netty5/microbench/src/main
Carl Mastrangelo 83a19d5650 Optimistically update ref counts
Motivation:
Highly retained and released objects have contention on their ref
count.  Currently, the ref count is updated using compareAndSet
with care to make sure the count doesn't overflow, double free, or
revive the object.

Profiling has shown that a non trivial (~1%) of CPU time on gRPC
latency benchmarks is from the ref count updating.

Modification:
Rather than pessimistically assuming the ref count will be invalid,
optimistically update it assuming it will be.  If the update was
wrong, then use the slow path to revert the change and throw an
execption.  Most of the time, the ref counts are correct.

This changes from using compareAndSet to getAndAdd, which emits a
different CPU instruction on x86 (CMPXCHG to XADD).  Because the
CPU knows it will modifiy the memory, it can avoid contention.

On a highly contended machine, this can be about 2x faster.

There is a downside to the new approach.  The ref counters can
temporarily enter invalid states if over retained or over released.
The code does handle these overflow and underflow scenarios, but it
is possible that another concurrent access may push the failure to
a different location.  For example:

Time 1 Thread 1: obj.retain(INT_MAX - 1)
Time 2 Thread 1: obj.retain(2)
Time 2 Thread 2: obj.retain(1)

Previously Thread 2 would always succeed and Thread 1 would always
fail on the second access.  Now, thread 2 could fail while thread 1
is rolling back its change.

====

There are a few reasons why I think this is okay:

1. Buggy code is going to have bugs.  An exception _is_ going to be
   thrown.  This just causes the other threads to notice the state
   is messed up and stop early.
2. If high retention counts are a use case, then ref count should
   be a long rather than an int.
3. The critical section is greatly reduced compared to the previous
   version, so the likelihood of this happening is lower
4. On error, the code always rollsback the change atomically, so
   there is no possibility of corruption.

Result:
Faster refcounting

```
BEFORE:

Benchmark                                                                                             (delay)    Mode      Cnt         Score    Error  Units
AbstractReferenceCountedByteBufBenchmark.retainRelease_contended                                            1  sample  2901361       804.579 ±  1.835  ns/op
AbstractReferenceCountedByteBufBenchmark.retainRelease_contended                                           10  sample  3038729       785.376 ± 16.471  ns/op
AbstractReferenceCountedByteBufBenchmark.retainRelease_contended                                          100  sample  2899401       817.392 ±  6.668  ns/op
AbstractReferenceCountedByteBufBenchmark.retainRelease_contended                                         1000  sample  3650566      2077.700 ±  0.600  ns/op
AbstractReferenceCountedByteBufBenchmark.retainRelease_contended                                        10000  sample  3005467     19949.334 ±  4.243  ns/op
AbstractReferenceCountedByteBufBenchmark.retainRelease_uncontended                                          1  sample   456091        48.610 ±  1.162  ns/op
AbstractReferenceCountedByteBufBenchmark.retainRelease_uncontended                                         10  sample   732051        62.599 ±  0.815  ns/op
AbstractReferenceCountedByteBufBenchmark.retainRelease_uncontended                                        100  sample   778925       228.629 ±  1.205  ns/op
AbstractReferenceCountedByteBufBenchmark.retainRelease_uncontended                                       1000  sample   633682      2002.987 ±  2.856  ns/op
AbstractReferenceCountedByteBufBenchmark.retainRelease_uncontended                                      10000  sample   506442     19735.345 ± 12.312  ns/op

AFTER:
Benchmark                                                                                             (delay)    Mode      Cnt         Score    Error  Units
AbstractReferenceCountedByteBufBenchmark.retainRelease_contended                                            1  sample  3761980       383.436 ±  1.315  ns/op
AbstractReferenceCountedByteBufBenchmark.retainRelease_contended                                           10  sample  3667304       474.429 ±  1.101  ns/op
AbstractReferenceCountedByteBufBenchmark.retainRelease_contended                                          100  sample  3039374       479.267 ±  0.435  ns/op
AbstractReferenceCountedByteBufBenchmark.retainRelease_contended                                         1000  sample  3709210      2044.603 ±  0.989  ns/op
AbstractReferenceCountedByteBufBenchmark.retainRelease_contended                                        10000  sample  3011591     19904.227 ± 18.025  ns/op
AbstractReferenceCountedByteBufBenchmark.retainRelease_uncontended                                          1  sample   494975        52.269 ±  8.345  ns/op
AbstractReferenceCountedByteBufBenchmark.retainRelease_uncontended                                         10  sample   771094        62.290 ±  0.795  ns/op
AbstractReferenceCountedByteBufBenchmark.retainRelease_uncontended                                        100  sample   763230       235.044 ±  1.552  ns/op
AbstractReferenceCountedByteBufBenchmark.retainRelease_uncontended                                       1000  sample   634037      2006.578 ±  3.574  ns/op
AbstractReferenceCountedByteBufBenchmark.retainRelease_uncontended                                      10000  sample   506284     19742.605 ± 13.729  ns/op

```
2017-10-04 08:42:33 +02:00
..
java/io/netty Optimistically update ref counts 2017-10-04 08:42:33 +02:00
resources Add benchmarks for SSLEngine implementations 2017-02-24 08:02:10 +01:00