cold loops as-if they were being optimized for size.
Nothing fancy here. Simply test case included. The nice thing is that we
can now incrementally build on top of this to drive other heuristics.
All of the infrastructure work is done to get the profile information
into this layer.
The remaining work necessary to make this a fully general purpose loop
unroller for very hot loops is to make it a fully general purpose loop
unroller. Things I know of but am not going to have time to benchmark
and fix in the immediate future:
1) Don't disable the entire pass when the target is lacking vector
registers. This really doesn't make any sense any more.
2) Teach the unroller at least and the vectorizer potentially to handle
non-if-converted loops. This is trivial for the unroller but hard for
the vectorizer.
3) Compute the relative hotness of the loop and thread that down to the
various places that make cost tradeoffs (very likely only the
unroller makes sense here, and then only when dealing with loops that
are small enough for unrolling to not completely blow out the LSD).
I'm still dubious how useful hotness information will be. So far, my
experiments show that if we can get the correct logic for determining
when unrolling actually helps performance, the code size impact is
completely unimportant and we can unroll in all cases. But at least
we'll no longer burn code size on cold code.
One somewhat unrelated idea that I've had forever but not had time to
implement: mark all functions which are only reachable via the global
constructors rigging in the module as optsize. This would also decrease
the impact of any more aggressive heuristics here on code size.
llvm-svn: 200219
object and fewer pointless variables.
Also, add a clarifying comment and a FIXME because the code which
disables *all* vectorization if we can't use implicit floating point
instructions just makes no sense at all.
llvm-svn: 200214
powers of two. This is essentially always the correct thing given the
impact on alignment, scaling factors that can be used in addressing
modes, etc. Also, fix the management of the unroll vs. small loop cost
to more accurately model things with this world.
Enhance a test case to actually exercise more of the unroll machinery if
using synthetic constants rather than a specific target model. Before
this change, with the added flags this test will unroll 3 times instead
of either 2 or 4 (the two sensible answers).
While I don't expect this to make a huge difference, if there are lots
of loops sitting right on the edge of hitting the 'small unroll' factor,
they might change behavior. However, I've benchmarked moving the small
loop cost up and down in many various ways and by a huge factor (2x)
without seeing more than 0.2% code size growth. Small adjustments such
as the series that led up here have led to about 1% improvement on some
benchmarks, but it is very close to the noise floor so I mostly checked
that nothing regressed. Let me know if you see bad behavior on other
targets but I don't expect this to be a sufficiently dramatic change to
trigger anything.
llvm-svn: 200213
with the unrolling behavior in the loop vectorizer. No functionality
changed at this point.
These are a bit hack-y, but talking with Hal, there doesn't seem to be
a cleaner way to easily experiment with different thresholds here and he
was also interested in them so I wanted to commit them. Suggestions for
improvement are very welcome here.
llvm-svn: 200212
number of vector registers rather than toggling between vector and
scalar register number based on VF. I don't have a test case as
I spotted this by inspection and on X86 it only makes a difference if
your target is lacking SSE and thus has *no* vector registers.
If someone wants to add a test case for this for ARM or somewhere else
where this is more significant, that would be awesome.
Also made the variable name a bit more sensible while I'm here.
llvm-svn: 200211
LoopVectorize pass.
The logic here doesn't make much sense. We *only* unrolled if the
unvectorized loop was a reduction loop with a single basic block *and*
small loop body. The reduction part in particular doesn't make much
sense. Instead, if we just fall through to the vectorized unroll logic
it makes more sense of unrolling if there is a vectorized reduction that
could be hacked on by the SLP vectorizer *or* if the loop is small.
This is mostly a cleanup and nothing in the test suite really exercises
this, but I did run benchmarks across this change and saw no really
significant changes.
llvm-svn: 200198
a FunctionPass. With this change the loop vectorizer no longer is a loop
pass and can readily depend on function analyses. In particular, with
this change we no longer have to form a loop pass manager to run the
loop vectorizer which simplifies the entire pass management of LLVM.
The next step here is to teach the loop vectorizer to leverage profile
information through the profile information providing analysis passes.
llvm-svn: 200074
a reduction.
Really. Under certain circumstances (the use list of an instruction has to be
set up right - hence the extra pass in the test case) we would not recognize
when a value in a potential reduction cycle was used multiple times by the
reduction cycle.
Fixes PR18526.
radar://15851149
llvm-svn: 199570
can be used by both the new pass manager and the old.
This removes it from any of the virtual mess of the pass interfaces and
lets it derive cleanly from the DominatorTreeBase<> template. In turn,
tons of boilerplate interface can be nuked and it turns into a very
straightforward extension of the base DominatorTree interface.
The old analysis pass is now a simple wrapper. The names and style of
this split should match the split between CallGraph and
CallGraphWrapperPass. All of the users of DominatorTree have been
updated to match using many of the same tricks as with CallGraph. The
goal is that the common type remains the resulting DominatorTree rather
than the pass. This will make subsequent work toward the new pass
manager significantly easier.
Also in numerous places things became cleaner because I switched from
re-running the pass (!!! mid way through some other passes run!!!) to
directly recomputing the domtree.
llvm-svn: 199104
directory. These passes are already defined in the IR library, and it
doesn't make any sense to have the headers in Analysis.
Long term, I think there is going to be a much better way to divide
these matters. The dominators code should be fully separated into the
abstract graph algorithm and have that put in Support where it becomes
obvious that evn Clang's CFGBlock's can use it. Then the verifier can
manually construct dominance information from the Support-driven
interface while the Analysis library can provide a pass which both
caches, reconstructs, and supports a nice update API.
But those are very long term, and so I don't want to leave the really
confusing structure until that day arrives.
llvm-svn: 199082
for (i = 0; i < N; ++i)
A[i * Stride1] += B[i * Stride2];
We take loops like this and check that the symbolic strides 'Strided1/2' are one
and drop to the scalar loop if they are not.
This is currently disabled by default and hidden behind the flag
'enable-mem-access-versioning'.
radar://13075509
llvm-svn: 198950
subsequent changes are easier to review. About to fix some layering
issues, and wanted to separate out the necessary churn.
Also comment and sink the include of "Windows.h" in three .inc files to
match the usage in Memory.inc.
llvm-svn: 198685
A phi node operand or an instruction operand could be a constant expression that
can trap (division). Check that we don't vectorize such cases.
PR16729
radar://15653590
llvm-svn: 197449
The intended behaviour is to force vectorization on the presence
of the flag (either turn on or off), and to continue the behaviour
as expected in its absence. Tests were added to make sure the all
cases are covered in opt. No tests were added in other tools with
the assumption that they should use the PassManagerBuilder in the
same way.
This patch also removes the outdated -late-vectorize flag, which was
on by default and not helping much.
The pragma metadata is being attached to the same place as other loop
metadata, but nothing forbids one from attaching it to a function
(to enable #pragma optimize) or basic blocks (to hint the basic-block
vectorizers), etc. The logic should be the same all around.
Patches to Clang to produce the metadata will be produced after the
initial implementation is agreed upon and committed. Patches to other
vectorizers (such as SLP and BB) will be added once we're happy with
the pass manager changes.
llvm-svn: 196537
We use CSEBlocks to initialize a worklist:
SmallVector<BasicBlock *, 8> CSEWorkList(CSEBlocks.begin(), CSEBlocks.end());
so it must have a deterministic order.
llvm-svn: 196520
We were creating external uses for scalar values in MustGather entries that also
had a ScalarToTreeEntry (they also are present in a vectorized tuple). This
meant we would keep a value 'alive' as a scalar and vectorized causing havoc.
This is not necessary because when we create a MustGather vector we explicitly
create external uses entries for the insertelement instructions of the
MustGather vector elements.
Fixes PR18129.
radar://15582184
llvm-svn: 196508
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.
llvm-svn: 195787
we generate PHI nodes with multiple entries from the same basic block but
with different values. Enabling CSE on ExtractElement instructions make sure
that all of the RAUWed instructions are the same.
llvm-svn: 195773
SLP vectorization. Based on the code in BBVectorizer.
Fixes PR17741.
Patch by Raul Silvera, reviewed by Hal and Nadav. Reformatted by my
driving of clang-format. =]
llvm-svn: 195528
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
llvm-svn: 195162
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
llvm-svn: 195008
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.
llvm-svn: 194876
Instead of doing a RPO traversal of the whole function remember the blocks
containing gathers (typically <= 2) and scan them in dominator-first order.
The actual CSE is still quadratic, but I'm not confident that adding a
scoped hash table here is worth it as we're only looking at the generated
instructions and not arbitrary code.
llvm-svn: 193956
Doing this with a hash map doesn't change behavior and avoids calling
isIdenticalTo O(n^2) times. This should probably eventually move into a utility
class shared with EarlyCSE and the limited CSE in the SLPVectorizer.
llvm-svn: 193926
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
llvm-svn: 193891
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
llvm-svn: 193853
By vectorizing a series of srl, or, ... instructions we have obfuscated the
intention so much that the backend does not know how to fold this code away.
radar://15336950
llvm-svn: 193573
No test case, because with the current cost model we don't see a difference.
An upcoming ARM memory cost model change will expose and test this bug.
radar://15332579
llvm-svn: 193572
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.
llvm-svn: 193434
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.
llvm-svn: 193349
Before this patch we relied on the order of phi nodes when we looked for phi
nodes of the same type. This could prevent vectorization of cases where there
was a phi node of a second type in between phi nodes of some type.
This is important for vectorization of an internal graphics kernel. On the test
suite + external on x86_64 (and on a run on armv7s) it showed no impact on
either performance or compile time.
radar://15024459
llvm-svn: 192537
Sort the operands of the other entries in the current vectorization root
according to the first entry's operands opcodes.
%conv0 = uitofp ...
%load0 = load float ...
= fmul %conv0, %load0
= fmul %load0, %conv1
= fmul %load0, %conv2
Make sure that we recursively vectorize <%conv0, %conv1, %conv2> and <%load0,
%load0, %load0>.
This makes it more likely to obtain vectorizable trees. We have to be careful
when we sort that we don't destroy 'good' existing ordering implied by source
order.
radar://15080067
llvm-svn: 191977
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.
llvm-svn: 191862
This recursively strips all GEPs like the existing code. It also handles bitcasts and
other operations that do not change the pointer value.
llvm-svn: 191847
Inspired by the object from the SLPVectorizer. This found a minor bug in the
debug loc restoration in the vectorizer where the location of a following
instruction was attached instead of the location from the original instruction.
llvm-svn: 191673
We were previously using getFirstInsertionPt to insert PHI
instructions when vectorizing, but getFirstInsertionPt also skips past
landingpads, causing this to generate invalid IR.
We can avoid this issue by using getFirstNonPHI instead.
llvm-svn: 191526
Put them under a separate flag for experimentation. They are more likely to
interfere with loop vectorization which happens later in the pass pipeline.
llvm-svn: 191371
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.
llvm-svn: 191206
Reapply r191108 with a fix for a memory corruption error I introduced. Of
course, we can't reference the scalars that we replace by vectorizing and then
call their eraseFromParent method. I only 'needed' the scalars to get the
DebugLoc. Just store the DebugLoc before actually vectorizing instead. As a nice
side effect, this also simplifies the interface between BoUpSLP and the
HorizontalReduction class to returning a value pointer (the vectorized tree
root).
radar://14607682
llvm-svn: 191123
Match reductions starting at binary operation feeding into a phi. The code
handles trees like
r += v1 + v2 + v3 ...
and
r += v1
r += v2
...
and
r *= v1 + v2 + ...
We currently only handle associative operations (add, fadd fast).
The code can now also handle reductions feeding into stores.
a[i] = v1 + v2 + v3 + ...
The code is currently disabled behind the flag "-slp-vectorize-hor". The cost
model for most architectures is not there yet.
I found one opportunity of a horizontal reduction feeding a phi in TSVC
(LoopRerolling-flt) and there are several opportunities where reductions feed
into stores.
radar://14607682
llvm-svn: 191108
XCore target: Add XCoreTargetTransformInfo
This is where getNumberOfRegisters() resides, which in turn returns the
number of vector registers (=0).
llvm-svn: 190936
We can't insert an insertelement after an invoke. We would have to split a
critical edge. So when we see a phi node that uses an invoke we just give up.
radar://14990770
llvm-svn: 190871
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.
llvm-svn: 190790
1) If the width of vectorization list candidate is bigger than vector reg width, we will break it down to fit the vector reg.
2) We do not vectorize the width which is not power of two.
The performance result shows it will help some spec benchmarks. mesa improved 6.97% and ammp improved 1.54%.
llvm-svn: 189830
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).
llvm-svn: 189499
This patch merges LoopVectorize of InnerLoopVectorizer and InnerLoopUnroller by adding checks for VF=1. This helps in erasing the Unroller code that is almost identical to the InnerLoopVectorizer code.
llvm-svn: 189391
The builder inserts from before the insert point,
not after, so this would insert before the last
instruction in the bundle instead of after it.
I'm not sure if this can actually be a problem
with any of the current insertions.
llvm-svn: 189285
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%
llvm-svn: 189281
using GEPs. Previously, it used a number of different heuristics for
analyzing the GEPs. Several of these were conservatively correct, but
failed to fall back to SCEV even when SCEV might have given a reasonable
answer. One was simply incorrect in how it was formulated.
There was good code already to recursively evaluate the constant offsets
in GEPs, look through pointer casts, etc. I gathered this into a form
code like the SLP code can use in a previous commit, which allows all of
this code to become quite simple.
There is some performance (compile time) concern here at first glance as
we're directly attempting to walk both pointers constant GEP chains.
However, a couple of thoughts:
1) The very common cases where there is a dynamic pointer, and a second
pointer at a constant offset (usually a stride) from it, this code
will actually not do any unnecessary work.
2) InstCombine and other passes work very hard to collapse constant
GEPs, so it will be rare that we iterate here for a long time.
That said, if there remain performance problems here, there are some
obvious things that can improve the situation immensely. Doing
a vectorizer-pass-wide memoizer for each individual layer of pointer
values, their base values, and the constant offset is likely to be able
to completely remove redundant work and strictly limit the scaling of
the work to scrape these GEPs. Since this optimization was not done on
the prior version (which would still benefit from it), I've not done it
here. But if folks have benchmarks that slow down it should be straight
forward for them to add.
I've added a test case, but I'm not really confident of the amount of
testing done for different access patterns, strides, and pointer
manipulation.
llvm-svn: 189007
