Add address sanitizer instrumentation support for accesses to global
and constant address spaces in AMDGPU. It strictly avoids instrumenting
the stack and assumes x86 as the host.
Reviewed by: vitalybuka
Differential Revision: https://reviews.llvm.org/D99071
This patch introduces a helper to obtain an iterator range for the
PHI-like recipes in a block.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D100101
The problem is the following. With fast8, we broke an important
invariant when loading shadows. A wide shadow of 64 bits used to
correspond to 4 application bytes with fast16; so, generating a single
load was okay since those 4 application bytes would share a single
origin. Now, using fast8, a wide shadow of 64 bits corresponds to 8
application bytes that should be backed by 2 origins (but we kept
generating just one).
Let’s say our wide shadow is 64-bit and consists of the following:
0xABCDEFGH. To check if we need the second origin value, we could do
the following (on the 64-bit wide shadow) case:
- bitwise shift the wide shadow left by 32 bits (yielding 0xEFGH0000)
- push the result along with the first origin load to the shadow/origin vectors
- load the second 32-bit origin of the 64-bit wide shadow
- push the wide shadow along with the second origin to the shadow/origin vectors.
The combineOrigins would then select the second origin if the wide
shadow is of the form 0xABCDE0000. The tests illustrate how this
change affects the generated bitcode.
Reviewed By: stephan.yichao.zhao
Differential Revision: https://reviews.llvm.org/D101584
If the extracts from the non-power-2 vectors are recognized as shuffles,
need some extra checks to not crash cost calculations if trying to gext
the ecost for subvector extracts. In this case need to check carefully
that we do not exit out of bounds of the original vector, otherwise the
TTI's cost model will crash on assert.
Differential Revision: https://reviews.llvm.org/D101477
Previous attempt to fix infinite recursion in min/max reassociation was not fully successful (D100170). Newly discovered failing case is due to not properly handled when there is a single use. It should be processed separately from 2 uses case.
Reviewed By: mkazantsev
Differential Revision: https://reviews.llvm.org/D101359
Hoisting and sinking instructions out of conditional blocks enables
additional vectorization by:
1. Executing memory accesses unconditionally.
2. Reducing the number of instructions that need predication.
After disabling early hoisting / sinking, we miss out on a few
vectorization opportunities. One of those is causing a ~10% performance
regression in one of the Geekbench benchmarks on AArch64.
This patch tires to recover the regression by running hoisting/sinking
as part of a SimplifyCFG run after LoopRotate and before LoopVectorize.
Note that in the legacy pass-manager, we run LoopRotate just before
vectorization again and there's no SimplifyCFG run in between, so the
sinking/hoisting may impact the later run on LoopRotate. But the impact
should be limited and the benefit of hosting/sinking at this stage
should outweigh the risk of not rotating.
Compile-time impact looks slightly positive for most cases.
http://llvm-compile-time-tracker.com/compare.php?from=2ea7fb7b1c045a7d60fcccf3df3ebb26aa3699e5&to=e58b4a763c691da651f25996aad619cb3d946faf&stat=instructions
NewPM-O3: geomean -0.19%
NewPM-ReleaseThinLTO: geoman -0.54%
NewPM-ReleaseLTO-g: geomean -0.03%
With a few benchmarks seeing a notable increase, but also some
improvements.
Alternative to D101290.
Reviewed By: lebedev.ri
Differential Revision: https://reviews.llvm.org/D101468
Added an extra analysis for better choosing of shuffle kind in
getShuffleCost functions for better cost estimation if mask was
provided.
Differential Revision: https://reviews.llvm.org/D100865
The profitability check is: we don't want to create more than a single PHI
per instruction sunk. We need to create the PHI unless we'll sink
all of it's would-be incoming values.
But there is a caveat there.
This profitability check doesn't converge on the first iteration!
If we first decide that we want to sink 10 instructions,
but then determine that 5'th one is unprofitable to sink,
that may result in us not sinking some instructions that
resulted in determining that some other instruction
we've determined to be profitable to sink becoming unprofitable.
So we need to iterate until we converge, as in determine
that all leftover instructions are profitable to sink.
But, the direct approach of just re-iterating seems dumb,
because in the worst case we'd find that the last instruction
is unprofitable, which would result in revisiting instructions
many many times.
Instead, i think we can get away with just two passes - forward and backward.
However then it isn't obvious what is the most performant way to update
InstructionsToSink.
Added an extra analysis for better choosing of shuffle kind in
getShuffleCost functions for better cost estimation if mask was
provided.
Differential Revision: https://reviews.llvm.org/D100865
As suggested in D99294, this adds a getVPSingleValue helper to use for
recipes that are guaranteed to define a single value. This replaces uses
of getVPValue() which used to default to I = 0.
Pointers in non-zero address spaces need to be address space
casted before appending to the used list.
Reviewed by: vitalybuka
Differential Revision: https://reviews.llvm.org/D101363
This patch makes sure that globals in supported address spaces
will be replaced by globals with red zones in the same address
space by copying the address space.
Reviewed By: vitalybuka
Differential Revision: https://reviews.llvm.org/D101362
While we have a known profitability issue for sinking in presence of
non-unconditional predecessors, there isn't any known issues
for having multiple such non-unconditional predecessors,
so said restriction appears to be artificial. Lift it.
We can just eagerly pre-check all the instructions that we *could*
sink that we'd actually want to sink them, clamping the number of
instructions that we'll sink to stop just before the first unprofitable one.
This patch causes the loop vectorizer to not interleave loops that have
nounroll loop hints (llvm.loop.unroll.disable and llvm.loop.unroll_count(1)).
Note that if a particular interleave count is being requested
(through llvm.loop.interleave_count), it will still be honoured, regardless
of the presence of nounroll hints.
Reviewed By: Meinersbur
Differential Revision: https://reviews.llvm.org/D101374
Before this change LLVM cannot simplify printf in following cases:
printf("%s", "") --> noop
printf("%s", str"\n") --> puts(str)
From the other hand GCC can perform such transformations for many years:
https://godbolt.org/z/7nnqbedfe
Differential Revision: https://reviews.llvm.org/D100724
This patch fixes a crash encountered when vectorising the following loop:
void foo(float *dst, float *src, long long n) {
for (long long i = 0; i < n; i++)
dst[i] = -src[i];
}
using scalable vectors. I've added a test to
Transforms/LoopVectorize/AArch64/sve-basic-vec.ll
as well as cleaned up the other tests in the same file.
Differential Revision: https://reviews.llvm.org/D98054
If the first tree element is vectorize and the second is gather, it
still might be profitable to vectorize it if the gather node contains
less scalars to vectorize than the original tree node. It might be
profitable to use shuffles.
Differential Revision: https://reviews.llvm.org/D101397
This patch simplifies the calculation of certain costs in
getInstructionCost when isScalarAfterVectorization() returns a true value.
There are a few places where we multiply a cost by a number N, i.e.
unsigned N = isScalarAfterVectorization(I, VF) ? VF.getKnownMinValue() : 1;
return N * TTI.getArithmeticInstrCost(...
After some investigation it seems that there are only these cases that occur
in practice:
1. VF is a scalar, in which case N = 1.
2. VF is a vector. We can only get here if: a) the instruction is a
GEP/bitcast/PHI with scalar uses, or b) this is an update to an induction
variable that remains scalar.
I have changed the code so that N is assumed to always be 1. For GEPs
the cost is always 0, since this is calculated later on as part of the
load/store cost. PHI nodes are costed separately and were never previously
multiplied by VF. For all other cases I have added an assert that none of
the users needs scalarising, which didn't fire in any unit tests.
Only one test required fixing and I believe the original cost for the scalar
add instruction to have been wrong, since only one copy remains after
vectorisation.
I have also added a new test for the case when a pointer PHI feeds directly
into a store that will be scalarised as we were previously never testing it.
Differential Revision: https://reviews.llvm.org/D99718
This patch also refactors the way the feasible max VF is calculated,
although this is NFC for fixed-width vectors.
After this change scalable VF hints are no longer truncated/clamped
to a shorter scalable VF, nor does it drop the 'scalable flag' from
the suggested VF to vectorize with a similar VF that is fixed.
Instead, the hint is ignored which means the vectorizer is free
to find a more suitable VF, using the CostModel to determine the
best possible VF.
Reviewed By: c-rhodes, fhahn
Differential Revision: https://reviews.llvm.org/D98509
When using the -enable-strict-reductions flag where UF>1 we generate multiple
Phi nodes, though only one of these is used as an input to the vector.reduce.fadd
intrinsics. The unused Phi nodes are removed later by instcombine.
This patch changes widenPHIInstruction/fixReduction to only generate
one Phi, and adds an additional test for unrolling to strict-fadd.ll
Reviewed By: david-arm
Differential Revision: https://reviews.llvm.org/D100570
Solves PR11896
As noted, this can be improved futher (calloc -> malloc) in some cases. But for know, this is the first step.
Reviewed By: nikic
Differential Revision: https://reviews.llvm.org/D101391
This patch simplifies the calculation of certain costs in
getInstructionCost when isScalarAfterVectorization() returns a true value.
There are a few places where we multiply a cost by a number N, i.e.
unsigned N = isScalarAfterVectorization(I, VF) ? VF.getKnownMinValue() : 1;
return N * TTI.getArithmeticInstrCost(...
After some investigation it seems that there are only these cases that occur
in practice:
1. VF is a scalar, in which case N = 1.
2. VF is a vector. We can only get here if: a) the instruction is a
GEP/bitcast/PHI with scalar uses, or b) this is an update to an induction
variable that remains scalar.
I have changed the code so that N is assumed to always be 1. For GEPs
the cost is always 0, since this is calculated later on as part of the
load/store cost. PHI nodes are costed separately and were never previously
multiplied by VF. For all other cases I have added an assert that none of
the users needs scalarising, which didn't fire in any unit tests.
Only one test required fixing and I believe the original cost for the scalar
add instruction to have been wrong, since only one copy remains after
vectorisation.
I have also added a new test for the case when a pointer PHI feeds directly
into a store that will be scalarised as we were previously never testing it.
Differential Revision: https://reviews.llvm.org/D99718
Reshabh Sharma