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https://issues.apache.org/jira/browse/RNG-160?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17398164#comment-17398164
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Alex Herbert commented on RNG-160:
----------------------------------
Added in commit:
b4929c899ea1f60d6bc7d61cfeeb7f589174e31a
Tested on JDK 11.0.11.
Before:
{noformat}
Benchmark (randomSourceName) (size)
(type) Mode Cnt Score Error Units
ZigguratSamplerPerformance.sequentialSample XO_RO_SHI_RO_128_PP 3
ModGaussian avgt 5 16.238 ± 0.028 ns/op
ZigguratSamplerPerformance.sequentialSample XO_RO_SHI_RO_128_PP 3
ModGaussian2 avgt 5 16.257 ± 0.053 ns/op
ZigguratSamplerPerformance.sequentialSample XO_RO_SHI_RO_128_PP 3
ModGaussianInlining avgt 5 14.160 ± 0.031 ns/op
ZigguratSamplerPerformance.sequentialSample XO_RO_SHI_RO_128_PP 128
ModGaussian avgt 5 638.158 ± 2.507 ns/op
ZigguratSamplerPerformance.sequentialSample XO_RO_SHI_RO_128_PP 128
ModGaussian2 avgt 5 636.690 ± 37.049 ns/op
ZigguratSamplerPerformance.sequentialSample XO_RO_SHI_RO_128_PP 128
ModGaussianInlining avgt 5 464.307 ± 7.701 ns/op
{noformat}
After:
{noformat}
Benchmark (randomSourceName) (size)
(type) Mode Cnt Score Error Units
ZigguratSamplerPerformance.sequentialSample XO_RO_SHI_RO_128_PP 3
ModGaussian avgt 5 14.241 ± 0.018 ns/op
ZigguratSamplerPerformance.sequentialSample XO_RO_SHI_RO_128_PP 3
ModGaussian2 avgt 5 16.630 ± 0.036 ns/op
ZigguratSamplerPerformance.sequentialSample XO_RO_SHI_RO_128_PP 3
ModGaussianInlining avgt 5 14.143 ± 0.042 ns/op
ZigguratSamplerPerformance.sequentialSample XO_RO_SHI_RO_128_PP 128
ModGaussian avgt 5 421.969 ± 3.697 ns/op
ZigguratSamplerPerformance.sequentialSample XO_RO_SHI_RO_128_PP 128
ModGaussian2 avgt 5 640.591 ± 0.342 ns/op
ZigguratSamplerPerformance.sequentialSample XO_RO_SHI_RO_128_PP 128
ModGaussianInlining avgt 5 463.447 ± 1.106 ns/op
{noformat}
> Performance of modified Ziggurat samplers
> -----------------------------------------
>
> Key: RNG-160
> URL: https://issues.apache.org/jira/browse/RNG-160
> Project: Commons RNG
> Issue Type: Improvement
> Components: sampling
> Affects Versions: 1.4
> Reporter: Alex Herbert
> Priority: Minor
> Fix For: 1.4
>
> Attachments: Exp.jpg, Gaussian.jpg
>
>
> The modified ziggurat algorithm implemented in RNG-151 has a variation for
> sampling from the overhang regions at the ziggurat edges, region A below:
> {noformat}
> \
> ----------+\
> | \
> B |A \
> -------------+\
> | \
> {noformat}
> Note: Region B is the ziggurat layer which is entirely within the
> distribution PDF.
> These overhangs can be convex, concave or an inflection (change from convex
> to concave). Samples from the region A must be below the distribution density
> curve (PDF). When sampling from region A, the sampler will create a random
> point (x,y) uniformly within the rectangle. This is tested to determine if it
> is below the curve. Convex and concave curves can use a fast method that
> knows the largest possible triangle that fits above or below the curve. If a
> sampled point (x,y) is within these triangles then the actual curve position
> (pdf( x)) for the point x does not need to be computed. This can save time if
> the pdf is computationally expensive. In the case of exponential (exp(-x)) or
> Gaussian (exp(-0.5 * x * x)) this involves a call to Math.exp.
> The current sampler implements the fast look-up method. The alternative is to
> always compute pdf( x) and determine if y is below the curve. This is known
> as 'simple overhangs'.
> Investigate the use of simple overhangs on the performance of the sampler.
> Note: The Marsaglia version of the ziggurat sampler uses the 'simple
> overhangs' method.
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