This patch tries to avoid unrelated changes other than fixing a few
hyphen-related ambiguities and contractions in nearby lines.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@196471 91177308-0d34-0410-b5e6-96231b3b80d8
clang enables vectorization at optimization levels > 1 and size level < 2. opt
should behave similarily.
Loop vectorization and SLP vectorization can be disabled with the flags
-disable-(loop/slp)-vectorization.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@196294 91177308-0d34-0410-b5e6-96231b3b80d8
In signed arithmetic we could end up with an i64 trip count for an i32 phi.
Because it is signed arithmetic we know that this is only defined if the i32
does not wrap. It is therefore safe to truncate the i64 trip count to a i32
value.
Fixes PR18049.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@195787 91177308-0d34-0410-b5e6-96231b3b80d8
We are going to drop debug info without a version number or with a different
version number, to make sure we don't crash when we see bitcode files with
different debug info metadata format.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@195504 91177308-0d34-0410-b5e6-96231b3b80d8
We are slicing an array of Value pointers and process those slices in a loop.
The problem is that we might invalidate a later slice by vectorizing a former
slice.
Use a WeakVH to track the pointer. If the pointer is deleted or RAUW'ed we can
tell.
The test case will only fail when running with libgmalloc.
radar://15498655
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In some case the loop exit count computation can overflow. Extend the type to
prevent most of those cases.
The problem is loops like:
int main ()
{
int a = 1;
char b = 0;
lbl:
a &= 4;
b--;
if (b) goto lbl;
return a;
}
The backedge count is 255. The induction variable type is i8. If we add one to
255 to get the exit count we overflow to zero.
To work around this issue we extend the type of the induction variable to i32 in
the case of i8 and i16.
PR17532
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When we vectorize a scalar access with no alignment specified, we have to set
the target's abi alignment of the scalar access on the vectorized access.
Using the same alignment of zero would be wrong because most targets will have a
bigger abi alignment for vector types.
This probably fixes PR17878.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@194876 91177308-0d34-0410-b5e6-96231b3b80d8
When the elements are extracted from a select on vectors
or a vector select, do the select on the extracted scalars
from the input if there is only one use.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@194013 91177308-0d34-0410-b5e6-96231b3b80d8
When the loop vectorizer was part of the SCC inliner pass manager gvn would
run after the loop vectorizer followed by instcombine. This way redundancy
(multiple uses) were removed and instcombine could perform scalarization on the
induction variables. Having moved the loop vectorizer to later we no longer run
any form of redundancy elimination before we perform instcombine. This caused
vectorized induction variables to survive that did not before.
On a recent iMac this helps linpack back from 6000Mflops to 7000Mflops.
This should also help lpbench and paq8p.
I ran a Release (without Asserts) build over the test-suite and did not see any
negative impact on compile time.
radar://15339680
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If we have a pointer to a single-element struct we can still build wide loads
and stores to it (if there is no padding).
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@193860 91177308-0d34-0410-b5e6-96231b3b80d8
When a dependence check fails we can still try to vectorize loops with runtime
array bounds checks.
This helps linpack to vectorize a loop in dgefa. And we are back to 2x of the
scalar performance on a corei7-avx.
radar://15339680
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@193853 91177308-0d34-0410-b5e6-96231b3b80d8
Updated a test case that assumed that <2 x double> would vectorize to use
<4 x float>.
radar://15338229
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The loop vectorizer does not currently understand how to vectorize
extractelement instructions. The existing check, which excluded all
vector-valued instructions, did not catch extractelement instructions because
it checked only the return value. As a result, vectorization would proceed,
producing illegal instructions like this:
%58 = extractelement <2 x i32> %15, i32 0
%59 = extractelement i32 %58, i32 0
where the second extractelement is illegal because its first operand is not a vector.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@193434 91177308-0d34-0410-b5e6-96231b3b80d8
Make sure we mark all loops (scalar and vector) when vectorizing,
so that we don't try to vectorize them anymore. Also, set unroll
to 1, since this is what we check for on early exit.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@193349 91177308-0d34-0410-b5e6-96231b3b80d8
Otherwise, we don't perform operations that would have been performed on
the scalar version.
Fixes PR17498.
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Don't vectorize with a runtime check if it requires a
comparison between pointers with different address spaces.
The values can't be assumed to be directly comparable.
Previously it would create an illegal bitcast.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@191862 91177308-0d34-0410-b5e6-96231b3b80d8
Revert 191122 - with extra checks we are allowed to vectorize math library
function calls.
Standard library indentifiers are reserved names so functions with external
linkage must not overrided them. However, functions with internal linkage can.
Therefore, we can vectorize calls to math library functions with a check for
external linkage and matching signature. This matches what we do during
SelectionDAG building.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@191206 91177308-0d34-0410-b5e6-96231b3b80d8
XCore target: Add XCoreTargetTransformInfo
This is where getNumberOfRegisters() resides, which in turn returns the
number of vector registers (=0).
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@190936 91177308-0d34-0410-b5e6-96231b3b80d8
We would have to compute the pre increment value, either by computing it on
every loop iteration or by splitting the edge out of the loop and inserting a
computation for it there.
For now, just give up vectorizing such loops.
Fixes PR17179.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@190790 91177308-0d34-0410-b5e6-96231b3b80d8
Field 2 of DIType (Context), field 9 of DIDerivedType (TypeDerivedFrom),
field 12 of DICompositeType (ContainingType), fields 2, 7, 12 of DISubprogram
(Context, Type, ContainingType).
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@190205 91177308-0d34-0410-b5e6-96231b3b80d8
When unrolling is disabled in the pass manager, the loop vectorizer should also
not unroll loops. This will allow the -fno-unroll-loops option in Clang to
behave as expected (even for vectorizable loops). The loop vectorizer's
-force-vector-unroll option will (continue to) override the pass-manager
setting (including -force-vector-unroll=0 to force use of the internal
auto-selection logic).
In order to test this, I added a flag to opt (-disable-loop-unrolling) to force
disable unrolling through opt (the analog of -fno-unroll-loops in Clang). Also,
this fixes a small bug in opt where the loop vectorizer was enabled only after
the pass manager populated the queue of passes (the global_alias.ll test needed
a slight update to the RUN line as a result of this fix).
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@189499 91177308-0d34-0410-b5e6-96231b3b80d8
DICompositeType will have an identifier field at position 14. For now, the
field is set to null in DIBuilder.
For DICompositeTypes where the template argument field (the 13th field)
was optional, modify DIBuilder to make sure the template argument field is set.
Now DICompositeType has 15 fields.
Update DIBuilder to use NULL instead of "i32 0" for null value of a MDNode.
Update verifier to check that DICompositeType has 15 fields and the last
field is null or a MDString.
Update testing cases to include an extra field for DICompositeType.
The identifier field will be used by type uniquing so a front end can
genearte a DICompositeType with a unique identifer.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@189282 91177308-0d34-0410-b5e6-96231b3b80d8
This patch enables unrolling of loops when vectorization is legal but not profitable.
We add a new class InnerLoopUnroller, that extends InnerLoopVectorizer and replaces some of the vector-specific logic with scalars.
This patch does not introduce any runtime regressions and improves the following workloads:
SingleSource/Benchmarks/Shootout/matrix -22.64%
SingleSource/Benchmarks/Shootout-C++/matrix -13.06%
External/SPEC/CINT2006/464_h264ref/464_h264ref -3.99%
SingleSource/Benchmarks/Adobe-C++/simple_types_constant_folding -1.95%
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@189281 91177308-0d34-0410-b5e6-96231b3b80d8
A single metadata will not span multiple lines. This also helps me with
my script to automatic update the testing cases.
A debug info testing case should have a llvm.dbg.cu.
Do not use hard-coded id for debug nodes.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@189033 91177308-0d34-0410-b5e6-96231b3b80d8
This adds a llvm.copysign intrinsic; We already have Libfunc recognition for
copysign (which is turned into the FCOPYSIGN SDAG node). In order to
autovectorize calls to copysign in the loop vectorizer, we need a corresponding
intrinsic as well.
In addition to the expected changes to the language reference, the loop
vectorizer, BasicTTI, and the SDAG builder (the intrinsic is transformed into
an FCOPYSIGN node, just like the function call), this also adds FCOPYSIGN to a
few lists in LegalizeVector{Ops,Types} so that vector copysigns can be
expanded.
In TargetLoweringBase::initActions, I've made the default action for FCOPYSIGN
be Expand for vector types. This seems correct for all in-tree targets, and I
think is the right thing to do because, previously, there was no way to generate
vector-values FCOPYSIGN nodes (and most targets don't specify an action for
vector-typed FCOPYSIGN).
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@188728 91177308-0d34-0410-b5e6-96231b3b80d8
- Instead of setting the suffixes in a bunch of places, just set one master
list in the top-level config. We now only modify the suffix list in a few
suites that have one particular unique suffix (.ml, .mc, .yaml, .td, .py).
- Aside from removing the need for a bunch of lit.local.cfg files, this enables
4 tests that were inadvertently being skipped (one in
Transforms/BranchFolding, a .s file each in DebugInfo/AArch64 and
CodeGen/PowerPC, and one in CodeGen/SI which is now failing and has been
XFAILED).
- This commit also fixes a bunch of config files to use config.root instead of
older copy-pasted code.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@188513 91177308-0d34-0410-b5e6-96231b3b80d8
All libm floating-point rounding functions, except for round(), had their own
ISD nodes. Recent PowerPC cores have an instruction for round(), and so here I'm
adding ISD::FROUND so that round() can be custom lowered as well.
For the most part, this is straightforward. I've added an intrinsic
and a matching ISD node just like those for nearbyint() and friends. The
SelectionDAG pattern I've named frnd (because ISD::FP_ROUND has already claimed
fround).
This will be used by the PowerPC backend in a follow-up commit.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@187926 91177308-0d34-0410-b5e6-96231b3b80d8
Function attributes are the future! So just query whether we want to realign the
stack directly from the function instead of through a random target options
structure.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@187618 91177308-0d34-0410-b5e6-96231b3b80d8
This conversion was done with the following bash script:
find test/Transforms -name "*.ll" | \
while read NAME; do
echo "$NAME"
if ! grep -q "^; *RUN: *llc" $NAME; then
TEMP=`mktemp -t temp`
cp $NAME $TEMP
sed -n "s/^define [^@]*@\([A-Za-z0-9_]*\)(.*$/\1/p" < $NAME | \
while read FUNC; do
sed -i '' "s/;\(.*\)\([A-Za-z0-9_]*\):\( *\)define\([^@]*\)@$FUNC\([( ]*\)\$/;\1\2-LABEL:\3define\4@$FUNC(/g" $TEMP
done
mv $TEMP $NAME
fi
done
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@186269 91177308-0d34-0410-b5e6-96231b3b80d8
This update was done with the following bash script:
find test/Transforms -name "*.ll" | \
while read NAME; do
echo "$NAME"
if ! grep -q "^; *RUN: *llc" $NAME; then
TEMP=`mktemp -t temp`
cp $NAME $TEMP
sed -n "s/^define [^@]*@\([A-Za-z0-9_]*\)(.*$/\1/p" < $NAME | \
while read FUNC; do
sed -i '' "s/;\(.*\)\([A-Za-z0-9_]*\):\( *\)@$FUNC\([( ]*\)\$/;\1\2-LABEL:\3@$FUNC(/g" $TEMP
done
mv $TEMP $NAME
fi
done
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@186268 91177308-0d34-0410-b5e6-96231b3b80d8
If an outside loop user of the reduction value uses the header phi node we
cannot just reduce the vectorized phi value in the vector code epilog because
we would loose VF-1 reductions.
lp:
p = phi (0, lv)
lv = lv + 1
...
brcond , lp, outside
outside:
usr = add 0, p
(Say the loop iterates two times, the value of p coming out of the loop is one).
We cannot just transform this to:
vlp:
p = phi (<0,0>, lv)
lv = lv + <1,1>
..
brcond , lp, outside
outside:
p_reduced = p[0] + [1];
usr = add 0, p_reduced
(Because the original loop iterated two times the vectorized loop would iterate
one time, but p_reduced ends up being zero instead of one).
We would have to execute VF-1 iterations in the scalar remainder loop in such
cases. For now, just disable vectorization.
PR16522
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@186256 91177308-0d34-0410-b5e6-96231b3b80d8
In general, one should always complete CFG modifications first, update
CFG-based analyses, like Dominatores and LoopInfo, then generate
instruction sequences.
LoopVectorizer was creating a new loop, calling SCEVExpander to
generate checks, then updating LoopInfo. I just changed the order.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@186241 91177308-0d34-0410-b5e6-96231b3b80d8
Fixes a 35% degradation compared to unvectorized code in
MiBench/automotive-susan and an equally serious regression on a private
image processing benchmark.
radar://14351991
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@186188 91177308-0d34-0410-b5e6-96231b3b80d8
We can vectorize them because in the case where we wrap in the address space the
unvectorized code would have had to access a pointer value of zero which is
undefined behavior in address space zero according to the LLVM IR semantics.
(Thank you Duncan, for pointing this out to me).
Fixes PR16592.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@186088 91177308-0d34-0410-b5e6-96231b3b80d8
Math functions are mark as readonly because they read the floating point
rounding mode. Because we don't vectorize loops that would contain function
calls that set the rounding mode it is safe to ignore this memory read.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@185299 91177308-0d34-0410-b5e6-96231b3b80d8
Use vectorized instruction instead of original instruction anchored in the
original loop.
Fixes PR16452 and t2075.c of PR16455.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@185081 91177308-0d34-0410-b5e6-96231b3b80d8
When we store values for reversed induction stores we must not store the
reversed value in the vectorized value map. Another instruction might use this
value.
This fixes 3 test cases of PR16455.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@185051 91177308-0d34-0410-b5e6-96231b3b80d8
This should hopefully have fixed the stage2/stage3 miscompare on the dragonegg
testers.
"LoopVectorize: Use the dependence test utility class
We now no longer need alias analysis - the cases that alias analysis would
handle are now handled as accesses with a large dependence distance.
We can now vectorize loops with simple constant dependence distances.
for (i = 8; i < 256; ++i) {
a[i] = a[i+4] * a[i+8];
}
for (i = 8; i < 256; ++i) {
a[i] = a[i-4] * a[i-8];
}
We would be able to vectorize about 200 more loops (in many cases the cost model
instructs us no to) in the test suite now. Results on x86-64 are a wash.
I have seen one degradation in ammp. Interestingly, the function in which we
now vectorize a loop is never executed so we probably see some instruction
cache effects. There is a 2% improvement in h264ref. There is one or the other
TSCV loop kernel that speeds up.
radar://13681598"
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@184724 91177308-0d34-0410-b5e6-96231b3b80d8
We now no longer need alias analysis - the cases that alias analysis would
handle are now handled as accesses with a large dependence distance.
We can now vectorize loops with simple constant dependence distances.
for (i = 8; i < 256; ++i) {
a[i] = a[i+4] * a[i+8];
}
for (i = 8; i < 256; ++i) {
a[i] = a[i-4] * a[i-8];
}
We would be able to vectorize about 200 more loops (in many cases the cost model
instructs us no to) in the test suite now. Results on x86-64 are a wash.
I have seen one degradation in ammp. Interestingly, the function in which we
now vectorize a loop is never executed so we probably see some instruction
cache effects. There is a 2% improvement in h264ref. There is one or the other
TSCV loop kernel that speeds up.
radar://13681598
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@184685 91177308-0d34-0410-b5e6-96231b3b80d8
vectorizing loops with memory accesses to non-zero address spaces. It
simply dropped the AS info. Fixes PR16306.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@184103 91177308-0d34-0410-b5e6-96231b3b80d8
We check that instructions in the loop don't have outside users (except if
they are reduction values). Unfortunately, we skipped this check for
if-convertable PHIs.
Fixes PR16184.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@183035 91177308-0d34-0410-b5e6-96231b3b80d8
- llvm.loop.parallel metadata has been renamed to llvm.loop to be more generic
by making the root of additional loop metadata.
- Loop::isAnnotatedParallel now looks for llvm.loop and associated
llvm.mem.parallel_loop_access
- document llvm.loop and update llvm.mem.parallel_loop_access
- add support for llvm.vectorizer.width and llvm.vectorizer.unroll
- document llvm.vectorizer.* metadata
- add utility class LoopVectorizerHints for getting/setting loop metadata
- use llvm.vectorizer.width=1 to indicate already vectorized instead of
already_vectorized
- update existing tests that used llvm.loop.parallel and
llvm.vectorizer.already_vectorized
Reviewed by: Nadav Rotem
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The Value pointers we store in the induction variable list can be RAUW'ed by a
call to SCEVExpander::expandCodeFor, use a TrackingVH instead. Do the same thing
in some other places where we store pointers that could potentially be RAUW'ed.
Fixes PR16073.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@182485 91177308-0d34-0410-b5e6-96231b3b80d8
InstCombine can be uncooperative to vectorization and sink loads into
conditional blocks. This prevents vectorization.
Undo this optimization if there are unconditional memory accesses to the same
addresses in the loop.
radar://13815763
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@181860 91177308-0d34-0410-b5e6-96231b3b80d8
We used to give up if we saw two integer inductions. After this patch, we base
further induction variables on the chosen one like we do in the reverse
induction and pointer induction case.
Fixes PR15720.
radar://13851975
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@181746 91177308-0d34-0410-b5e6-96231b3b80d8
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
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@181667 91177308-0d34-0410-b5e6-96231b3b80d8
A computable loop exit count does not imply the presence of an induction
variable. Scalar evolution can return a value for an infinite loop.
Fixes PR15926.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@181495 91177308-0d34-0410-b5e6-96231b3b80d8
The two nested loops were confusing and also conservative in identifying
reduction variables. This patch replaces them by a worklist based approach.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@181369 91177308-0d34-0410-b5e6-96231b3b80d8
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.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@181286 91177308-0d34-0410-b5e6-96231b3b80d8
Add support for min/max reductions when "no-nans-float-math" is enabled. This
allows us to assume we have ordered floating point math and treat ordered and
unordered predicates equally.
radar://13723044
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@181144 91177308-0d34-0410-b5e6-96231b3b80d8
We can just use the initial element that feeds the reduction.
max(max(x, y), z) == max(max(x,y), max(x,z))
radar://13723044
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@181141 91177308-0d34-0410-b5e6-96231b3b80d8
By supporting the vectorization of PHINodes with more than two incoming values we can increase the complexity of nested if statements.
We can now vectorize this loop:
int foo(int *A, int *B, int n) {
for (int i=0; i < n; i++) {
int x = 9;
if (A[i] > B[i]) {
if (A[i] > 19) {
x = 3;
} else if (B[i] < 4 ) {
x = 4;
} else {
x = 5;
}
}
A[i] = x;
}
}
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@181037 91177308-0d34-0410-b5e6-96231b3b80d8
This patch disables memory-instruction vectorization for types that need padding
bytes, e.g., x86_fp80 has 10 bytes store size with 6 bytes padding in darwin on
x86_64. Because the load/store vectorization is performed by the bit casting to
a packed vector, which has incompatible memory layout due to the lack of padding
bytes, the present vectorizer produces inconsistent result for memory
instructions of those types.
This patch checks an equality of the AllocSize of a scalar type and allocated
size for each vector element, to ensure that there is no padding bytes and the
array can be read/written using vector operations.
Patch by Daisuke Takahashi!
Fixes PR15758.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@180196 91177308-0d34-0410-b5e6-96231b3b80d8
even if erroneously annotated with the parallel loop metadata.
Fixes Bug 15794:
"Loop Vectorizer: Crashes with the use of llvm.loop.parallel metadata"
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@180081 91177308-0d34-0410-b5e6-96231b3b80d8
A min/max operation is represented by a select(cmp(lt/le/gt/ge, X, Y), X, Y)
sequence in LLVM. If we see such a sequence we can treat it just as any other
commutative binary instruction and reduce it.
This appears to help bzip2 by about 1.5% on an imac12,2.
radar://12960601
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Pass down the fact that an operand is going to be a vector of constants.
This should bring the performance of MultiSource/Benchmarks/PAQ8p/paq8p on x86
back. It had degraded to scalar performance due to my pervious shift cost change
that made all shifts expensive on x86.
radar://13576547
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@178809 91177308-0d34-0410-b5e6-96231b3b80d8
We generate a select with a vectorized condition argument when the condition is
NOT loop invariant. Not the other way around.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@177098 91177308-0d34-0410-b5e6-96231b3b80d8
We want vectorization to happen at -g. Ignore calls to the dbg.value intrinsic
and don't transfer them to the vectorized code.
radar://13378964
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@176768 91177308-0d34-0410-b5e6-96231b3b80d8
This matters for example in following matrix multiply:
int **mmult(int rows, int cols, int **m1, int **m2, int **m3) {
int i, j, k, val;
for (i=0; i<rows; i++) {
for (j=0; j<cols; j++) {
val = 0;
for (k=0; k<cols; k++) {
val += m1[i][k] * m2[k][j];
}
m3[i][j] = val;
}
}
return(m3);
}
Taken from the test-suite benchmark Shootout.
We estimate the cost of the multiply to be 2 while we generate 9 instructions
for it and end up being quite a bit slower than the scalar version (48% on my
machine).
Also, properly differentiate between avx1 and avx2. On avx-1 we still split the
vector into 2 128bits and handle the subvector muls like above with 9
instructions.
Only on avx-2 will we have a cost of 9 for v4i64.
I changed the test case in test/Transforms/LoopVectorize/X86/avx1.ll to use an
add instead of a mul because with a mul we now no longer vectorize. I did
verify that the mul would be indeed more expensive when vectorized with 3
kernels:
for (i ...)
r += a[i] * 3;
for (i ...)
m1[i] = m1[i] * 3; // This matches the test case in avx1.ll
and a matrix multiply.
In each case the vectorized version was considerably slower.
radar://13304919
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@176403 91177308-0d34-0410-b5e6-96231b3b80d8
The LoopVectorizer often runs multiple times on the same function due to inlining.
When this happens the loop vectorizer often vectorizes the same loops multiple times, increasing code size and adding unneeded branches.
With this patch, the vectorizer during vectorization puts metadata on scalar loops and marks them as 'already vectorized' so that it knows to ignore them when it sees them a second time.
PR14448.
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This properly asks TargetLibraryInfo if a call is available and if it is, it
can be translated into the corresponding LLVM builtin. We don't vectorize sqrt()
yet because I'm not sure about the semantics for negative numbers. The other
intrinsic should be exact equivalents to the libm functions.
Differential Revision: http://llvm-reviews.chandlerc.com/D465
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Storing the load/store instructions with the values
and inspect them using Alias Analysis to make sure
they don't alias, since the GEP pointer operand doesn't
take the offset into account.
Trying hard to not add any extra cost to loads and stores
that don't overlap on global values, AA is *only* calculated
if all of the previous attempts failed.
Using biggest vector register size as the stride for the
vectorization access, as we're being conservative and
the cost model (which calculates the real vectorization
factor) is only run after the legalization phase.
We might re-think this relationship in the future, but
for now, I'd rather be safe than sorry.
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In the loop vectorizer cost model, we used to ignore stores/loads of a pointer
type when computing the widest type within a loop. This meant that if we had
only stores/loads of pointers in a loop we would return a widest type of 8bits
(instead of 32 or 64 bit) and therefore a vector factor that was too big.
Now, if we see a consecutive store/load of pointers we use the size of a pointer
(from data layout).
This problem occured in SingleSource/Benchmarks/Shootout-C++/hash.cpp (reduced
test case is the first test in vector_ptr_load_store.ll).
radar://13139343
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Changing ARMBaseTargetMachine to return ARMTargetLowering intead of
the generic one (similar to x86 code).
Tests showing which instructions were added to cast when necessary
or cost zero when not. Downcast to 16 bits are not lowered in NEON,
so costs are not there yet.
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We ignore the cpu frontend and focus on pipeline utilization. We do this because we
don't have a good way to estimate the loop body size at the IR level.
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This separates the check for "too few elements to run the vector loop" from the
"memory overlap" check, giving a lot nicer code and allowing to skip the memory
checks when we're not going to execute the vector code anyways. We still leave
the decision of whether to emit the memory checks as branches or setccs, but it
seems to be doing a good job. If ugly code pops up we may want to emit them as
separate blocks too. Small speedup on MultiSource/Benchmarks/MallocBench/espresso.
Most of this is legwork to allow multiple bypass blocks while updating PHIs,
dominators and loop info.
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the target if it supports the different CAST types. We didn't do this
on X86 because of the different register sizes and types, but on ARM
this makes sense.
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We don't have a detailed analysis on which values are vectorized and which stay scalars in the vectorized loop so we use
another method. We look at reduction variables, loads and stores, which are the only ways to get information in and out
of loop iterations. If the data types are extended and truncated then the cost model will catch the cost of the vector
zext/sext/trunc operations.
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small loops. On small loops post-loop that handles scalars (and runs slower) can take more time to execute than the
rest of the loop. This patch disables widening of loops with a small static trip count.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@171798 91177308-0d34-0410-b5e6-96231b3b80d8
Since subtraction does not commute the loop vectorizer incorrectly vectorizes
reductions such as x = A[i] - x.
Disabling for now.
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1. Add code to estimate register pressure.
2. Add code to select the unroll factor based on register pressure.
3. Add bits to TargetTransformInfo to provide the number of registers.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@171469 91177308-0d34-0410-b5e6-96231b3b80d8
LCSSA PHIs may have undef values. The vectorizer updates values that are used by outside users such as PHIs.
The bug happened because undefs are not loop values. This patch handles these PHIs.
PR14725
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the cost of arithmetic functions. We now assume that the cost of arithmetic
operations that are marked as Legal or Promote is low, but ops that are
marked as custom are higher.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@171002 91177308-0d34-0410-b5e6-96231b3b80d8
memory bound checks. Before the fix we were able to vectorize this loop from
the Livermore Loops benchmark:
for ( k=1 ; k<n ; k++ )
x[k] = x[k-1] + y[k];
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@170811 91177308-0d34-0410-b5e6-96231b3b80d8
Before if-conversion we could check if a value is loop invariant
if it was declared inside the basic block. Now that loops have
multiple blocks this check is incorrect.
This fixes External/SPEC/CINT95/099_go/099_go
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- An MVT can become an EVT when being split (e.g. v2i8 -> v1i8, the latter doesn't exist)
- Return the scalar value when an MVT is scalarized (v1i64 -> i64)
Fixes PR14639ff.
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