RFR: 8308869: C2: use profile data in subtype checks when profile has more than one class [v6]
Vladimir Ivanov
vlivanov at openjdk.org
Tue Jun 20 23:39:06 UTC 2023
On Mon, 19 Jun 2023 12:22:56 GMT, Roland Westrelin <roland at openjdk.org> wrote:
>> In this simple micro benchmark:
>>
>> https://github.com/franz1981/java-puzzles/blob/main/src/main/java/red/hat/puzzles/polymorphism/RequireNonNullCheckcastScalability.java#L70
>>
>> Performance drops sharply with polluted profile:
>>
>>
>> Benchmark (typePollution) Mode Cnt Score Error Units
>> RequireNonNullCheckcastScalability.isDuplicated1 false thrpt 10 1453.372 ± 24.919 ops/us
>>
>>
>> to:
>>
>>
>> Benchmark (typePollution) Mode Cnt Score Error Units
>> RequireNonNullCheckcastScalability.isDuplicated1 true thrpt 10 28.579 ± 2.280 ops/us
>>
>>
>> The test has 2 type checks to 2 different interfaces so caching with
>> `secondary_super_cache` doesn't help.
>>
>> The micro-benchmark only uses 2 different concrete classes
>> (`DuplicatedContext` and `NonDuplicatedContext`) and they are recorded
>> in profile data at the type checks. But c2 only take advantage of
>> profile data at type checks if they report a single class.
>>
>> What I propose is that the full blown type check expanded in
>> `Phase::gen_subtype_check()` takes advantage of profile data. So in
>> the case of the micro benchmark, before checking the
>> `secondary_super_cache`, generated code checks whether the object
>> being type checked is a `DuplicatedContext` or a
>> `NonDuplicatedContext`.
>>
>> This works fairly well on this micro benchmark:
>>
>>
>> Benchmark (typePollution) Mode Cnt Score Error Units
>> RequireNonNullCheckcastScalability.isDuplicated1 true thrpt 10 871.224 ± 20.750 ops/us
>>
>>
>> It also scales much better if there are multiple threads running the
>> same test (`secondary_super_cache` doesn't scale well: see
>> JDK-8180450).
>>
>> Now if the micro-benchmark is changed according to the comment:
>>
>> https://github.com/franz1981/java-puzzles/blob/d2d60af3d0dfe7a2567807395138edcb1d1c24f5/src/main/java/red/hat/puzzles/polymorphism/RequireNonNullCheckcastScalability.java#L62
>>
>> so the type check hits in the `secondary_super_cache`, the current
>> code performs much better:
>>
>>
>> Benchmark (typePollution) Mode Cnt Score Error Units
>> RequireNonNullCheckcastScalability.isDuplicated1 true thrpt 10 871.224 ± 20.750 ops/us
>>
>>
>> but leveraging profiling as explained above performs even better:
>>
>>
>> Benchmark ...
>
> Roland Westrelin has updated the pull request with a new target base due to a merge or a rebase. The incremental webrev excludes the unrelated changes brought in by the merge/rebase. The pull request contains eight additional commits since the last revision:
>
> - more test failures
> - Merge branch 'master' into JDK-8308869
> - whitespaces
> - test failures
> - review
> - 32 bit fix
> - white spaces
> - fix & test
Nice enhancement, Roland!
(I believe the monomorphic case you refer to is covered by `GraphKit::maybe_cast_profiled_receiver()`.)
I'm trying to understand what are the implications if you generate profile-based type guards early (during parsing). Any particular benefits from late expansion or downsides from early expansion? I'd expect that additional type info may be helpful (even though bimorphic/polymorphic cases are less useful than monomorphic one).
Handling it during parsing would relieve `SubTypeCheck` from caring about profile data and enable placing an uncommon trap on slow path for bimorphic case. (Doing that during macro expansion would require `SubTypeCheckNode` to keep JVM state.)
What are the implications if you make profiling changes separately? My understanding is you gain access to accurate probabilities and ability to distinguish between bi-/poly-/mega-morphic cases. Is it correct?
Speaking of alternative ways to pass profile info around, you could just embed `ciCallProfile` in `SubTypeCheck`. Any particular reasons not to do so?
-------------
PR Comment: https://git.openjdk.org/jdk/pull/14375#issuecomment-1599733943
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