I closely followed the precedents set by the vectorizer:
* With -Rpass-missed, the loop is reported with further details pointing
to -Rpass--analysis.
* -Rpass-analysis reports the details why distribution has failed.
* Regardless of -Rpass*, when distribution fails for a loop where
distribution was forced with the pragma, a warning is produced according
to -Wpass-failed. In this case the analysis info is also printed even
without -Rpass-analysis.
llvm-svn: 267952
The next patch will start using these for -Rpass-analysis so they won't
be internal-only anymore.
Move the 'Skipping; ' prefix that some of the message are using into the
'fail' function. We don't want to include this prefix in
the -Rpass-analysis report.
llvm-svn: 267951
Summary:
D19403 adds a new pragma for loop distribution. This change adds
support for the corresponding metadata that the pragma is translated to
by the FE.
As part of this I had to rethink the flag -enable-loop-distribute. My
goal was to be backward compatible with the existing behavior:
A1. pass is off by default from the optimization pipeline
unless -enable-loop-distribute is specified
A2. pass is on when invoked directly from opt (e.g. for unit-testing)
The new pragma/metadata overrides these defaults so the new behavior is:
B1. A1 + enable distribution for individual loop with the pragma/metadata
B2. A2 + disable distribution for individual loop with the pragma/metadata
The default value whether the pass is on or off comes from the initiator
of the pass. From the PassManagerBuilder the default is off, from opt
it's on.
I moved -enable-loop-distribute under the pass. If the flag is
specified it overrides the default from above.
Then the pragma/metadata can further modifies this per loop.
As a side-effect, we can now also use -enable-loop-distribute=0 from opt
to emulate the default from the optimization pipeline. So to be precise
this is the new behavior:
C1. pass is off by default from the optimization pipeline
unless -enable-loop-distribute or the pragma/metadata enables it
C2. pass is on when invoked directly from opt
unless -enable-loop-distribute=0 or the pragma/metadata disables it
Reviewers: hfinkel
Subscribers: joker.eph, mzolotukhin, llvm-commits
Differential Revision: http://reviews.llvm.org/D19431
llvm-svn: 267672
This splits out the per-loop functionality from the Pass class.
With this the fact whether the loop is forced-distribute with the new
metadata/pragma can be cached in the per-loop class rather than passed
around.
llvm-svn: 267643
Summary:
If we decide to version a loop to benefit a transformation, it makes
sense to record the now non-aliasing accesses in the newly versioned
loop. This allows non-aliasing information to be used by subsequent
passes.
One example is 456.hmmer in SPECint2006 where after loop distribution,
we vectorize one of the newly distributed loops. To vectorize we
version this loop to fully disambiguate may-aliasing accesses. If we
add the noalias markers, we can use the same information in a later DSE
pass to eliminate some dead stores which amounts to ~25% of the
instructions of this hot memory-pipeline-bound loop. The overall
performance improves by 18% on our ARM64.
The scoped noalias annotation is added in LoopVersioning. The patch
then enables this for loop distribution. A follow-on patch will enable
it for the vectorizer. Eventually this should be run by default when
versioning the loop but first I'd like to get some feedback whether my
understanding and application of scoped noalias metadata is correct.
Essentially my approach was to have a separate alias domain for each
versioning of the loop. For example, if we first version in loop
distribution and then in vectorization of the distributed loops, we have
a different set of memchecks for each versioning. By keeping the scopes
in different domains they can conveniently be defined independently
since different alias domains don't affect each other.
As written, I also have a separate domain for each loop. This is not
necessary and we could save some metadata here by using the same domain
across the different loops. I don't think it's a big deal either way.
Probably the best is to review the tests first to see if I mapped this
problem correctly to scoped noalias markers. I have plenty of comments
in the tests.
Note that the interface is prepared for the vectorizer which needs the
annotateInstWithNoAlias API. The vectorizer does not use LoopVersioning
so we need a way to pass in the versioned instructions. This is also
why the maps have to become part of the object state.
Also currently, we only have an AA-aware DSE after the vectorizer if we
also run the LTO pipeline. Depending how widely this triggers we may
want to schedule a DSE toward the end of the regular pass pipeline.
Reviewers: hfinkel, nadav, ashutosh.nema
Subscribers: mssimpso, aemerson, llvm-commits, mcrosier
Differential Revision: http://reviews.llvm.org/D16712
llvm-svn: 263743
A large number of loop utility functions take a `Pass *` and reach
into it to find out which analyses to preserve. There are a number of
problems with this:
- The APIs have access to pretty well any Pass state they want, so
it's hard to tell what they may or may not do.
- Other APIs have copied these and pass around a `Pass *` even though
they don't even use it. Some of these just hand a nullptr to the API
since the callers don't even have a pass available.
- Passes in the new pass manager don't work like the current ones, so
the APIs can't be used as is there.
Instead, we should explicitly thread the analysis results that we
actually care about through these APIs. This is both simpler and more
reusable.
llvm-svn: 255669
ScalarEvolution.h, in order to avoid cyclic dependencies between the Transform
and Analysis modules:
[LV][LAA] Add a layer over SCEV to apply run-time checked knowledge on SCEV expressions
Summary:
This change creates a layer over ScalarEvolution for LAA and LV, and centralizes the
usage of SCEV predicates. The SCEVPredicatedLayer takes the statically deduced knowledge
by ScalarEvolution and applies the knowledge from the SCEV predicates. The end goal is
that both LAA and LV should use this interface everywhere.
This also solves a problem involving the result of SCEV expression rewritting when
the predicate changes. Suppose we have the expression (sext {a,+,b}) and two predicates
P1: {a,+,b} has nsw
P2: b = 1.
Applying P1 and then P2 gives us {a,+,1}, while applying P2 and the P1 gives us
sext({a,+,1}) (the AddRec expression was changed by P2 so P1 no longer applies).
The SCEVPredicatedLayer maintains the order of transformations by feeding back
the results of previous transformations into new transformations, and therefore
avoiding this issue.
The SCEVPredicatedLayer maintains a cache to remember the results of previous
SCEV rewritting results. This also has the benefit of reducing the overall number
of expression rewrites.
Reviewers: mzolotukhin, anemet
Subscribers: jmolloy, sanjoy, llvm-commits
Differential Revision: http://reviews.llvm.org/D14296
llvm-svn: 255122
Summary:
This change creates a layer over ScalarEvolution for LAA and LV, and centralizes the
usage of SCEV predicates. The SCEVPredicatedLayer takes the statically deduced knowledge
by ScalarEvolution and applies the knowledge from the SCEV predicates. The end goal is
that both LAA and LV should use this interface everywhere.
This also solves a problem involving the result of SCEV expression rewritting when
the predicate changes. Suppose we have the expression (sext {a,+,b}) and two predicates
P1: {a,+,b} has nsw
P2: b = 1.
Applying P1 and then P2 gives us {a,+,1}, while applying P2 and the P1 gives us
sext({a,+,1}) (the AddRec expression was changed by P2 so P1 no longer applies).
The SCEVPredicatedLayer maintains the order of transformations by feeding back
the results of previous transformations into new transformations, and therefore
avoiding this issue.
The SCEVPredicatedLayer maintains a cache to remember the results of previous
SCEV rewritting results. This also has the benefit of reducing the overall number
of expression rewrites.
Reviewers: mzolotukhin, anemet
Subscribers: jmolloy, sanjoy, llvm-commits
Differential Revision: http://reviews.llvm.org/D14296
llvm-svn: 255115
Summary:
LAA currently generates a set of SCEV predicates that must be checked by users.
In the case of Loop Distribute/Loop Load Elimination, no such predicates could have
been emitted, since we don't allow stride versioning. However, in the future there
could be SCEV predicates that will need to be checked.
This change adds support for SCEV predicate versioning in the Loop Distribute, Loop
Load Eliminate and the loop versioning infrastructure.
Reviewers: anemet
Subscribers: mssimpso, sanjoy, llvm-commits
Differential Revision: http://reviews.llvm.org/D14240
llvm-svn: 252467
Summary:
We now collect all types of dependences including lexically forward
deps not just "interesting" ones.
Reviewers: hfinkel
Subscribers: rengolin, llvm-commits
Differential Revision: http://reviews.llvm.org/D13256
llvm-svn: 251985
Since Ashutosh made findDefsUsedOutsideOfLoop public, we can clean this
up.
Now clients that don't compute DefsUsedOutsideOfLoop can just call
versionLoop() and computing DefsUsedOutsideOfLoop will happen
implicitly. With that there is no reason to expose addPHINodes anymore.
Ashutosh, you can now drop the calls to findDefsUsedOutsideOfLoop and
addPHINodes in LVerLICM and things should just work.
llvm-svn: 245579
This is the full set of checks that clients can further filter. IOW,
it's client-agnostic. This makes LAA complete in the sense that it now
provides the two main results of its analysis precomputed:
1. memory dependences via getDepChecker().getInsterestingDependences()
2. run-time checks via getRuntimePointerCheck().getChecks()
However, as a consequence we now compute this information pro-actively.
Thus if the client decides to skip the loop based on the dependences
we've computed the checks unnecessarily. In order to see whether this
was a significant overhead I checked compile time on SPEC2k6 LTO bitcode
files. The change was in the noise.
The checks are generated in canCheckPtrAtRT, at the same place where we
used to call groupChecks to merge checks.
llvm-svn: 244368
Before, we were passing the pointer partitions to LAA. Now, we get all
the checks from LAA and filter out the checks within partitions in
LoopDistribution.
This effectively concludes the steps to move filtering memchecks from
LAA into its clients. There is still some cleanup left to remove the
unused interfaces in LAA that still take PtrPartition.
(Moving this functionality to LoopDistribution also requires
needsChecking on pointers to be made public.)
llvm-svn: 243613
Before the patch, the checks were generated internally in
addRuntimeCheck. Now, we use the new overloaded version of
addRuntimeCheck that takes the ready-made set of checks as a parameter.
The checks are now generated by the client (LoopDistribution) with the
new RuntimePointerChecking::generateChecks API.
Also the new printChecks API is used to print out the checks for
debugging.
This is to continue the transition over to the new model whereby clients
will get the full set of checks from LAA, filter it and then pass it to
LoopVersioning and in turn to addRuntimeCheck.
llvm-svn: 243382
Instead of the pattern
for (auto I = x.rbegin(), E = x.end(); I != E; ++I)
we can use make_range to construct the reverse range and iterate using
that instead.
llvm-svn: 243163
I am planning to add more nested classes inside RuntimePointerCheck so
all these triple-nesting would be hard to follow.
Also rename it to RuntimePointerChecking (i.e. append 'ing').
llvm-svn: 242218
Summary:
The class will obviously need improvement down the road. For one, there
is no reason that addPHINodes would have to be exposed like that. I
will make this and other improvements in follow-up patches.
The main goal is to be able to share this functionality. The
LoopLoadElimination pass I am working on needs it too. Later we can
move other clients as well (LV and Ashutosh's LICMVer).
Reviewers: hfinkel, ashutosh.nema
Subscribers: llvm-commits
Differential Revision: http://reviews.llvm.org/D10577
llvm-svn: 241932
Summary:
This makes them available to the LoopVersioning class as that is moved
to its own module in the next patch.
Reviewers: ashutosh.nema, hfinkel
Subscribers: llvm-commits
Differential Revision: http://reviews.llvm.org/D10576
llvm-svn: 241931
As with the previous patch, the goal is to turn the class into a general
loop-versioning class. This patch removes any references to loop
distribution.
llvm-svn: 240352
Summary:
This implements the initial version as was proposed earlier this year
(http://lists.cs.uiuc.edu/pipermail/llvmdev/2015-January/080462.html).
Since then Loop Access Analysis was split out from the Loop Vectorizer
and was made into a separate analysis pass. Loop Distribution becomes
the second user of this analysis.
The pass is off by default and can be enabled
with -enable-loop-distribution. There is currently no notion of
profitability; if there is a loop with dependence cycles, the pass will
try to split them off from other memory operations into a separate loop.
I decided to remove the control-dependence calculation from this first
version. This and the issues with the PDT are actively discussed so it
probably makes sense to treat it separately. Right now I just mark all
terminator instruction required which keeps identical CFGs for each
distributed loop. This seems to be working pretty well for 456.hmmer
where even though there is an empty if-then block in the distributed
loop initially, it gets completely removed.
The pass keeps DominatorTree and LoopInfo updated. I've tested this
with -loop-distribute-verify with the testsuite where we distribute ~90
loops. SimplifyLoop is violated in some cases and I have a FIXME
covering this.
Reviewers: hfinkel, nadav, aschwaighofer
Reviewed By: aschwaighofer
Subscribers: llvm-commits
Differential Revision: http://reviews.llvm.org/D8831
llvm-svn: 237358
