forked from OSchip/llvm-project
9 Commits
| Author | SHA1 | Message | Date |
|---|---|---|---|
Chandler Carruth
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b95def7491 |
[LCG] Spell the printing pass pipeline name for the lazy call graph
'lcg' instead of just 'cg'. This makes it consistent with the analysis name of 'lcg'. No functionality changed. llvm-svn: 263103 |
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Chandler Carruth
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e5944d97d8 |
[LCG] Construct an actual call graph with call-edge SCCs nested inside
reference-edge SCCs. This essentially builds a more normal call graph as a subgraph of the "reference graph" that was the old model. This allows both to exist and the different use cases to use the aspect which addresses their needs. Specifically, the pass manager and other *ordering* constrained logic can use the reference graph to achieve conservative order of visit, while analyses reasoning about attributes and other properties derived from reachability can reason about the direct call graph. Note that this isn't necessarily complete: it doesn't model edges to declarations or indirect calls. Those can be found by scanning the instructions of the function if desirable, and in fact every user currently does this in order to handle things like calls to instrinsics. If useful, we could consider caching this information in the call graph to save the instruction scans, but currently that doesn't seem to be important. An important realization for why the representation chosen here works is that the call graph is a formal subset of the reference graph and thus both can live within the same data structure. All SCCs of the call graph are necessarily contained within an SCC of the reference graph, etc. The design is to build 'RefSCC's to model SCCs of the reference graph, and then within them more literal SCCs for the call graph. The formation of actual call edge SCCs is not done lazily, unlike reference edge 'RefSCC's. Instead, once a reference SCC is formed, it directly builds the call SCCs within it and stores them in a post-order sequence. This is used to provide a consistent platform for mutation and update of the graph. The post-order also allows for very efficient updates in common cases by bounding the number of nodes (and thus edges) considered. There is considerable common code that I'm still looking for the best way to factor out between the various DFS implementations here. So far, my attempts have made the code harder to read and understand despite reducing the duplication, which seems a poor tradeoff. I've not given up on figuring out the right way to do this, but I wanted to wait until I at least had the system working and tested to continue attempting to factor it differently. This also requires introducing several new algorithms in order to handle all of the incremental update scenarios for the more complex structure involving two edge colorings. I've tried to comment the algorithms sufficiently to make it clear how this is expected to work, but they may still need more extensive documentation. I know that there are some changes which are not strictly necessarily coupled here. The process of developing this started out with a very focused set of changes for the new structure of the graph and algorithms, but subsequent changes to bring the APIs and code into consistent and understandable patterns also ended up touching on other aspects. There was no good way to separate these out without causing *massive* merge conflicts. Ultimately, to a large degree this is a rewrite of most of the core algorithms in the LCG class and so I don't think it really matters much. Many thanks to the careful review by Sanjoy Das! Differential Revision: http://reviews.llvm.org/D16802 llvm-svn: 261040 |
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Chandler Carruth
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a4499e9f73 |
[LCG] Build an edge abstraction for the LazyCallGraph and use it to
differentiate between indirect references to functions an direct calls. This doesn't do a whole lot yet other than change the print out produced by the analysis, but it lays the groundwork for a very major change I'm working on next: teaching the call graph to actually be a call graph, modeling *both* the indirect reference graph and the call graph simultaneously. More details on that in the next patch though. The rest of this is essentially a bunch of over-engineering that won't be interesting until the next patch. But this also isolates essentially all of the churn necessary to introduce the edge abstraction from the very important behavior change necessary in order to separately model the two graphs. So it should make review of the subsequent patch a bit easier at the cost of making this patch seem poorly motivated. ;] Differential Revision: http://reviews.llvm.org/D16038 llvm-svn: 259463 |
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David Majnemer
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7fddeccb8b |
Move the personality function from LandingPadInst to Function
The personality routine currently lives in the LandingPadInst. This isn't desirable because: - All LandingPadInsts in the same function must have the same personality routine. This means that each LandingPadInst beyond the first has an operand which produces no additional information. - There is ongoing work to introduce EH IR constructs other than LandingPadInst. Moving the personality routine off of any one particular Instruction and onto the parent function seems a lot better than have N different places a personality function can sneak onto an exceptional function. Differential Revision: http://reviews.llvm.org/D10429 llvm-svn: 239940 |
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David Blaikie
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23af64846f |
[opaque pointer type] Add textual IR support for explicit type parameter to the call instruction
See r230786 and r230794 for similar changes to gep and load
respectively.
Call is a bit different because it often doesn't have a single explicit
type - usually the type is deduced from the arguments, and just the
return type is explicit. In those cases there's no need to change the
IR.
When that's not the case, the IR usually contains the pointer type of
the first operand - but since typed pointers are going away, that
representation is insufficient so I'm just stripping the "pointerness"
of the explicit type away.
This does make the IR a bit weird - it /sort of/ reads like the type of
the first operand: "call void () %x(" but %x is actually of type "void
()*" and will eventually be just of type "ptr". But this seems not too
bad and I don't think it would benefit from repeating the type
("void (), void () * %x(" and then eventually "void (), ptr %x(") as has
been done with gep and load.
This also has a side benefit: since the explicit type is no longer a
pointer, there's no ambiguity between an explicit type and a function
that returns a function pointer. Previously this case needed an explicit
type (eg: a function returning a void() function was written as
"call void () () * @x(" rather than "call void () * @x(" because of the
ambiguity between a function returning a pointer to a void() function
and a function returning void).
No ambiguity means even function pointer return types can just be
written alone, without writing the whole function's type.
This leaves /only/ the varargs case where the explicit type is required.
Given the special type syntax in call instructions, the regex-fu used
for migration was a bit more involved in its own unique way (as every
one of these is) so here it is. Use it in conjunction with the apply.sh
script and associated find/xargs commands I've provided in rr230786 to
migrate your out of tree tests. Do let me know if any of this doesn't
cover your cases & we can iterate on a more general script/regexes to
help others with out of tree tests.
About 9 test cases couldn't be automatically migrated - half of those
were functions returning function pointers, where I just had to manually
delete the function argument types now that we didn't need an explicit
function type there. The other half were typedefs of function types used
in calls - just had to manually drop the * from those.
import fileinput
import sys
import re
pat = re.compile(r'((?:=|:|^|\s)call\s(?:[^@]*?))(\s*$|\s*(?:(?:\[\[[a-zA-Z0-9_]+\]\]|[@%](?:(")?[\\\?@a-zA-Z0-9_.]*?(?(3)"|)|{{.*}}))(?:\(|$)|undef|inttoptr|bitcast|null|asm).*$)')
addrspace_end = re.compile(r"addrspace\(\d+\)\s*\*$")
func_end = re.compile("(?:void.*|\)\s*)\*$")
def conv(match, line):
if not match or re.search(addrspace_end, match.group(1)) or not re.search(func_end, match.group(1)):
return line
return line[:match.start()] + match.group(1)[:match.group(1).rfind('*')].rstrip() + match.group(2) + line[match.end():]
for line in sys.stdin:
sys.stdout.write(conv(re.search(pat, line), line))
llvm-svn: 235145
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David Blaikie
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f72d05bc7b |
[opaque pointer type] Add textual IR support for explicit type parameter to gep operator
Similar to gep (r230786) and load (r230794) changes.
Similar migration script can be used to update test cases, which
successfully migrated all of LLVM and Polly, but about 4 test cases
needed manually changes in Clang.
(this script will read the contents of stdin and massage it into stdout
- wrap it in the 'apply.sh' script shown in previous commits + xargs to
apply it over a large set of test cases)
import fileinput
import sys
import re
rep = re.compile(r"(getelementptr(?:\s+inbounds)?\s*\()((<\d*\s+x\s+)?([^@]*?)(|\s*addrspace\(\d+\))\s*\*(?(3)>)\s*)(?=$|%|@|null|undef|blockaddress|getelementptr|addrspacecast|bitcast|inttoptr|zeroinitializer|<|\[\[[a-zA-Z]|\{\{)", re.MULTILINE | re.DOTALL)
def conv(match):
line = match.group(1)
line += match.group(4)
line += ", "
line += match.group(2)
return line
line = sys.stdin.read()
off = 0
for match in re.finditer(rep, line):
sys.stdout.write(line[off:match.start()])
sys.stdout.write(conv(match))
off = match.end()
sys.stdout.write(line[off:])
llvm-svn: 232184
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David Blaikie
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a79ac14fa6 |
[opaque pointer type] Add textual IR support for explicit type parameter to load instruction
Essentially the same as the GEP change in r230786.
A similar migration script can be used to update test cases, though a few more
test case improvements/changes were required this time around: (r229269-r229278)
import fileinput
import sys
import re
pat = re.compile(r"((?:=|:|^)\s*load (?:atomic )?(?:volatile )?(.*?))(| addrspace\(\d+\) *)\*($| *(?:%|@|null|undef|blockaddress|getelementptr|addrspacecast|bitcast|inttoptr|\[\[[a-zA-Z]|\{\{).*$)")
for line in sys.stdin:
sys.stdout.write(re.sub(pat, r"\1, \2\3*\4", line))
Reviewers: rafael, dexonsmith, grosser
Differential Revision: http://reviews.llvm.org/D7649
llvm-svn: 230794
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Chandler Carruth
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18eadd9260 |
[LCG] Add support for building persistent and connected SCCs to the
LazyCallGraph. This is the start of the whole point of this different abstraction, but it is just the initial bits. Here is a run-down of what's going on here. I'm planning to incorporate some (or all) of this into comments going forward, hopefully with better editing and wording. =] The crux of the problem with the traditional way of building SCCs is that they are ephemeral. The new pass manager however really needs the ability to associate analysis passes and results of analysis passes with SCCs in order to expose these analysis passes to the SCC passes. Making this work is kind-of the whole point of the new pass manager. =] So, when we're building SCCs for the call graph, we actually want to build persistent nodes that stick around and can be reasoned about later. We'd also like the ability to walk the SCC graph in more complex ways than just the traditional postorder traversal of the current CGSCC walk. That means that in addition to being persistent, the SCCs need to be connected into a useful graph structure. However, we still want the SCCs to be formed lazily where possible. These constraints are quite hard to satisfy with the SCC iterator. Also, using that would bypass our ability to actually add data to the nodes of the call graph to facilite implementing the Tarjan walk. So I've re-implemented things in a more direct and embedded way. This immediately makes it easy to get the persistence and connectivity correct, and it also allows leveraging the existing nodes to simplify the algorithm. I've worked somewhat to make this implementation more closely follow the traditional paper's nomenclature and strategy, although it is still a bit obtuse because it isn't recursive, using an explicit stack and a tail call instead, and it is interruptable, resuming each time we need another SCC. The other tricky bit here, and what actually took almost all the time and trials and errors I spent building this, is exactly *what* graph structure to build for the SCCs. The naive thing to build is the call graph in its newly acyclic form. I wrote about 4 versions of this which did precisely this. Inevitably, when I experimented with them across various use cases, they became incredibly awkward. It was all implementable, but it felt like a complete wrong fit. Square peg, round hole. There were two overriding aspects that pushed me in a different direction: 1) We want to discover the SCC graph in a postorder fashion. That means the root node will be the *last* node we find. Using the call-SCC DAG as the graph structure of the SCCs results in an orphaned graph until we discover a root. 2) We will eventually want to walk the SCC graph in parallel, exploring distinct sub-graphs independently, and synchronizing at merge points. This again is not helped by the call-SCC DAG structure. The structure which, quite surprisingly, ended up being completely natural to use is the *inverse* of the call-SCC DAG. We add the leaf SCCs to the graph as "roots", and have edges to the caller SCCs. Once I switched to building this structure, everything just fell into place elegantly. Aside from general cleanups (there are FIXMEs and too few comments overall) that are still needed, the other missing piece of this is support for iterating across levels of the SCC graph. These will become useful for implementing #2, but they aren't an immediate priority. Once SCCs are in good shape, I'll be working on adding mutation support for incremental updates and adding the pass manager that this analysis enables. llvm-svn: 206581 |
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Chandler Carruth
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bf71a34eb9 |
[PM] Add a new "lazy" call graph analysis pass for the new pass manager.
The primary motivation for this pass is to separate the call graph analysis used by the new pass manager's CGSCC pass management from the existing call graph analysis pass. That analysis pass is (somewhat unfortunately) over-constrained by the existing CallGraphSCCPassManager requirements. Those requirements make it *really* hard to cleanly layer the needed functionality for the new pass manager on top of the existing analysis. However, there are also a bunch of things that the pass manager would specifically benefit from doing differently from the existing call graph analysis, and this new implementation tries to address several of them: - Be lazy about scanning function definitions. The existing pass eagerly scans the entire module to build the initial graph. This new pass is significantly more lazy, and I plan to push this even further to maximize locality during CGSCC walks. - Don't use a single synthetic node to partition functions with an indirect call from functions whose address is taken. This node creates a huge choke-point which would preclude good parallelization across the fanout of the SCC graph when we got to the point of looking at such changes to LLVM. - Use a memory dense and lightweight representation of the call graph rather than value handles and tracking call instructions. This will require explicit update calls instead of some updates working transparently, but should end up being significantly more efficient. The explicit update calls ended up being needed in many cases for the existing call graph so we don't really lose anything. - Doesn't explicitly model SCCs and thus doesn't provide an "identity" for an SCC which is stable across updates. This is essential for the new pass manager to work correctly. - Only form the graph necessary for traversing all of the functions in an SCC friendly order. This is a much simpler graph structure and should be more memory dense. It does limit the ways in which it is appropriate to use this analysis. I wish I had a better name than "call graph". I've commented extensively this aspect. This is still very much a WIP, in fact it is really just the initial bits. But it is about the fourth version of the initial bits that I've implemented with each of the others running into really frustrating problms. This looks like it will actually work and I'd like to split the actual complexity across commits for the sake of my reviewers. =] The rest of the implementation along with lots of wiring will follow somewhat more rapidly now that there is a good path forward. Naturally, this doesn't impact any of the existing optimizer. This code is specific to the new pass manager. A bunch of thanks are deserved for the various folks that have helped with the design of this, especially Nick Lewycky who actually sat with me to go through the fundamentals of the final version here. llvm-svn: 200903 |