LinearProbeHashtable <was> Re: ClassValue perf?

[Paul Sandoz]

Hi Peter,

Opportunistically if your LinearProbeHashtable works out then i am wondering if we could replace the use of CHM within MethodType.ConcurrentWeakInternSet, which only uses get/putIfAbsent/remove.

Thereby CHM can use VarHandles without inducing a circular dependency.

Paul.

> On 26 May 2016, at 10:59, Peter Levart <peter.levart at gmail.com> wrote:
> 
> Hi Michael,
> 
> On 05/23/2016 03:56 PM, Michael Haupt wrote:
>> I've ran the unpatched version and Peter's two patches once more. The results are attached (results.txt). They confirm Aleksey's observation.
>> 
>> Regarding the 03 patch (plevart3 column in the results), perfasm output (see http://cr.openjdk.java.net/~mhaupt/8031043/perfasm.zip) suggests the cost is mainly accrued in ConcurrentHashMap. The same is the case for the 02 patch (plevart2 column).
>> 
>> As things stand, I think we can even focus on Peter's 02 patch, as this is the faster of his two proposals (plevart2 column in the results), reduces the footprint, and reduces the implementation complexity. Can anything be done to improve on its performance? (It has slight performance slowdowns for the single-value case as well.)
> 
> I can't think of anything else short of improving performance of CHM itself.
> 
> Or replacing CHM with a "better" implementation:
> 
>     http://cr.openjdk.java.net/~plevart/misc/ClassValue.Alternative2/webrev.04/
> 
> This webrev is similar to webrev.02. It's only difference is in ClassValueMap which extends LinearProbeHashtable instead of ConcurrentHashMap. LinearProbeHashtable is a simple implementation of a linear-probe hash table. It's not a full Map implementation. It only implements methods needed in ClassValue. With this implementation I get a slight boost compared to JDK 9 ClassValue implementation for all sizes and counts:
> 
> Benchmark                         (classCount)  (classValueCount)  (impl)  Mode  Cnt   Score   Error  Units
> ClassValueBench.randomAccess               128                  1    jdk9  avgt   10   9.079 ± 0.092  ns/op
> ClassValueBench.randomAccess               128                  4    jdk9  avgt   10  10.615 ± 0.102  ns/op
> ClassValueBench.randomAccess               128                 16    jdk9  avgt   10  11.665 ± 0.012  ns/op
> ClassValueBench.randomAccess               128                256    jdk9  avgt   10  19.151 ± 0.219  ns/op
> ClassValueBench.randomAccess              1024                  1    jdk9  avgt   10  14.642 ± 0.425  ns/op
> ClassValueBench.randomAccess              1024                  4    jdk9  avgt   10  22.577 ± 0.093  ns/op
> ClassValueBench.randomAccess              1024                 16    jdk9  avgt   10  19.864 ± 0.736  ns/op
> ClassValueBench.randomAccess              1024                256    jdk9  avgt   10  60.470 ± 0.285  ns/op
> ClassValueBench.sequentialAccess           128                  1    jdk9  avgt   10   9.741 ± 0.033  ns/op
> ClassValueBench.sequentialAccess           128                  4    jdk9  avgt   10   8.252 ± 0.029  ns/op
> ClassValueBench.sequentialAccess           128                 16    jdk9  avgt   10   7.888 ± 1.249  ns/op
> ClassValueBench.sequentialAccess           128                256    jdk9  avgt   10  16.493 ± 0.415  ns/op
> ClassValueBench.sequentialAccess          1024                  1    jdk9  avgt   10  13.376 ± 0.452  ns/op
> ClassValueBench.sequentialAccess          1024                  4    jdk9  avgt   10  10.023 ± 0.020  ns/op
> ClassValueBench.sequentialAccess          1024                 16    jdk9  avgt   10   8.029 ± 0.178  ns/op
> ClassValueBench.sequentialAccess          1024                256    jdk9  avgt   10  33.472 ± 0.058  ns/op
> 
> Benchmark                         (classCount)  (classValueCount)  (impl)  Mode  Cnt   Score   Error  Units
> ClassValueBench.randomAccess               128                  1    pl04  avgt   10   8.955 ± 0.055  ns/op
> ClassValueBench.randomAccess               128                  4    pl04  avgt   10   9.999 ± 0.017  ns/op
> ClassValueBench.randomAccess               128                 16    pl04  avgt   10  11.615 ± 1.928  ns/op
> ClassValueBench.randomAccess               128                256    pl04  avgt   10  17.063 ± 0.460  ns/op
> ClassValueBench.randomAccess              1024                  1    pl04  avgt   10  12.553 ± 0.086  ns/op
> ClassValueBench.randomAccess              1024                  4    pl04  avgt   10  16.766 ± 0.221  ns/op
> ClassValueBench.randomAccess              1024                 16    pl04  avgt   10  18.496 ± 0.051  ns/op
> ClassValueBench.randomAccess              1024                256    pl04  avgt   10  41.390 ± 0.321  ns/op
> ClassValueBench.sequentialAccess           128                  1    pl04  avgt   10   7.854 ± 0.381  ns/op
> ClassValueBench.sequentialAccess           128                  4    pl04  avgt   10   7.498 ± 0.055  ns/op
> ClassValueBench.sequentialAccess           128                 16    pl04  avgt   10   9.218 ± 1.000  ns/op
> ClassValueBench.sequentialAccess           128                256    pl04  avgt   10  13.593 ± 0.275  ns/op
> ClassValueBench.sequentialAccess          1024                  1    pl04  avgt   10   8.774 ± 0.037  ns/op
> ClassValueBench.sequentialAccess          1024                  4    pl04  avgt   10   8.562 ± 0.014  ns/op
> ClassValueBench.sequentialAccess          1024                 16    pl04  avgt   10   7.596 ± 0.027  ns/op
> ClassValueBench.sequentialAccess          1024                256    pl04  avgt   10  24.605 ± 0.143  ns/op
> 
> 
> The footprint is even better than with CHM as LPHT does not maintain internal Map.Entry(s).
> 
> How does this implementation compare on your hardware, Michael?
> 
> Regards, Peter
> 
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