Analysis, it has Analysis passes, and once NewGVN is made an Analysis,
this removes the cross dependency from Analysis to Transform/Utils.
NFC.
llvm-svn: 299980
This patch optimizes two memory intrinsic operations: memset and memcpy based
on the profiled size of the operation. The high level transformation is like:
mem_op(..., size)
==>
switch (size) {
case s1:
mem_op(..., s1);
goto merge_bb;
case s2:
mem_op(..., s2);
goto merge_bb;
...
default:
mem_op(..., size);
goto merge_bb;
}
merge_bb:
Differential Revision: http://reviews.llvm.org/D28966
llvm-svn: 299446
Summary: SamplePGO uses branch_weight annotation to represent callsite hotness. When ICP promotes an indirect call to direct call, we need to make sure the direct call is annotated with branch_weight in SamplePGO mode, so that downstream function inliner can use hot callsite heuristic.
Reviewers: davidxl, eraman, xur
Reviewed By: davidxl, xur
Subscribers: mehdi_amini, llvm-commits
Differential Revision: https://reviews.llvm.org/D30282
llvm-svn: 296028
default pipeline.
A clang with this patch built with ASan and asserts can build all of the
test-suite as well, so it seems to not uncover any latent problems.
Differential Revision: https://reviews.llvm.org/D29853
llvm-svn: 294888
All the invalidation issues and bugs in this seem to be fixed, it has
survived a full build of the test suite plus SPEC with asserts and ASan
enabled on the Clang binary used.
Differential Revision: https://reviews.llvm.org/D29815
llvm-svn: 294887
This needs explicit requires of the optimization remark emission before
loop pass pipelines containing LICM as we no longer get it from the
inliner -- Argument Promotion may invalidate it. Technically the inliner
could also have broken this, but it never came up in testing.
Differential Revision: https://reviews.llvm.org/D29595
llvm-svn: 294670
Now that the call graph supports efficient replacement of a function and
spurious reference edges, we can port ArgumentPromotion to the new pass
manager very easily.
The old PM-specific bits are sunk into callbacks that the new PM simply
doesn't use. Unlike the old PM, the new PM simply does argument
promotion and afterward does the update to LCG reflecting the promoted
function.
Differential Revision: https://reviews.llvm.org/D29580
llvm-svn: 294667
I intend to use the same type with the same semantics in the WholeProgramDevirt
pass.
Differential Revision: https://reviews.llvm.org/D29746
llvm-svn: 294629
Summary:
This patch adds a utility to build extended SSA (see "ABCD: eliminating
array bounds checks on demand"), and an intrinsic to support it. This
is then used to get functionality equivalent to propagateEquality in
GVN, in NewGVN (without having to replace instructions as we go). It
would work similarly in SCCP or other passes. This has been talked
about a few times, so i built a real implementation and tried to
productionize it.
Copies are inserted for operands used in assumes and conditional
branches that are based on comparisons (see below for more)
Every use affected by the predicate is renamed to the appropriate
intrinsic result.
E.g.
%cmp = icmp eq i32 %x, 50
br i1 %cmp, label %true, label %false
true:
ret i32 %x
false:
ret i32 1
will become
%cmp = icmp eq i32, %x, 50
br i1 %cmp, label %true, label %false
true:
; Has predicate info
; branch predicate info { TrueEdge: 1 Comparison: %cmp = icmp eq i32 %x, 50 }
%x.0 = call @llvm.ssa_copy.i32(i32 %x)
ret i32 %x.0
false:
ret i23 1
(you can use -print-predicateinfo to get an annotated-with-predicateinfo dump)
This enables us to easily determine what operations are affected by a
given predicate, and how operations affected by a chain of
predicates.
Reviewers: davide, sanjoy
Subscribers: mgorny, llvm-commits, Prazek
Differential Revision: https://reviews.llvm.org/D29519
Update for review comments
Fix a bug Nuno noticed where we are giving information about and/or on edges where the info is not useful and easy to use wrong
Update for review comments
llvm-svn: 294351
the main pipeline.
This is a very straight forward port. Nothing weird or surprising.
This brings the number of missing passes from the new PM's pipeline down
to three.
llvm-svn: 293249
With this the per-module pass pipeline is *extremely* close to the
legacy PM. The missing pieces are:
- PruneEH (or some equivalent)
- ArgumentPromotion
- LoopLoadElimination
- LoopUnswitch
I'm going to work through those in essentially that order but this seems
like a worthwhile incremental step toward the end state.
One difference in what I have here from the legacy PM is that I've
consolidated some of the per-function passes at the very end of the
pipeline into the main optimization function pipeline. The intervening
passes are *really* uninteresting and so this seems very likely to have
any effect other than minor improvement to locality.
Note that there are still some failures in the test suite, but the
compiler doesn't crash or assert.
Differential Revision: https://reviews.llvm.org/D29114
llvm-svn: 293241
loop-unswitch in the main pipelines for the new PM.
All of these now work, and Clang built using this pipeline can build the
test suite and SPEC without hitting any asserts of ASan failures.
There are still some bugs hiding though -- 7 tests regress with the new
PM. I'm going to be investigating these, but it seems worthwhile to at
least get the pipelines in place so that others can play with them, and
they aren't completely broken.
Differential Revision: https://reviews.llvm.org/D29113
llvm-svn: 293225
factory functions for the two modes the loop unroller is actually used
in in-tree: simplified full-unrolling and the entire thing including
partial unrolling.
I've also wired these up to nice names so you can express both of these
being in a pipeline easily. This is a precursor to actually enabling
these parts of the O2 pipeline.
Differential Revision: https://reviews.llvm.org/D28897
llvm-svn: 293136
This patch introduces guard based loop predication optimization. The new LoopPredication pass tries to convert loop variant range checks to loop invariant by widening checks across loop iterations. For example, it will convert
for (i = 0; i < n; i++) {
guard(i < len);
...
}
to
for (i = 0; i < n; i++) {
guard(n - 1 < len);
...
}
After this transformation the condition of the guard is loop invariant, so loop-unswitch can later unswitch the loop by this condition which basically predicates the loop by the widened condition:
if (n - 1 < len)
for (i = 0; i < n; i++) {
...
}
else
deoptimize
This patch relies on an NFC change to make ScalarEvolution::isMonotonicPredicate public (revision 293062).
Reviewed By: sanjoy
Differential Revision: https://reviews.llvm.org/D29034
llvm-svn: 293064
Like several other loop passes (the vectorizer, etc) this pass doesn't
really fit the model of a loop pass. The critical distinction is that it
isn't intended to be pipelined together with other loop passes. I plan
to add some documentation to the loop pass manager to make this more
clear on that side.
LoopSink is also different because it doesn't really need a lot of the
infrastructure of our loop passes. For example, if there aren't loop
invariant instructions causing a preheader to exist, there is no need to
form a preheader. It also doesn't need LCSSA because this pass is
only involved in sinking invariant instructions from a preheader into
the loop, not reasoning about live-outs.
This allows some nice simplifications to the pass in the new PM where we
can directly walk the loops once without restructuring them.
Differential Revision: https://reviews.llvm.org/D28921
llvm-svn: 292589
LV no longer "requires" LCSSA and LoopSimplify, and instead forms
them internally as required. So, there's nothing preventing it from
being enabled.
llvm-svn: 292464
the latter to the Transforms library.
While the loop PM uses an analysis to form the IR units, the current
plan is to have the PM itself establish and enforce both loop simplified
form and LCSSA. This would be a layering violation in the analysis
library.
Fundamentally, the idea behind the loop PM is to *transform* loops in
addition to running passes over them, so it really seemed like the most
natural place to sink this was into the transforms library.
We can't just move *everything* because we also have loop analyses that
rely on a subset of the invariants. So this patch splits the the loop
infrastructure into the analysis management that has to be part of the
analysis library, and the transform-aware pass manager.
This also required splitting the loop analyses' printer passes out to
the transforms library, which makes sense to me as running these will
transform the code into LCSSA in theory.
I haven't split the unittest though because testing one component
without the other seems nearly intractable.
Differential Revision: https://reviews.llvm.org/D28452
llvm-svn: 291662
arguments much like the CGSCC pass manager.
This is a major redesign following the pattern establish for the CGSCC layer to
support updates to the set of loops during the traversal of the loop nest and
to support invalidation of analyses.
An additional significant burden in the loop PM is that so many passes require
access to a large number of function analyses. Manually ensuring these are
cached, available, and preserved has been a long-standing burden in LLVM even
with the help of the automatic scheduling in the old pass manager. And it made
the new pass manager extremely unweildy. With this design, we can package the
common analyses up while in a function pass and make them immediately available
to all the loop passes. While in some cases this is unnecessary, I think the
simplicity afforded is worth it.
This does not (yet) address loop simplified form or LCSSA form, but those are
the next things on my radar and I have a clear plan for them.
While the patch is very large, most of it is either mechanically updating loop
passes to the new API or the new testing for the loop PM. The code for it is
reasonably compact.
I have not yet updated all of the loop passes to correctly leverage the update
mechanisms demonstrated in the unittests. I'll do that in follow-up patches
along with improved FileCheck tests for those passes that ensure things work in
more realistic scenarios. In many cases, there isn't much we can do with these
until the loop simplified form and LCSSA form are in place.
Differential Revision: https://reviews.llvm.org/D28292
llvm-svn: 291651
This is an orthogonal and separated layer instead of being embedded
inside the pass manager. While it adds a small amount of complexity, it
is fairly minimal and the composability and control seems worth the
cost.
The logic for this ends up being nicely isolated and targeted. It should
be easy to experiment with different iteration strategies wrapped around
the CGSCC bottom-up walk using this kind of facility.
The mechanism used to track devirtualization is the simplest one I came
up with. I think it handles most of the cases the existing iteration
machinery handles, but I haven't done a *very* in depth analysis. It
does however match the basic intended semantics, and we can tweak or
tune its exact behavior incrementally as necessary. One thing that we
may want to revisit is freshly building the value handle set on each
iteration. While I don't think this will be a significant cost (it is
strictly fewer value handles but more churn of value handes than the old
call graph), it is conceivable that we'll want a somewhat more clever
tracking mechanism. My hope is to layer that on as a follow up patch
with data supporting any implementation complexity it adds.
This code also provides for a basic count heuristic: if the number of
indirect calls decreases and the number of direct calls increases for
a given function in the SCC, we assume devirtualization is responsible.
This matches the heuristics currently used in the legacy pass manager.
Differential Revision: https://reviews.llvm.org/D23114
llvm-svn: 290665
currenty relies on the old PM's dependency system forming LCSSA.
The new PM will require a different design for this, and for now this is
causing most of the issues I'm currently seeing in testing. I'd like to
get to a testable baseline and then work on re-enabling things one at
a time.
llvm-svn: 290644
not really wired into the loop pass manager in a way that will let us
productively use these passes yet.
This lets the new PM get farther in basic testing which is useful for
establishing a good baseline of "doesn't explode". There are still
plenty of crashers in basic testing though, this just gets rid of some
noise that is well understood and not representing a specific or narrow
bug.
llvm-svn: 290601
Pretty boring and lame as-is but necessary. This is definitely a place
we'll end up with extension hooks longer term. =]
Differential Revision: https://reviews.llvm.org/D28076
llvm-svn: 290449
from the old pass manager in the new one.
I'm not trying to support (initially) the numerous options that are
currently available to customize the pass pipeline. If we end up really
wanting them, we can add them later, but I suspect many are no longer
interesting. The simplicity of omitting them will help a lot as we sort
out what the pipeline should look like in the new PM.
I've also documented to the best of my ability *why* each pass or group
of passes is used so that reading the pipeline is more helpful. In many
cases I think we have some questionable choices of ordering and I've
left FIXME comments in place so we know what to come back and revisit
going forward. But for now, I've left it as similar to the current
pipeline as I could.
Lastly, I've had to comment out several places where passes are not
ported to the new pass manager or where the loop pass infrastructure is
not yet ready. I did at least fix a few bugs in the loop pass
infrastructure uncovered by running the full pipeline, but I didn't want
to go too far in this patch -- I'll come back and re-enable these as the
infrastructure comes online. But I'd like to keep the comments in place
because I don't want to lose track of which passes need to be enabled
and where they go.
One thing that seemed like a significant API improvement was to require
that we don't build pipelines for O0. It seems to have no real benefit.
I've also switched back to returning pass managers by value as at this
API layer it feels much more natural to me for composition. But if
others disagree, I'm happy to go back to an output parameter.
I'm not 100% happy with the testing strategy currently, but it seems at
least OK. I may come back and try to refactor or otherwise improve this
in subsequent patches but I wanted to at least get a good starting point
in place.
Differential Revision: https://reviews.llvm.org/D28042
llvm-svn: 290325
This doesn't implement *every* feature of the existing inliner, but
tries to implement the most important ones for building a functional
optimization pipeline and beginning to sort out bugs, regressions, and
other problems.
Notable, but intentional omissions:
- No alloca merging support. Why? Because it isn't clear we want to do
this at all. Active discussion and investigation is going on to remove
it, so for simplicity I omitted it.
- No support for trying to iterate on "internally" devirtualized calls.
Why? Because it adds what I suspect is inappropriate coupling for
little or no benefit. We will have an outer iteration system that
tracks devirtualization including that from function passes and
iterates already. We should improve that rather than approximate it
here.
- Optimization remarks. Why? Purely to make the patch smaller, no other
reason at all.
The last one I'll probably work on almost immediately. But I wanted to
skip it in the initial patch to try to focus the change as much as
possible as there is already a lot of code moving around and both of
these *could* be skipped without really disrupting the core logic.
A summary of the different things happening here:
1) Adding the usual new PM class and rigging.
2) Fixing minor underlying assumptions in the inline cost analysis or
inline logic that don't generally hold in the new PM world.
3) Adding the core pass logic which is in essence a loop over the calls
in the nodes in the call graph. This is a bit duplicated from the old
inliner, but only a handful of lines could realistically be shared.
(I tried at first, and it really didn't help anything.) All told,
this is only about 100 lines of code, and most of that is the
mechanics of wiring up analyses from the new PM world.
4) Updating the LazyCallGraph (in the new PM) based on the *newly
inlined* calls and references. This is very minimal because we cannot
form cycles.
5) When inlining removes the last use of a function, eagerly nuking the
body of the function so that any "one use remaining" inline cost
heuristics are immediately refined, and queuing these functions to be
completely deleted once inlining is complete and the call graph
updated to reflect that they have become dead.
6) After all the inlining for a particular function, updating the
LazyCallGraph and the CGSCC pass manager to reflect the
function-local simplifications that are done immediately and
internally by the inline utilties. These are the exact same
fundamental set of CG updates done by arbitrary function passes.
7) Adding a bunch of test cases to specifically target CGSCC and other
subtle aspects in the new PM world.
Many thanks to the careful review from Easwaran and Sanjoy and others!
Differential Revision: https://reviews.llvm.org/D24226
llvm-svn: 290161
After r289755, the AssumptionCache is no longer needed. Variables affected by
assumptions are now found by using the new operand-bundle-based scheme. This
new scheme is more computationally efficient, and also we need much less
code...
llvm-svn: 289756
Summary:
This never really got implemented, and was very hard to test before
a lot of the refactoring changes to make things more robust. But now we
can test it thoroughly and cleanly, especially at the CGSCC level.
The core idea is that when an inner analysis manager proxy receives the
invalidation event for the outer IR unit, it needs to walk the inner IR
units and propagate it to the inner analysis manager for each of those
units. For example, each function in the SCC needs to get an
invalidation event when the SCC gets one.
The function / module interaction is somewhat boring here. This really
becomes interesting in the face of analysis-backed IR units. This patch
effectively handles all of the CGSCC layer's needs -- both invalidating
SCC analysis and invalidating function analysis when an SCC gets
invalidated.
However, this second aspect doesn't really handle the
LoopAnalysisManager well at this point. That one will need some change
of design in order to fully integrate, because unlike the call graph,
the entire function behind a LoopAnalysis's results can vanish out from
under us, and we won't even have a cached API to access. I'd like to try
to separate solving the loop problems into a subsequent patch though in
order to keep this more focused so I've adapted them to the API and
updated the tests that immediately fail, but I've not added the level of
testing and validation at that layer that I have at the CGSCC layer.
An important aspect of this change is that the proxy for the
FunctionAnalysisManager at the SCC pass layer doesn't work like the
other proxies for an inner IR unit as it doesn't directly manage the
FunctionAnalysisManager and invalidation or clearing of it. This would
create an ever worsening problem of dual ownership of this
responsibility, split between the module-level FAM proxy and this
SCC-level FAM proxy. Instead, this patch changes the SCC-level FAM proxy
to work in terms of the module-level proxy and defer to it to handle
much of the updates. It only does SCC-specific invalidation. This will
become more important in subsequent patches that support more complex
invalidaiton scenarios.
Reviewers: jlebar
Subscribers: mehdi_amini, mcrosier, mzolotukhin, llvm-commits
Differential Revision: https://reviews.llvm.org/D27197
llvm-svn: 289317
analyses to have a common type which is enforced rather than using
a char object and a `void *` type when used as an identifier.
This has a number of advantages. First, it at least helps some of the
confusion raised in Justin Lebar's code review of why `void *` was being
used everywhere by having a stronger type that connects to documentation
about this.
However, perhaps more importantly, it addresses a serious issue where
the alignment of these pointer-like identifiers was unknown. This made
it hard to use them in pointer-like data structures. We were already
dodging this in dangerous ways to create the "all analyses" entry. In
a subsequent patch I attempted to use these with TinyPtrVector and
things fell apart in a very bad way.
And it isn't just a compile time or type system issue. Worse than that,
the actual alignment of these pointer-like opaque identifiers wasn't
guaranteed to be a useful alignment as they were just characters.
This change introduces a type to use as the "key" object whose address
forms the opaque identifier. This both forces the objects to have proper
alignment, and provides type checking that we get it right everywhere.
It also makes the types somewhat less mysterious than `void *`.
We could go one step further and introduce a truly opaque pointer-like
type to return from the `ID()` static function rather than returning
`AnalysisKey *`, but that didn't seem to be a clear win so this is just
the initial change to get to a reliably typed and aligned object serving
is a key for all the analyses.
Thanks to Richard Smith and Justin Lebar for helping pick plausible
names and avoid making this refactoring many times. =] And thanks to
Sean for the super fast review!
While here, I've tried to move away from the "PassID" nomenclature
entirely as it wasn't really helping and is overloaded with old pass
manager constructs. Now we have IDs for analyses, and key objects whose
address can be used as IDs. Where possible and clear I've shortened this
to just "ID". In a few places I kept "AnalysisID" to make it clear what
was being identified.
Differential Revision: https://reviews.llvm.org/D27031
llvm-svn: 287783
This patch updates a bunch of places where add_dependencies was being explicitly called to add dependencies on intrinsics_gen to instead use the DEPENDS named parameter. This cleanup is needed for a patch I'm working on to add a dependency debugging mode to the build system.
llvm-svn: 287206
Summary:
This pass shrink-wraps a condition to some library calls where the call
result is not used. For example:
sqrt(val);
is transformed to
if (val < 0)
sqrt(val);
Even if the result of library call is not being used, the compiler cannot
safely delete the call because the function can set errno on error
conditions.
Note in many functions, the error condition solely depends on the incoming
parameter. In this optimization, we can generate the condition can lead to
the errno to shrink-wrap the call. Since the chances of hitting the error
condition is low, the runtime call is effectively eliminated.
These partially dead calls are usually results of C++ abstraction penalty
exposed by inlining. This optimization hits 108 times in 19 C/C++ programs
in SPEC2006.
Reviewers: hfinkel, mehdi_amini, davidxl
Subscribers: modocache, mgorny, mehdi_amini, xur, llvm-commits, beanz
Differential Revision: https://reviews.llvm.org/D24414
llvm-svn: 284542
Summary:
Use MemorySSA, if requested, to do less conservative memory dependency
checking.
This change doesn't enable the MemorySSA enhanced EarlyCSE in the
default pipelines, so should be NFC.
Reviewers: dberlin, sanjoy, reames, majnemer
Subscribers: mcrosier, llvm-commits
Differential Revision: http://reviews.llvm.org/D19821
llvm-svn: 280279
manager, including both plumbing and logic to handle function pass
updates.
There are three fundamentally tied changes here:
1) Plumbing *some* mechanism for updating the CGSCC pass manager as the
CG changes while passes are running.
2) Changing the CGSCC pass manager infrastructure to have support for
the underlying graph to mutate mid-pass run.
3) Actually updating the CG after function passes run.
I can separate them if necessary, but I think its really useful to have
them together as the needs of #3 drove #2, and that in turn drove #1.
The plumbing technique is to extend the "run" method signature with
extra arguments. We provide the call graph that intrinsically is
available as it is the basis of the pass manager's IR units, and an
output parameter that records the results of updating the call graph
during an SCC passes's run. Note that "...UpdateResult" isn't a *great*
name here... suggestions very welcome.
I tried a pretty frustrating number of different data structures and such
for the innards of the update result. Every other one failed for one
reason or another. Sometimes I just couldn't keep the layers of
complexity right in my head. The thing that really worked was to just
directly provide access to the underlying structures used to walk the
call graph so that their updates could be informed by the *particular*
nature of the change to the graph.
The technique for how to make the pass management infrastructure cope
with mutating graphs was also something that took a really, really large
number of iterations to get to a place where I was happy. Here are some
of the considerations that drove the design:
- We operate at three levels within the infrastructure: RefSCC, SCC, and
Node. In each case, we are working bottom up and so we want to
continue to iterate on the "lowest" node as the graph changes. Look at
how we iterate over nodes in an SCC running function passes as those
function passes mutate the CG. We continue to iterate on the "lowest"
SCC, which is the one that continues to contain the function just
processed.
- The call graph structure re-uses SCCs (and RefSCCs) during mutation
events for the *highest* entry in the resulting new subgraph, not the
lowest. This means that it is necessary to continually update the
current SCC or RefSCC as it shifts. This is really surprising and
subtle, and took a long time for me to work out. I actually tried
changing the call graph to provide the opposite behavior, and it
breaks *EVERYTHING*. The graph update algorithms are really deeply
tied to this particualr pattern.
- When SCCs or RefSCCs are split apart and refined and we continually
re-pin our processing to the bottom one in the subgraph, we need to
enqueue the newly formed SCCs and RefSCCs for subsequent processing.
Queuing them presents a few challenges:
1) SCCs and RefSCCs use wildly different iteration strategies at
a high level. We end up needing to converge them on worklist
approaches that can be extended in order to be able to handle the
mutations.
2) The order of the enqueuing need to remain bottom-up post-order so
that we don't get surprising order of visitation for things like
the inliner.
3) We need the worklists to have set semantics so we don't duplicate
things endlessly. We don't need a *persistent* set though because
we always keep processing the bottom node!!!! This is super, super
surprising to me and took a long time to convince myself this is
correct, but I'm pretty sure it is... Once we sink down to the
bottom node, we can't re-split out the same node in any way, and
the postorder of the current queue is fixed and unchanging.
4) We need to make sure that the "current" SCC or RefSCC actually gets
enqueued here such that we re-visit it because we continue
processing a *new*, *bottom* SCC/RefSCC.
- We also need the ability to *skip* SCCs and RefSCCs that get merged
into a larger component. We even need the ability to skip *nodes* from
an SCC that are no longer part of that SCC.
This led to the design you see in the patch which uses SetVector-based
worklists. The RefSCC worklist is always empty until an update occurs
and is just used to handle those RefSCCs created by updates as the
others don't even exist yet and are formed on-demand during the
bottom-up walk. The SCC worklist is pre-populated from the RefSCC, and
we push new SCCs onto it and blacklist existing SCCs on it to get the
desired processing.
We then *directly* update these when updating the call graph as I was
never able to find a satisfactory abstraction around the update
strategy.
Finally, we need to compute the updates for function passes. This is
mostly used as an initial customer of all the update mechanisms to drive
their design to at least cover some real set of use cases. There are
a bunch of interesting things that came out of doing this:
- It is really nice to do this a function at a time because that
function is likely hot in the cache. This means we want even the
function pass adaptor to support online updates to the call graph!
- To update the call graph after arbitrary function pass mutations is
quite hard. We have to build a fairly comprehensive set of
data structures and then process them. Fortunately, some of this code
is related to the code for building the cal graph in the first place.
Unfortunately, very little of it makes any sense to share because the
nature of what we're doing is so very different. I've factored out the
one part that made sense at least.
- We need to transfer these updates into the various structures for the
CGSCC pass manager. Once those were more sanely worked out, this
became relatively easier. But some of those needs necessitated changes
to the LazyCallGraph interface to make it significantly easier to
extract the changed SCCs from an update operation.
- We also need to update the CGSCC analysis manager as the shape of the
graph changes. When an SCC is merged away we need to clear analyses
associated with it from the analysis manager which we didn't have
support for in the analysis manager infrsatructure. New SCCs are easy!
But then we have the case that the original SCC has its shape changed
but remains in the call graph. There we need to *invalidate* the
analyses associated with it.
- We also need to invalidate analyses after we *finish* processing an
SCC. But the analyses we need to invalidate here are *only those for
the newly updated SCC*!!! Because we only continue processing the
bottom SCC, if we split SCCs apart the original one gets invalidated
once when its shape changes and is not processed farther so its
analyses will be correct. It is the bottom SCC which continues being
processed and needs to have the "normal" invalidation done based on
the preserved analyses set.
All of this is mostly background and context for the changes here.
Many thanks to all the reviewers who helped here. Especially Sanjoy who
caught several interesting bugs in the graph algorithms, David, Sean,
and others who all helped with feedback.
Differential Revision: http://reviews.llvm.org/D21464
llvm-svn: 279618
was done to hopefully appease MSVC.
As an upside, this also implements the suggestion Sanjoy made in code
review, so two for one! =]
I'll be watching the bots to see if there are still issues.
llvm-svn: 279295
solve completely opaque MSVC build errors. It complains about lots of
stuff with this change without givin nearly enough information to even
try to fix.
llvm-svn: 279231
to run methods, both for transform passes and analysis passes.
This also allows the analysis manager to use a different set of extra
arguments from the pass manager where useful. Consider passes over
analysis produced units of IR like SCCs of the call graph or loops.
Passes of this nature will often want to refer to the analysis result
that was used to compute their IR units (the call graph or LoopInfo).
And for transformations, they may want to communicate special update
information to the outer pass manager. With this change, it becomes
possible to have a run method for a loop pass that looks more like:
PreservedAnalyses run(Loop &L, AnalysisManager<Loop, LoopInfo> &AM,
LoopInfo &LI, LoopUpdateRecord &UR);
And to query the analysis manager like:
AM.getResult<MyLoopAnalysis>(L, LI);
This makes accessing the known-available analyses convenient and clear,
and it makes passing customized data structures around easy.
My initial use case is going to be in updating the pass manager layers
when the analysis units of IR change. But there are more use cases here
such as having a layer that lets inner passes signal whether certain
additional passes should be run because of particular simplifications
made. Two desires for this have come up in the past: triggering
additional optimization after successfully unrolling loops, and
triggering additional inlining after collapsing indirect calls to direct
calls.
Despite adding this layer of generic extensibility, the *only* change to
existing, simple usage are for places where we forward declare the
AnalysisManager template. We really shouldn't be doing this because of
the fragility exposed here, but currently it makes coping with the
legacy PM code easier.
Differential Revision: http://reviews.llvm.org/D21462
llvm-svn: 279227
minimal and boring form than the old pass manager's version.
This pass does the very minimal amount of work necessary to inline
functions declared as always-inline. It doesn't support a wide array of
things that the legacy pass manager did support, but is alse ... about
20 lines of code. So it has that going for it. Notably things this
doesn't support:
- Array alloca merging
- To support the above, bottom-up inlining with careful history
tracking and call graph updates
- DCE of the functions that become dead after this inlining.
- Inlining through call instructions with the always_inline attribute.
Instead, it focuses on inlining functions with that attribute.
The first I've omitted because I'm hoping to just turn it off for the
primary pass manager. If that doesn't pan out, I can add it here but it
will be reasonably expensive to do so.
The second should really be handled by running global-dce after the
inliner. I don't want to re-implement the non-trivial logic necessary to
do comdat-correct DCE of functions. This means the -O0 pipeline will
have to be at least 'always-inline,global-dce', but that seems
reasonable to me. If others are seriously worried about this I'd like to
hear about it and understand why. Again, this is all solveable by
factoring that logic into a utility and calling it here, but I'd like to
wait to do that until there is a clear reason why the existing
pass-based factoring won't work.
The final point is a serious one. I can fairly easily add support for
this, but it seems both costly and a confusing construct for the use
case of the always inliner running at -O0. This attribute can of course
still impact the normal inliner easily (although I find that
a questionable re-use of the same attribute). I've started a discussion
to sort out what semantics we want here and based on that can figure out
if it makes sense ta have this complexity at O0 or not.
One other advantage of this design is that it should be quite a bit
faster due to checking for whether the function is a viable candidate
for inlining exactly once per function instead of doing it for each call
site.
Anyways, hopefully a reasonable starting point for this pass.
Differential Revision: https://reviews.llvm.org/D23299
llvm-svn: 278896
Summary:
Refactor the existing support into a LoopDataPrefetch implementation
class and a LoopDataPrefetchLegacyPass class that invokes it.
Add a new LoopDataPrefetchPass for the new pass manager that utilizes
the LoopDataPrefetch implementation class.
Reviewers: mehdi_amini
Subscribers: sanjoy, mzolotukhin, nemanjai, llvm-commits
Differential Revision: https://reviews.llvm.org/D23483
llvm-svn: 278591
Summary:
Port the NameAnonFunction pass and add a test.
Depends on D23439.
Reviewers: mehdi_amini
Subscribers: llvm-commits, mehdi_amini
Differential Revision: https://reviews.llvm.org/D23440
llvm-svn: 278509
Summary:
Port the ModuleSummaryAnalysisWrapperPass to the new pass manager.
Use it in the ported BitcodeWriterPass (similar to how we use the
legacy ModuleSummaryAnalysisWrapperPass in the legacy WriteBitcodePass).
Also, pass the -module-summary opt flag through to the new pass
manager pipeline and through to the bitcode writer pass, and add
a test that uses it.
Reviewers: mehdi_amini
Subscribers: llvm-commits, mehdi_amini
Differential Revision: https://reviews.llvm.org/D23439
llvm-svn: 278508
Besides a general consistently benefit, the extra layer of indirection
allows the mechanical part of https://reviews.llvm.org/D23256 that
requires touching every transformation and analysis to be factored out
cleanly.
Thanks to David for the suggestion.
llvm-svn: 278080
Daniel Berlin