Slightly improves the precision of GlobalsAA in certain situations, and
makes the behavior of optimization passes more predictable.
Differential Revision: https://reviews.llvm.org/D24104
llvm-svn: 283165
Summary: Added 6 new target hooks for the vectorizer in order to filter types, handle size constraints and decide how to split chains.
Reviewers: tstellarAMD, arsenm
Subscribers: arsenm, mzolotukhin, wdng, llvm-commits, nhaehnle
Differential Revision: https://reviews.llvm.org/D24727
llvm-svn: 283099
This was first landed in rL283058 and subsequenlty reverted since a
change this depends on (rL283057) was buggy and had to be reverted.
llvm-svn: 283079
They've broken the sanitizer-bootstrap bots. Reverting while I investigate.
Original commit messages:
r283057: "[ConstantRange] Make getEquivalentICmp smarter"
r283058: "[SCEV] Rely on ConstantRange instead of custom logic; NFCI"
llvm-svn: 283062
(Recommit after making sure IsVerbose gets properly initialized in
DiagnosticInfoOptimizationBase. See previous commit that takes care of
this.)
OptimizationRemarkAnalysis directly takes the role of the report that is
generated by LAA.
Then we need the magic to be able to turn an LAA remark into an LV
remark. This is done via a new OptimizationRemark ctor.
llvm-svn: 282813
OptimizationRemarkAnalysis directly takes the role of the report that is
generated by LAA.
Then we need the magic to be able to turn an LAA remark into an LV
remark. This is done via a new OptimizationRemark ctor.
llvm-svn: 282758
Summary:
When using llc with -compile-twice, module is generated twice, but getAnalysis<ProfileSummaryInfoWrapperPass>().getPSI will still get the old PSI with the original (invalidated) Module. This patch checks if the module has changed when calling getPSI, if yes, update the module and invalidate the Summary.
The bug does not show up in the current llc because PSI is not used in CodeGen yet. But with https://reviews.llvm.org/D24989, the bug will be exposed by test/CodeGen/PowerPC/pr26378.ll
Reviewers: eraman, davidxl
Subscribers: llvm-commits
Differential Revision: https://reviews.llvm.org/D24993
llvm-svn: 282616
Pointers in different addrspaces can have different sizes, so it's not valid to look through addrspace cast calculating base and offset for a value.
This is similar to D13008.
Reviewed By: reames
Differential Revision: https://reviews.llvm.org/D24729
llvm-svn: 282612
Summary:
Instead of creating and destroying SCEVUnionPredicate instances (which
internally creates and destroys a DenseMap), use temporary SmallPtrSet
instances of remember the set of predicates that will get reified into a
SCEVUnionPredicate.
Reviewers: silviu.baranga, sbaranga
Subscribers: sanjoy, mcrosier, llvm-commits, mzolotukhin
Differential Revision: https://reviews.llvm.org/D25000
llvm-svn: 282606
Ever since LAA was split out into an analysis on its own, this function
stopped emitting the report directly. Instead it stores it to be
retrieved by the client which can then emit it as its own report
(e.g. -Rpass-analysis=loop-vectorize).
llvm-svn: 282561
(Re-committed after moving the template specialization under the yaml
namespace. GCC was complaining about this.)
This allows various presentation of this data using an external tool.
This was first recommended here[1].
As an example, consider this module:
1 int foo();
2 int bar();
3
4 int baz() {
5 return foo() + bar();
6 }
The inliner generates these missed-optimization remarks today (the
hotness information is pulled from PGO):
remark: /tmp/s.c:5:10: foo will not be inlined into baz (hotness: 30)
remark: /tmp/s.c:5:18: bar will not be inlined into baz (hotness: 30)
Now with -pass-remarks-output=<yaml-file>, we generate this YAML file:
--- !Missed
Pass: inline
Name: NotInlined
DebugLoc: { File: /tmp/s.c, Line: 5, Column: 10 }
Function: baz
Hotness: 30
Args:
- Callee: foo
- String: will not be inlined into
- Caller: baz
...
--- !Missed
Pass: inline
Name: NotInlined
DebugLoc: { File: /tmp/s.c, Line: 5, Column: 18 }
Function: baz
Hotness: 30
Args:
- Callee: bar
- String: will not be inlined into
- Caller: baz
...
This is a summary of the high-level decisions:
* There is a new streaming interface to emit optimization remarks.
E.g. for the inliner remark above:
ORE.emit(DiagnosticInfoOptimizationRemarkMissed(
DEBUG_TYPE, "NotInlined", &I)
<< NV("Callee", Callee) << " will not be inlined into "
<< NV("Caller", CS.getCaller()) << setIsVerbose());
NV stands for named value and allows the YAML client to process a remark
using its name (NotInlined) and the named arguments (Callee and Caller)
without parsing the text of the message.
Subsequent patches will update ORE users to use the new streaming API.
* I am using YAML I/O for writing the YAML file. YAML I/O requires you
to specify reading and writing at once but reading is highly non-trivial
for some of the more complex LLVM types. Since it's not clear that we
(ever) want to use LLVM to parse this YAML file, the code supports and
asserts that we're writing only.
On the other hand, I did experiment that the class hierarchy starting at
DiagnosticInfoOptimizationBase can be mapped back from YAML generated
here (see D24479).
* The YAML stream is stored in the LLVM context.
* In the example, we can probably further specify the IR value used,
i.e. print "Function" rather than "Value".
* As before hotness is computed in the analysis pass instead of
DiganosticInfo. This avoids the layering problem since BFI is in
Analysis while DiagnosticInfo is in IR.
[1] https://reviews.llvm.org/D19678#419445
Differential Revision: https://reviews.llvm.org/D24587
llvm-svn: 282539
I don't expect `PendingLoopPredicates` to have very many
elements (e.g. when -O3'ing the sqlite3 amalgamation,
`PendingLoopPredicates` has at most 3 elements). So now we use a
`SmallPtrSet` for it instead of the more heavyweight `DenseSet`.
llvm-svn: 282511
This allows various presentation of this data using an external tool.
This was first recommended here[1].
As an example, consider this module:
1 int foo();
2 int bar();
3
4 int baz() {
5 return foo() + bar();
6 }
The inliner generates these missed-optimization remarks today (the
hotness information is pulled from PGO):
remark: /tmp/s.c:5:10: foo will not be inlined into baz (hotness: 30)
remark: /tmp/s.c:5:18: bar will not be inlined into baz (hotness: 30)
Now with -pass-remarks-output=<yaml-file>, we generate this YAML file:
--- !Missed
Pass: inline
Name: NotInlined
DebugLoc: { File: /tmp/s.c, Line: 5, Column: 10 }
Function: baz
Hotness: 30
Args:
- Callee: foo
- String: will not be inlined into
- Caller: baz
...
--- !Missed
Pass: inline
Name: NotInlined
DebugLoc: { File: /tmp/s.c, Line: 5, Column: 18 }
Function: baz
Hotness: 30
Args:
- Callee: bar
- String: will not be inlined into
- Caller: baz
...
This is a summary of the high-level decisions:
* There is a new streaming interface to emit optimization remarks.
E.g. for the inliner remark above:
ORE.emit(DiagnosticInfoOptimizationRemarkMissed(
DEBUG_TYPE, "NotInlined", &I)
<< NV("Callee", Callee) << " will not be inlined into "
<< NV("Caller", CS.getCaller()) << setIsVerbose());
NV stands for named value and allows the YAML client to process a remark
using its name (NotInlined) and the named arguments (Callee and Caller)
without parsing the text of the message.
Subsequent patches will update ORE users to use the new streaming API.
* I am using YAML I/O for writing the YAML file. YAML I/O requires you
to specify reading and writing at once but reading is highly non-trivial
for some of the more complex LLVM types. Since it's not clear that we
(ever) want to use LLVM to parse this YAML file, the code supports and
asserts that we're writing only.
On the other hand, I did experiment that the class hierarchy starting at
DiagnosticInfoOptimizationBase can be mapped back from YAML generated
here (see D24479).
* The YAML stream is stored in the LLVM context.
* In the example, we can probably further specify the IR value used,
i.e. print "Function" rather than "Value".
* As before hotness is computed in the analysis pass instead of
DiganosticInfo. This avoids the layering problem since BFI is in
Analysis while DiagnosticInfo is in IR.
[1] https://reviews.llvm.org/D19678#419445
Differential Revision: https://reviews.llvm.org/D24587
llvm-svn: 282499
Summary:
This patch improves thinlto importer
by importing 3x larger functions that are called from hot block.
I compared performance with the trunk on spec, and there
were about 2% on povray and 3.33% on milc. These results seems
to be consistant and match the results Teresa got with her simple
heuristic. Some benchmarks got slower but I think they are just
noisy (mcf, xalancbmki, omnetpp)- running the benchmarks again with
more iterations to confirm. Geomean of all benchmarks including the noisy ones
were about +0.02%.
I see much better improvement on google branch with Easwaran patch
for pgo callsite inlining (the inliner actually inline those big functions)
Over all I see +0.5% improvement, and I get +8.65% on povray.
So I guess we will see much bigger change when Easwaran patch will land
(it depends on new pass manager), but it is still worth putting this to trunk
before it.
Implementation details changes:
- Removed CallsiteCount.
- ProfileCount got replaced by Hotness
- hot-import-multiplier is set to 3.0 for now,
didn't have time to tune it up, but I see that we get most of the interesting
functions with 3, so there is no much performance difference with higher, and
binary size doesn't grow as much as with 10.0.
Reviewers: eraman, mehdi_amini, tejohnson
Subscribers: mehdi_amini, llvm-commits
Differential Revision: https://reviews.llvm.org/D24638
llvm-svn: 282437
In a previous change I collapsed two different caches into one. When
doing that I noticed that ScalarEvolution's move constructor was not
moving those caches.
To keep the previous change simple, I've moved that bugfix into this
separate change.
llvm-svn: 282376
Both `loopHasNoSideEffects` and `loopHasNoAbnormalExits` involve walking
the loop and maintaining similar sorts of caches. This commit changes
SCEV to compute both the predicates via a single walk, and maintain a
single cache instead of two.
llvm-svn: 282375
This change simplifies a data structure optimization in the
`BackedgeTakenInfo` class for loops with exactly one computable exit.
I've sanity checked that this does not regress compile time performance,
using sqlite3's amalgamated build.
llvm-svn: 282365
There is no benefit in looking through assumptions on UndefValue to
guess known bits. Return early to avoid walking their use-lists, and
assert that all instances of ConstantData are handled here for similar
reasons (UndefValue was the only integer/pointer holdout).
llvm-svn: 282337
Check and return early for ConstantPointerNull and UndefValue
specifically in isKnownNonNullAt, and assert that ConstantData never
make it to isKnownNonNullFromDominatingCondition.
This confirms that isKnownNonNullFromDominatingCondition never walks
through the use-list of an instance of ConstantData. Given that such
use-lists cross module boundaries, it never really made sense to do so,
and was potentially very expensive.
llvm-svn: 282333
Summary: When identifying cold blocks, consider only the edge to the normal destination if the terminator is InvokeInst and let calcInvokeHeuristics() decide edge weights for the InvokeInst.
Reviewers: mcrosier, hfinkel, davidxl
Subscribers: mcrosier, llvm-commits
Differential Revision: https://reviews.llvm.org/D24868
llvm-svn: 282262
Adam Nemet