7.0 KiB
xsync benchmarks
If you're interested in MapOf comparison with some of the popular concurrent hash maps written in Go, check this and this PRs.
The below results were obtained for xsync v2.3.1 on a c6g.metal EC2 instance (64 CPU, 128GB RAM) running Linux and Go 1.19.3. I'd like to thank @felixge who kindly ran the benchmarks.
The following commands were used to run the benchmarks:
$ go test -run='^$' -cpu=1,2,4,8,16,32,64 -bench . -count=30 -timeout=0 | tee bench.txt
$ benchstat bench.txt | tee benchstat.txt
The below sections contain some of the results. Refer to this gist for the complete output.
Please note that MapOf got a number of optimizations since v2.3.1, so the current result is likely to be different.
Counter vs. atomic int64
name time/op
Counter 27.3ns ± 1%
Counter-2 27.2ns ±11%
Counter-4 15.3ns ± 8%
Counter-8 7.43ns ± 7%
Counter-16 3.70ns ±10%
Counter-32 1.77ns ± 3%
Counter-64 0.96ns ±10%
AtomicInt64 7.60ns ± 0%
AtomicInt64-2 12.6ns ±13%
AtomicInt64-4 13.5ns ±14%
AtomicInt64-8 12.7ns ± 9%
AtomicInt64-16 12.8ns ± 8%
AtomicInt64-32 13.0ns ± 6%
AtomicInt64-64 12.9ns ± 7%
Here time/op stands for average time spent on operation. If you divide 10^9 by the result in nanoseconds per operation, you'd get the throughput in operations per second. Thus, the ideal theoretical scalability of a concurrent data structure implies that the reported time/op decreases proportionally with the increased number of CPU cores. On the contrary, if the measured time per operation increases when run on more cores, it means performance degradation.
MapOf vs. sync.Map
1,000 [int, int] entries with a warm-up, 100% Loads:
IntegerMapOf_WarmUp/reads=100% 24.0ns ± 0%
IntegerMapOf_WarmUp/reads=100%-2 12.0ns ± 0%
IntegerMapOf_WarmUp/reads=100%-4 6.02ns ± 0%
IntegerMapOf_WarmUp/reads=100%-8 3.01ns ± 0%
IntegerMapOf_WarmUp/reads=100%-16 1.50ns ± 0%
IntegerMapOf_WarmUp/reads=100%-32 0.75ns ± 0%
IntegerMapOf_WarmUp/reads=100%-64 0.38ns ± 0%
IntegerMapStandard_WarmUp/reads=100% 55.3ns ± 0%
IntegerMapStandard_WarmUp/reads=100%-2 27.6ns ± 0%
IntegerMapStandard_WarmUp/reads=100%-4 16.1ns ± 3%
IntegerMapStandard_WarmUp/reads=100%-8 8.35ns ± 7%
IntegerMapStandard_WarmUp/reads=100%-16 4.24ns ± 7%
IntegerMapStandard_WarmUp/reads=100%-32 2.18ns ± 6%
IntegerMapStandard_WarmUp/reads=100%-64 1.11ns ± 3%
1,000 [int, int] entries with a warm-up, 99% Loads, 0.5% Stores, 0.5% Deletes:
IntegerMapOf_WarmUp/reads=99% 31.0ns ± 0%
IntegerMapOf_WarmUp/reads=99%-2 16.4ns ± 1%
IntegerMapOf_WarmUp/reads=99%-4 8.42ns ± 0%
IntegerMapOf_WarmUp/reads=99%-8 4.41ns ± 0%
IntegerMapOf_WarmUp/reads=99%-16 2.38ns ± 2%
IntegerMapOf_WarmUp/reads=99%-32 1.37ns ± 4%
IntegerMapOf_WarmUp/reads=99%-64 0.85ns ± 2%
IntegerMapStandard_WarmUp/reads=99% 121ns ± 1%
IntegerMapStandard_WarmUp/reads=99%-2 109ns ± 3%
IntegerMapStandard_WarmUp/reads=99%-4 115ns ± 4%
IntegerMapStandard_WarmUp/reads=99%-8 114ns ± 2%
IntegerMapStandard_WarmUp/reads=99%-16 105ns ± 2%
IntegerMapStandard_WarmUp/reads=99%-32 97.0ns ± 3%
IntegerMapStandard_WarmUp/reads=99%-64 98.0ns ± 2%
1,000 [int, int] entries with a warm-up, 75% Loads, 12.5% Stores, 12.5% Deletes:
IntegerMapOf_WarmUp/reads=75%-reads 46.2ns ± 1%
IntegerMapOf_WarmUp/reads=75%-reads-2 36.7ns ± 2%
IntegerMapOf_WarmUp/reads=75%-reads-4 22.0ns ± 1%
IntegerMapOf_WarmUp/reads=75%-reads-8 12.8ns ± 2%
IntegerMapOf_WarmUp/reads=75%-reads-16 7.69ns ± 1%
IntegerMapOf_WarmUp/reads=75%-reads-32 5.16ns ± 1%
IntegerMapOf_WarmUp/reads=75%-reads-64 4.91ns ± 1%
IntegerMapStandard_WarmUp/reads=75%-reads 156ns ± 0%
IntegerMapStandard_WarmUp/reads=75%-reads-2 177ns ± 1%
IntegerMapStandard_WarmUp/reads=75%-reads-4 197ns ± 1%
IntegerMapStandard_WarmUp/reads=75%-reads-8 221ns ± 2%
IntegerMapStandard_WarmUp/reads=75%-reads-16 242ns ± 1%
IntegerMapStandard_WarmUp/reads=75%-reads-32 258ns ± 1%
IntegerMapStandard_WarmUp/reads=75%-reads-64 264ns ± 1%
MPMCQueue vs. Go channels
Concurrent producers and consumers (1:1), queue/channel size 1,000, some work done by both producers and consumers:
QueueProdConsWork100 252ns ± 0%
QueueProdConsWork100-2 206ns ± 5%
QueueProdConsWork100-4 136ns ±12%
QueueProdConsWork100-8 110ns ± 6%
QueueProdConsWork100-16 108ns ± 2%
QueueProdConsWork100-32 102ns ± 2%
QueueProdConsWork100-64 101ns ± 0%
ChanProdConsWork100 283ns ± 0%
ChanProdConsWork100-2 406ns ±21%
ChanProdConsWork100-4 549ns ± 7%
ChanProdConsWork100-8 754ns ± 7%
ChanProdConsWork100-16 828ns ± 7%
ChanProdConsWork100-32 810ns ± 8%
ChanProdConsWork100-64 832ns ± 4%
RBMutex vs. sync.RWMutex
The writer locks on each 100,000 iteration with some work in the critical section for both readers and the writer:
RBMutexWorkWrite100000 146ns ± 0%
RBMutexWorkWrite100000-2 73.3ns ± 0%
RBMutexWorkWrite100000-4 36.7ns ± 0%
RBMutexWorkWrite100000-8 18.6ns ± 0%
RBMutexWorkWrite100000-16 9.83ns ± 3%
RBMutexWorkWrite100000-32 5.53ns ± 0%
RBMutexWorkWrite100000-64 4.04ns ± 3%
RWMutexWorkWrite100000 121ns ± 0%
RWMutexWorkWrite100000-2 128ns ± 1%
RWMutexWorkWrite100000-4 124ns ± 2%
RWMutexWorkWrite100000-8 101ns ± 1%
RWMutexWorkWrite100000-16 92.9ns ± 1%
RWMutexWorkWrite100000-32 89.9ns ± 1%
RWMutexWorkWrite100000-64 88.4ns ± 1%