- Jan 30, 2017
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Haicheng Wu authored
TotalAltCost => TotalSecondaryCost Differential Revision: https://reviews.llvm.org/D29231 llvm-svn: 293490
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- Jan 24, 2017
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Chandler Carruth authored
a lazy-asserting PoisoningVH. AssertVH is fundamentally incompatible with cache-invalidation of analysis results. The invaliadtion happens after the AssertingVH has already fired. Instead, use a PoisoningVH that will assert if the dangling handle is ever used rather than merely be assigned or destroyed. This patch also removes all of the (numerous) doomed attempts to work around this fundamental incompatibility. It is a pretty significant simplification IMO. The most interesting change is in the Inliner where we still do some clearing because we don't want to rely on the coarse grained invalidation strategy of the containing pass manager. However, I prefer the approach that contains this logic to the cleanup phase of the Inliner, and I think we could enhance the CGSCC analysis management layer to make this even better in the future if desired. The rest is straight cleanup. I've also added a test for one of the harder cases to work around: when a *module analysis* contains many AssertingVHes pointing at functions. Differential Revision: https://reviews.llvm.org/D29006 llvm-svn: 292928
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- Jan 23, 2017
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Chandler Carruth authored
clearing its body. This is essential to avoid triggering asserting value handles in analyses on the function's body. I'm working on a test case for this behavior in LLVM, but Clang has a great one that managed to trigger this on all of the bots already. llvm-svn: 292770
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- Jan 22, 2017
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Chandler Carruth authored
new PM's inliner. The bug happens when we refine an SCC after having computed a proxy for the FunctionAnalysisManager, and then proceed to compute fresh analyses for functions in the *new* SCC using the manager provided by the old SCC's proxy. *And* when we manage to mutate a function in this new SCC in a way that invalidates those analyses. This can be... challenging to reproduce. I've managed to contrive a set of functions that trigger this and added a test case, but it is a bit brittle. I've directly checked that the passes run in the expected ways to help avoid the test just becoming silently irrelevant. This gets the new PM back to passing the LLVM test suite after the PGO improvements landed. llvm-svn: 292757
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Chandler Carruth authored
trace its behavior. llvm-svn: 292756
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- Jan 20, 2017
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Easwaran Raman authored
This adds the following to the new PM based inliner in PGO mode: * Use block frequency analysis to derive callsite's profile count and use that to adjust thresholds of hot and cold callsites. * Incrementally update the BFI of the caller after a callee gets inlined into it. This incremental update is only within an invocation of the run method - BFI is not preserved across calls to run. Update the function entry count of the callee after inlining it into a caller. * I've tuned the thresholds for the hot and cold callsites using a hacked up version of the old inliner that explicitly computes BFI on a set of internal benchmarks and spec. Once the new PM based pipeline stabilizes (IIRC Chandler mentioned there are known issues) I'll benchmark this again and adjust the thresholds if required. Inliner PGO support. Differential revision: https://reviews.llvm.org/D28331 llvm-svn: 292666
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- Dec 28, 2016
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Chandler Carruth authored
when they are call edges at the leaf but may (transitively) be reached via ref edges. It turns out there is a simple rule: insert everything as a ref edge which is a safe conservative default. Then we let the existing update logic handle promoting some of those to call edges. Note that it would be fairly cheap to make these call edges right away if that is desirable by testing whether there is some existing call path from the source to the target. It just seemed like slightly more complexity in this code path that isn't strictly necessary. If anyone feels strongly about handling this differently I'm happy to change it. llvm-svn: 290649
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- Dec 27, 2016
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Chandler Carruth authored
skipping indirectly recursive inline chains. To do this, we implicitly build an inline stack for each callsite and check prior to inlining that doing so would not form a cycle. This uses the exact same technique and even shares some code with the legacy PM inliner. This solution remains deeply unsatisfying to me because it means we cannot actually iterate the inliner externally. Doing so would not be able to easily detect and avoid such cycles. Some day I would very much like to have a solution that works without this internal state to detect cycles, but this is not that day. llvm-svn: 290590
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Chandler Carruth authored
Also enable the new PM in the attributes test case which caught this issue. llvm-svn: 290572
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Chandler Carruth authored
removing fully-dead comdats without removing dead entries in comdats with live members. This factors the core logic out of the current inliner's internals to a reusable utility and leverages that in both places. The factored out code should also be (minorly) more efficient in cases where we have very few dead functions or dead comdats to consider. I've added a test case to cover this behavior of the always inliner. This is the last significant bug in the new PM's always inliner I've found (so far). llvm-svn: 290557
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- Dec 22, 2016
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Easwaran Raman authored
Differential revision: https://reviews.llvm.org/D28038 llvm-svn: 290295
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- Dec 20, 2016
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Chandler Carruth authored
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
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- Dec 19, 2016
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Daniel Jasper authored
This creates non-linear behavior in the inliner (see more details in r289755's commit thread). llvm-svn: 290086
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- Dec 15, 2016
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Hal Finkel authored
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
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- Nov 20, 2016
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Simon Pilgrim authored
Identified by Pedro Giffuni in PR27636. llvm-svn: 287488
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- Nov 04, 2016
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Xinliang David Li authored
llvm-svn: 285978
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- Oct 08, 2016
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Mehdi Amini authored
The core of the change is supposed to be NFC, however it also fixes what I believe was an undefined behavior when calling: va_start(ValueArgs, Desc); with Desc being a StringRef. Differential Revision: https://reviews.llvm.org/D25342 llvm-svn: 283671
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- Sep 28, 2016
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Dehao Chen authored
Summary: This refactors the change in r282616 Reviewers: davidxl, eraman, mehdi_amini Subscribers: mehdi_amini, davide, llvm-commits Differential Revision: https://reviews.llvm.org/D25041 llvm-svn: 282630
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Adam Nemet authored
llvm-svn: 282559
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Adam Nemet authored
With the new streaming interface, these class names need to be typed a lot and it's way too looong. llvm-svn: 282544
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- Sep 27, 2016
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Adam Nemet authored
There is really no reason for these to be separate. The vectorizer started this pretty bad tradition that the text of the missed remarks is pretty meaningless, i.e. vectorization failed. There, you have to query analysis to get the full picture. I think we should just explain the reason for missing the optimization in the missed remark when possible. Analysis remarks should provide information that the pass gathers regardless whether the optimization is passing or not. llvm-svn: 282542
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Adam Nemet authored
(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
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Adam Nemet authored
This reverts commit r282499. The GCC bots are failing llvm-svn: 282503
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Adam Nemet authored
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
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- Aug 26, 2016
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Adam Nemet authored
Summary: This is obviously an interesting case because it may motivate code restructuring or LTO. Reporting this requires instantiation of ORE in the loop where the call sites are first gathered. I've checked compile-time overhead *with* -Rpass-with-hotness and the worst slow-down was 6% in mcf and quickly tailing off. As before without -Rpass-with-hotness there is no overhead. Because this could be a pretty noisy diagnostics, it is currently qualified as 'verbose'. As of this patch, 'verbose' diagnostics are only emitted with -Rpass-with-hotness, i.e. when the output is expected to be filtered. Reviewers: eraman, chandlerc, davidxl, hfinkel Subscribers: tejohnson, Prazek, davide, llvm-commits Differential Revision: https://reviews.llvm.org/D23415 llvm-svn: 279860
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- Aug 17, 2016
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Chandler Carruth authored
This is off for now while testing can take place to make sure that in fact we do sufficient stack coloring to fully obviate the manual alloca array merging. Some context on why we should be using stack coloring rather than merging allocas in this way: LLVM relies very heavily on analyzing pointers as coming from different allocas in order to make aliasing decisions. These are some of the most powerful aliasing signals available in LLVM. So merging allocas is an extremely destructive operation on the LLVM IR -- it takes away highly valuable and hard to reconstruct information. As a consequence, inlined functions which happen to have array allocas that this pattern matches will fail to be properly interleaved unless SROA manages to hoist everything to an SSA register. Instead, the inliner will have added an unnecessary dependence that one inlined function execute after the other because they will have been rewritten to refer to the same memory. All that said, folks will reasonably want some time to experiment here and make sure there are no significant regressions. A flag should give us an easy knob to test. For more context, see the thread here: http://lists.llvm.org/pipermail/llvm-dev/2016-July/103277.html http://lists.llvm.org/pipermail/llvm-dev/2016-August/103285.html Differential Revision: https://reviews.llvm.org/D23052 llvm-svn: 278892
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- Aug 10, 2016
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Piotr Padlewski authored
Summary: I think it is much better this way. When I firstly saw line: Cost += InlineConstants::LastCallToStaticBonus; I though that this is a bug, because everywhere where the cost is being reduced it is usuing -=. Reviewers: eraman, tejohnson, mehdi_amini Subscribers: llvm-commits, mehdi_amini Differential Revision: https://reviews.llvm.org/D23222 llvm-svn: 278290
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Adam Nemet authored
Summary: The inliner not being a function pass requires the work-around of generating the OptimizationRemarkEmitter and in turn BFI on demand. This will go away after the new PM is ready. BFI is only computed inside ORE if the user has requested hotness information for optimization diagnostitics (-pass-remark-with-hotness at the 'opt' level). Thus there is no additional overhead without the flag. Reviewers: hfinkel, davidxl, eraman Subscribers: llvm-commits Differential Revision: https://reviews.llvm.org/D22694 llvm-svn: 278185
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- Aug 06, 2016
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Benjamin Kramer authored
llvm-svn: 277922
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- Aug 03, 2016
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Chandler Carruth authored
here. NFC. llvm-svn: 277557
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- Jul 29, 2016
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Piotr Padlewski authored
Summary: copypasta doc of ImportedFunctionsInliningStatistics class \brief Calculate and dump ThinLTO specific inliner stats. The main statistics are: (1) Number of inlined imported functions, (2) Number of imported functions inlined into importing module (indirect), (3) Number of non imported functions inlined into importing module (indirect). The difference between first and the second is that first stat counts all performed inlines on imported functions, but the second one only the functions that have been eventually inlined to a function in the importing module (by a chain of inlines). Because llvm uses bottom-up inliner, it is possible to e.g. import function `A`, `B` and then inline `B` to `A`, and after this `A` might be too big to be inlined into some other function that calls it. It calculates this statistic by building graph, where the nodes are functions, and edges are performed inlines and then by marking the edges starting from not imported function. If `Verbose` is set to true, then it also dumps statistics per each inlined function, sorted by the greatest inlines count like - number of performed inlines - number of performed inlines to importing module Reviewers: eraman, tejohnson, mehdi_amini Subscribers: mehdi_amini, llvm-commits Differential Revision: https://reviews.llvm.org/D22491 llvm-svn: 277089
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- Jul 23, 2016
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Sean Silva authored
This unblocks the new PM part of River's patch in https://reviews.llvm.org/D22706 Conveniently, this same change was needed for D21921 and so these changes are just spun out from there. llvm-svn: 276515
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- Jun 10, 2016
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Easwaran Raman authored
Instead of directly using MaxFunctionCount and function entry count to determine callee hotness, use the isHotFunction/isColdFunction methods provided by ProfileSummaryInfo. Differential revision: http://reviews.llvm.org/D21045 llvm-svn: 272321
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- May 23, 2016
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Andrew Kaylor authored
Differential Revision: http://reviews.llvm.org/D19640 llvm-svn: 270495
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- Apr 30, 2016
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Xinliang David Li authored
Makes the new method to set data needed by debug dump. llvm-svn: 268130
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- Apr 29, 2016
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Xinliang David Li authored
llvm-svn: 268116
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Xinliang David Li authored
The implemented heuristic has a large body of code which better sits in its own function for better readability. It also allows adding more heuristics easier in the future. llvm-svn: 268107
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- Apr 23, 2016
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Andrew Kaylor authored
The original commit was reverted because of a buildbot problem with LazyCallGraph::SCC handling (not related to the OptBisect handling). Differential Revision: http://reviews.llvm.org/D19172 llvm-svn: 267231
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- Apr 22, 2016
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Vedant Kumar authored
This reverts commit r267022, due to an ASan failure: http://lab.llvm.org:8080/green/job/clang-stage2-cmake-RgSan_check/1549 llvm-svn: 267115
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- Apr 21, 2016
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Andrew Kaylor authored
This patch implements a optimization bisect feature, which will allow optimizations to be selectively disabled at compile time in order to track down test failures that are caused by incorrect optimizations. The bisection is enabled using a new command line option (-opt-bisect-limit). Individual passes that may be skipped call the OptBisect object (via an LLVMContext) to see if they should be skipped based on the bisect limit. A finer level of control (disabling individual transformations) can be managed through an addition OptBisect method, but this is not yet used. The skip checking in this implementation is based on (and replaces) the skipOptnoneFunction check. Where that check was being called, a new call has been inserted in its place which checks the bisect limit and the optnone attribute. A new function call has been added for module and SCC passes that behaves in a similar way. Differential Revision: http://reviews.llvm.org/D19172 llvm-svn: 267022
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