
Matthew Simpson c62266d680 [LV] Sink scalar operands of predicated instructions
When we predicate an instruction (div, rem, store) we place the instruction in
its own basic block within the vectorized loop. If a predicated instruction has
scalar operands, it's possible to recursively sink these scalar expressions
into the predicated block so that they might avoid execution. This patch sinks
as much scalar computation as possible into predicated blocks. We previously
were able to sink such operands only if they were extractelement instructions.

Differential Revision: https://reviews.llvm.org/D25632

llvm-svn: 285097
2016-10-25 18:59:45 +00:00
Michael Kuperstein 5185b7dde3 [LV] Remove triples from target-independent vectorizer tests. NFC.
Vectorizer tests in the target-independent directory should not have a target
triple. If a test really needs to query a specific backend, it belongs in the
right target subdirectory (which "REQUIRES" the right backend). Otherwise, it
should not specify a triple.

llvm-svn: 283512
2016-10-06 23:57:25 +00:00
Michael Kuperstein 2954d1db77 [LoopVectorizer] Predicate instructions in blocks with several incoming edges
We don't need to limit predication to blocks that have a single incoming
edge, we just need to use the right mask.
This fixes PR30172.

Differential Revision: https://reviews.llvm.org/D24009

llvm-svn: 280148
2016-08-30 20:22:21 +00:00
Matthew Simpson abd2be1e2e [LV] Unify vector and scalar maps
This patch unifies the data structures we use for mapping instructions from the
original loop to their corresponding instructions in the new loop. Previously,
we maintained two distinct maps for this purpose: WidenMap and ScalarIVMap.
WidenMap maintained the vector values each instruction from the old loop was
represented with, and ScalarIVMap maintained the scalar values each scalarized
induction variable was represented with. With this patch, all values created
for the new loop are maintained in VectorLoopValueMap.

The change allows for several simplifications. Previously, when an instruction
was scalarized, we had to insert the scalar values into vectors in order to
maintain the mapping in WidenMap. Then, if a user of the scalarized value was
also scalar, we had to extract the scalar values from the temporary vector we
created. We now aovid these unnecessary scalar-to-vector-to-scalar conversions.
If a scalarized value is used by a scalar instruction, the scalar value is used
directly. However, if the scalarized value is needed by a vector instruction,
we generate the needed insertelement instructions on-demand.

A common idiom in several locations in the code (including the scalarization
code), is to first get the vector values an instruction from the original loop
maps to, and then extract a particular scalar value. This patch adds
getScalarValue for this purpose along side getVectorValue as an interface into
VectorLoopValueMap. These functions work together to return the requested
values if they're available or to produce them if they're not.

The mapping has also be made less permissive. Entries can be added to
VectorLoopValue map with the new initVector and initScalar functions.
getVectorValue has been modified to return a constant reference to the mapped
entries.

There's no real functional change with this patch; however, in some cases we
will generate slightly different code. For example, instead of an insertelement
sequence following the definition of an instruction, it will now precede the
first use of that instruction. This can be seen in the test case changes.

Differential Revision: https://reviews.llvm.org/D23169

llvm-svn: 279649
2016-08-24 18:23:17 +00:00
Gil Rapaport 550148b2f6 [Loop Vectorizer] Support predication of div/rem
div/rem instructions in basic blocks that require predication currently prevent
vectorization. This patch extends the existing mechanism for predicating stores
to handle other instructions and leverages it to predicate divs and rems.

Differential Revision: https://reviews.llvm.org/D22918

llvm-svn: 279620
2016-08-24 11:37:57 +00:00
Adam Nemet fdb20595a1 [LV] Preserve LoopInfo when store predication is used
This was a latent bug that got exposed by the change to add LoopSimplify
as a dependence to LoopLoadElimination.  Since LoopInfo was corrupted
after LV, LoopSimplify mis-compiled nbench in the test-suite (more
details in the PR).

The problem was that when we create the blocks for predicated stores we
didn't add those to any loops.

The original testcase for store predication provides coverage for this
assuming we verify LI on the way out of LV.

Fixes PR26952.

llvm-svn: 263565
2016-03-15 18:06:20 +00:00
James Molloy 89eccee4db Delay predication of stores until near the end of vector code generation
Predicating stores requires creating extra blocks. It's much cleaner if we do this in one pass instead of mutating the CFG while writing vector instructions.

Besides which we can make use of helper functions to update domtree for us, reducing the work we need to do.

llvm-svn: 247139
2015-09-09 12:51:06 +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
Sanjay Patel b653de1ada 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
2014-09-10 17:58:16 +00:00
Arnold Schwaighofer 348e1b60be LoopVectorizer: Keep track of conditional store basic blocks
Before conditional store vectorization/unrolling we had only one
vectorized/unrolled basic block. After adding support for conditional store
vectorization this will not only be one block but multiple basic blocks. The
last block would have the back-edge. I updated the code to use a vector of basic
blocks instead of a single basic block and fixed the users to use the last entry
in this vector. But, I forgot to add the basic blocks to this vector!

Fixes PR18724.

llvm-svn: 201028
2014-02-08 20:41:13 +00:00
Arnold Schwaighofer 18865db3c1 LoopVectorize: Support conditional stores by scalarizing
The vectorizer takes a loop like this and widens all instructions except for the
store. The stores are scalarized/unrolled and hidden behind an "if" block.

  for (i = 0; i < 128; ++i) {
    if (a[i] < 10)
      a[i] += val;
  }

  for (i = 0; i < 128; i+=2) {
    v = a[i:i+1];
    v0 = (extract v, 0) + 10;
    v1 = (extract v, 1) + 10;
    if (v0 < 10)
      a[i] = v0;
    if (v1 < 10)
      a[i] = v1;
  }

The vectorizer relies on subsequent optimizations to sink instructions into the
conditional block where they are anticipated.

The flag "vectorize-num-stores-pred" controls whether and how many stores to
handle this way. Vectorization of conditional stores is disabled per default for
now.

This patch also adds a change to the heuristic when the flag
"enable-loadstore-runtime-unroll" is enabled (off by default). It unrolls small
loops until load/store ports are saturated. This heuristic uses TTI's
getMaxUnrollFactor as a measure for load/store ports.

I also added a second flag -enable-cond-stores-vec. It will enable vectorization
of conditional stores. But there is no cost model for vectorization of
conditional stores in place yet so this will not do good at the moment.

rdar://15892953

Results for x86-64 -O3 -mavx +/- -mllvm -enable-loadstore-runtime-unroll
-vectorize-num-stores-pred=1 (before the BFI change):

 Performance Regressions:
   Benchmarks/Ptrdist/yacr2/yacr2 7.35% (maze3() is identical but 10% slower)
   Applications/siod/siod         2.18%
 Performance improvements:
   mesa                          -4.42%
   libquantum                    -4.15%

 With a patch that slightly changes the register heuristics (by subtracting the
 induction variable on both sides of the register pressure equation, as the
 induction variable is probably not really unrolled):

 Performance Regressions:
   Benchmarks/Ptrdist/yacr2/yacr2  7.73%
   Applications/siod/siod          1.97%

 Performance Improvements:
   libquantum                    -13.05% (we now also unroll quantum_toffoli)
   mesa                           -4.27%

llvm-svn: 200270
2014-01-28 01:01:53 +00:00