mirror of
https://github.com/c64scene-ar/llvm-6502.git
synced 2024-08-26 07:29:55 +00:00
9ed0d629ce
7 Commits
Author | SHA1 | Message | Date | |
---|---|---|---|---|
|
c6f1b8a4ba |
[LazyCallGraph] Port test case from r240039 to LCG.
Summary: r240039 adds a test case to check that CallGraph does the right thing with respect to non-leaf intrinsics like statepoint and patchpoint. This ports the same test case to LazyCallGraph. LazyCallGraph already does the right thing with respect to escaping function pointers so there is no need to change any code. Reviewers: chandlerc Subscribers: llvm-commits Differential Revision: http://reviews.llvm.org/D10582 git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@241226 91177308-0d34-0410-b5e6-96231b3b80d8 |
||
|
cc714e2142 |
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 git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@239940 91177308-0d34-0410-b5e6-96231b3b80d8 |
||
|
32b845d223 |
[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)) git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@235145 91177308-0d34-0410-b5e6-96231b3b80d8 |
||
|
5a70dd1d82 |
[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:]) git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@232184 91177308-0d34-0410-b5e6-96231b3b80d8 |
||
|
7c9c6ed761 |
[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 git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@230794 91177308-0d34-0410-b5e6-96231b3b80d8 |
||
|
4c7edb1240 |
[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. git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@206581 91177308-0d34-0410-b5e6-96231b3b80d8 |
||
|
57732bff1e |
[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. git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@200903 91177308-0d34-0410-b5e6-96231b3b80d8 |