7ec95de8e8
This should reduce memory usage when big number of Summary metrics are in use while small number of these metrics are updated
77 lines
2.8 KiB
Markdown
77 lines
2.8 KiB
Markdown
[](https://travis-ci.org/valyala/fastrand)
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[](http://godoc.org/github.com/valyala/fastrand)
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[](https://goreportcard.com/report/github.com/valyala/fastrand)
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# fastrand
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Fast pseudorandom number generator.
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# Features
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- Optimized for speed.
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- Performance scales on multiple CPUs.
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# How does it work?
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It abuses [sync.Pool](https://golang.org/pkg/sync/#Pool) for maintaining
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"per-CPU" pseudorandom number generators.
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TODO: firgure out how to use real per-CPU pseudorandom number generators.
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# Benchmark results
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```
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$ GOMAXPROCS=1 go test -bench=. github.com/valyala/fastrand
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goos: linux
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goarch: amd64
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pkg: github.com/valyala/fastrand
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BenchmarkUint32n 50000000 29.7 ns/op
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BenchmarkRNGUint32n 200000000 6.50 ns/op
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BenchmarkRNGUint32nWithLock 100000000 21.5 ns/op
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BenchmarkMathRandInt31n 50000000 31.8 ns/op
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BenchmarkMathRandRNGInt31n 100000000 17.9 ns/op
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BenchmarkMathRandRNGInt31nWithLock 50000000 30.2 ns/op
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PASS
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ok github.com/valyala/fastrand 10.634s
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```
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```
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$ GOMAXPROCS=2 go test -bench=. github.com/valyala/fastrand
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goos: linux
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goarch: amd64
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pkg: github.com/valyala/fastrand
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BenchmarkUint32n-2 100000000 17.6 ns/op
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BenchmarkRNGUint32n-2 500000000 3.36 ns/op
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BenchmarkRNGUint32nWithLock-2 50000000 32.0 ns/op
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BenchmarkMathRandInt31n-2 20000000 51.2 ns/op
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BenchmarkMathRandRNGInt31n-2 100000000 11.0 ns/op
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BenchmarkMathRandRNGInt31nWithLock-2 20000000 91.0 ns/op
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PASS
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ok github.com/valyala/fastrand 9.543s
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```
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```
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$ GOMAXPROCS=4 go test -bench=. github.com/valyala/fastrand
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goos: linux
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goarch: amd64
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pkg: github.com/valyala/fastrand
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BenchmarkUint32n-4 100000000 14.2 ns/op
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BenchmarkRNGUint32n-4 500000000 3.30 ns/op
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BenchmarkRNGUint32nWithLock-4 20000000 88.7 ns/op
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BenchmarkMathRandInt31n-4 10000000 145 ns/op
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BenchmarkMathRandRNGInt31n-4 200000000 8.35 ns/op
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BenchmarkMathRandRNGInt31nWithLock-4 20000000 102 ns/op
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PASS
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ok github.com/valyala/fastrand 11.534s
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```
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As you can see, [fastrand.Uint32n](https://godoc.org/github.com/valyala/fastrand#Uint32n)
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scales on multiple CPUs, while [rand.Int31n](https://golang.org/pkg/math/rand/#Int31n)
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doesn't scale. Their performance is comparable on `GOMAXPROCS=1`,
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but `fastrand.Uint32n` runs 3x faster than `rand.Int31n` on `GOMAXPROCS=2`
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and 10x faster than `rand.Int31n` on `GOMAXPROCS=4`.
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