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Austin Clements authored
Currently, each M has a cache of the most recently used *workbuf. This is used primarily by the write barrier so it doesn't have to access the global workbuf lists on every write barrier. It's also used by stack scanning because it's convenient. This cache is important for write barrier performance, but this particular approach has several downsides. It's faster than no cache, but far from optimal (as the benchmarks below show). It's complex: access to the cache is sprinkled through most of the workbuf list operations and it requires special care to transform into and back out of the gcWork cache that's actually used for scanning and marking. It requires atomic exchanges to take ownership of the cached workbuf and to return it to the M's cache even though it's almost always used by only the current M. Since it's per-M, flushing these caches is O(# of Ms), which may be high. And it has some significant subtleties: for example, in general the cache shouldn't be used after the harvestwbufs() in mark termination because it could hide work from mark termination, but stack scanning can happen after this and *will* use the cache (but it turns out this is okay because it will always be followed by a getfull(), which drains the cache). This change replaces this cache with a per-P gcWork object. This gcWork cache can be used directly by scanning and marking (as long as preemption is disabled, which is a general requirement of gcWork). Since it's per-P, it doesn't require synchronization, which simplifies things and means the only atomic operations in the write barrier are occasionally fetching new work buffers and setting a mark bit if the object isn't already marked. This cache can be flushed in O(# of Ps), which is generally small. It follows a simple flushing rule: the cache can be used during any phase, but during mark termination it must be flushed before allowing preemption. This also makes the dispose during mutator assist no longer necessary, which eliminates the vast majority of gcWork dispose calls and reduces contention on the global workbuf lists. And it's a lot faster on some benchmarks: benchmark old ns/op new ns/op delta BenchmarkBinaryTree17 11963668673 11206112763 -6.33% BenchmarkFannkuch11 2643217136 2649182499 +0.23% BenchmarkFmtFprintfEmpty 70.4 70.2 -0.28% BenchmarkFmtFprintfString 364 307 -15.66% BenchmarkFmtFprintfInt 317 282 -11.04% BenchmarkFmtFprintfIntInt 512 483 -5.66% BenchmarkFmtFprintfPrefixedInt 404 380 -5.94% BenchmarkFmtFprintfFloat 521 479 -8.06% BenchmarkFmtManyArgs 2164 1894 -12.48% BenchmarkGobDecode 30366146 22429593 -26.14% BenchmarkGobEncode 29867472 26663152 -10.73% BenchmarkGzip 391236616 396779490 +1.42% BenchmarkGunzip 96639491 96297024 -0.35% BenchmarkHTTPClientServer 100110 70763 -29.31% BenchmarkJSONEncode 51866051 52511382 +1.24% BenchmarkJSONDecode 103813138 86094963 -17.07% BenchmarkMandelbrot200 4121834 4120886 -0.02% BenchmarkGoParse 16472789 5879949 -64.31% BenchmarkRegexpMatchEasy0_32 140 140 +0.00% BenchmarkRegexpMatchEasy0_1K 394 394 +0.00% BenchmarkRegexpMatchEasy1_32 120 120 +0.00% BenchmarkRegexpMatchEasy1_1K 621 614 -1.13% BenchmarkRegexpMatchMedium_32 209 202 -3.35% BenchmarkRegexpMatchMedium_1K 54889 55175 +0.52% BenchmarkRegexpMatchHard_32 2682 2675 -0.26% BenchmarkRegexpMatchHard_1K 79383 79524 +0.18% BenchmarkRevcomp 584116718 584595320 +0.08% BenchmarkTemplate 125400565 109620196 -12.58% BenchmarkTimeParse 386 387 +0.26% BenchmarkTimeFormat 580 447 -22.93% (Best out of 10 runs. The delta of averages is similar.) This also puts us in a good position to flush these caches when nearing the end of concurrent marking, which will let us increase the size of the work buffers while still controlling mark termination pause time. Change-Id: I2dd94c8517a19297a98ec280203cccaa58792522 Reviewed-on: https://go-review.googlesource.com/9178 Run-TryBot: Austin Clements <austin@google.com> TryBot-Result: Gobot Gobot <gobot@golang.org> Reviewed-by: Russ Cox <rsc@golang.org>
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