I did this a long time ago with a janky python script, but now
clang-format has built-in support for this. I fed clang-format every
line with a #include and let it re-sort things according to the precise
LLVM rules for include ordering baked into clang-format these days.
I've reverted a number of files where the results of sorting includes
isn't healthy. Either places where we have legacy code relying on
particular include ordering (where possible, I'll fix these separately)
or where we have particular formatting around #include lines that
I didn't want to disturb in this patch.
This patch is *entirely* mechanical. If you get merge conflicts or
anything, just ignore the changes in this patch and run clang-format
over your #include lines in the files.
Sorry for any noise here, but it is important to keep these things
stable. I was seeing an increasing number of patches with irrelevant
re-ordering of #include lines because clang-format was used. This patch
at least isolates that churn, makes it easy to skip when resolving
conflicts, and gets us to a clean baseline (again).
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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
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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.
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Below are my super rough notes when porting. They can probably serve as
a basic guide for porting other passes to the new PM. As I port more
passes I'll expand and generalize this and make a proper
docs/HowToPortToNewPassManager.rst document. There is also missing
documentation for general concepts and API's in the new PM which will
require some documentation.
Once there is proper documentation in place we can put up a list of
passes that have to be ported and game-ify/crowdsource the rest of the
porting (at least of the middle end; the backend is still unclear).
I will however be taking personal responsibility for ensuring that the
LLD/ELF LTO pipeline is ported in a timely fashion. The remaining passes
to be ported are (do something like
`git grep "<the string in the bullet point below>"` to find the pass):
General Scalar:
[ ] Simplify the CFG
[ ] Jump Threading
[ ] MemCpy Optimization
[ ] Promote Memory to Register
[ ] MergedLoadStoreMotion
[ ] Lazy Value Information Analysis
General IPO:
[ ] Dead Argument Elimination
[ ] Deduce function attributes in RPO
Loop stuff / vectorization stuff:
[ ] Alignment from assumptions
[ ] Canonicalize natural loops
[ ] Delete dead loops
[ ] Loop Access Analysis
[ ] Loop Invariant Code Motion
[ ] Loop Vectorization
[ ] SLP Vectorizer
[ ] Unroll loops
Devirtualization / CFI:
[ ] Cross-DSO CFI
[ ] Whole program devirtualization
[ ] Lower bitset metadata
CGSCC passes:
[ ] Function Integration/Inlining
[ ] Remove unused exception handling info
[ ] Promote 'by reference' arguments to scalars
Please let me know if you are interested in working on any of the passes
in the above list (e.g. reply to the post-commit thread for this patch).
I'll probably be tackling "General Scalar" and "General IPO" first FWIW.
Steps as I port "Deduce function attributes in RPO"
---------------------------------------------------
(note: if you are doing any work based on these notes, please leave a
note in the post-commit review thread for this commit with any
improvements / suggestions / incompleteness you ran into!)
Note: "Deduce function attributes in RPO" is a module pass.
1. Do preparatory refactoring.
Do preparatory factoring. In this case all I had to do was to pull out a static helper (r272503).
(TODO: give more advice here e.g. if pass holds state or something)
2. Rename the old pass class.
llvm/lib/Transforms/IPO/FunctionAttrs.cpp
Rename class ReversePostOrderFunctionAttrs -> ReversePostOrderFunctionAttrsLegacyPass
in preparation for adding a class ReversePostOrderFunctionAttrs as the pass in the new PM.
(edit: actually wait what? The new class name will be
ReversePostOrderFunctionAttrsPass, so it doesn't conflict. So this step is
sort of useless churn).
llvm/include/llvm/InitializePasses.h
llvm/lib/LTO/LTOCodeGenerator.cpp
llvm/lib/Transforms/IPO/IPO.cpp
llvm/lib/Transforms/IPO/FunctionAttrs.cpp
Rename initializeReversePostOrderFunctionAttrsPass -> initializeReversePostOrderFunctionAttrsLegacyPassPass
(note that the "PassPass" thing falls out of `s/ReversePostOrderFunctionAttrs/ReversePostOrderFunctionAttrsLegacyPass/`)
Note that the INITIALIZE_PASS macro is what creates this identifier name, so renaming the class requires this renaming too.
Note that createReversePostOrderFunctionAttrsPass does not need to be
renamed since its name is not generated from the class name.
3. Add the new PM pass class.
In the new PM all passes need to have their
declaration in a header somewhere, so you will often need to add a header.
In this case
llvm/include/llvm/Transforms/IPO/FunctionAttrs.h is already there because
PostOrderFunctionAttrsPass was already ported.
The file-level comment from the .cpp file can be used as the file-level
comment for the new header. You may want to tweak the wording slightly
from "this file implements" to "this file provides" or similar.
Add declaration for the new PM pass in this header:
class ReversePostOrderFunctionAttrsPass
: public PassInfoMixin<ReversePostOrderFunctionAttrsPass> {
public:
PreservedAnalyses run(Module &M, AnalysisManager<Module> &AM);
};
Its name should end with `Pass` for consistency (note that this doesn't
collide with the names of most old PM passes). E.g. call it
`<name of the old PM pass>Pass`.
Also, move the doxygen comment from the old PM pass to the declaration of
this class in the header.
Also, include the declaration for the new PM class
`llvm/Transforms/IPO/FunctionAttrs.h` at the top of the file (in this case,
it was already done when the other pass in this file was ported).
Now define the `run` method for the new class.
The main things here are:
a) Use AM.getResult<...>(M) to get results instead of `getAnalysis<...>()`
b) If the old PM pass would have returned "false" (i.e. `Changed ==
false`), then you should return PreservedAnalyses::all();
c) In the old PM getAnalysisUsage method, observe the calls
`AU.addPreserved<...>();`.
In the case `Changed == true`, for each preserved analysis you should do
call `PA.preserve<...>()` on a PreservedAnalyses object and return it.
E.g.:
PreservedAnalyses PA;
PA.preserve<CallGraphAnalysis>();
return PA;
Note that calls to skipModule/skipFunction are not supported in the new PM
currently, so optnone and optimization bisect support do not work. You can
just drop those calls for now.
4. Add the pass to the new PM pass registry to make it available in opt.
In llvm/lib/Passes/PassBuilder.cpp add a #include for your header.
`#include "llvm/Transforms/IPO/FunctionAttrs.h"`
In this case there is already an include (from when
PostOrderFunctionAttrsPass was ported).
Add your pass to llvm/lib/Passes/PassRegistry.def
In this case, I added
`MODULE_PASS("rpo-functionattrs", ReversePostOrderFunctionAttrsPass())`
The string is from the `INITIALIZE_PASS*` macros used in the old pass
manager.
Then choose a test that uses the pass and use the new PM `-passes=...` to
run it.
E.g. in this case there is a test that does:
; RUN: opt < %s -basicaa -functionattrs -rpo-functionattrs -S | FileCheck %s
I have added the line:
; RUN: opt < %s -aa-pipeline=basic-aa -passes='require<targetlibinfo>,cgscc(function-attrs),rpo-functionattrs' -S | FileCheck %s
The `-aa-pipeline=basic-aa` and
`require<targetlibinfo>,cgscc(function-attrs)` are what is needed to run
functionattrs in the new PM (note that in the new PM "functionattrs"
becomes "function-attrs" for some reason). This is just pulled from
`readattrs.ll` which contains the change from when functionattrs was ported
to the new PM.
Adding rpo-functionattrs causes the pass that was just ported to run.
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This was originally a pointer to support pass managers which didn't use
AnalysisManagers. However, that doesn't realistically come up much and
the complexity of supporting it doesn't really make sense.
In fact, *many* parts of the pass manager were just assuming the pointer
was never null already. This at least makes it much more explicit and
clear.
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clarify their purpose.
Firstly, call them "...Mixin" types so it is clear that there is no
type hierarchy being formed here. Secondly, use the term 'Info' to
clarify that they aren't adding any interesting *semantics* to the
passes or analyses, just exposing APIs used by the management layer to
get information about the pass or analysis.
Thanks to Manuel for helping pin down the naming confusion here and come
up with effective names to address it.
In case you already have some out-of-tree stuff, the following should be
roughly what you want to update:
perl -pi -e 's/\b(Pass|Analysis)Base\b/\1InfoMixin/g'
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analyses in the new pass manager.
These just handle really basic stuff: turning a type name into a string
statically that is nice to print in logs, and getting a static unique ID
for each analysis.
Sadly, the format of passes in anonymous namespaces makes using their
names in tests really annoying so I've customized the names of the no-op
passes to keep tests sane to read.
This is the first of a few simplifying refactorings for the new pass
manager that should reduce boilerplate and confusion.
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convert one test to use this.
This is a particularly significant milestone because it required
a working per-function AA framework which can be queried over each
function from within a CGSCC transform pass (and additionally a module
analysis to be accessible). This is essentially *the* point of the
entire pass manager rewrite. A CGSCC transform is able to query for
multiple different function's analysis results. It works. The whole
thing appears to actually work and accomplish the original goal. While
we were able to hack function attrs and basic-aa to "work" in the old
pass manager, this port doesn't use any of that, it directly leverages
the new fundamental functionality.
For this to work, the CGSCC framework also has to support SCC-based
behavior analysis, etc. The only part of the CGSCC pass infrastructure
not sorted out at this point are the updates in the face of inlining and
running function passes that mutate the call graph.
The changes are pretty boring and boiler-plate. Most of the work was
factored into more focused preperatory patches. But this is what wires
it all together.
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