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https://issues.apache.org/jira/browse/SPARK-35150?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sean R. Owen resolved SPARK-35150.
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Fix Version/s: 3.2.0
Resolution: Fixed
Issue resolved by pull request 32253
[https://github.com/apache/spark/pull/32253]
> Accelerate fallback BLAS with dev.ludovic.netlib
> ------------------------------------------------
>
> Key: SPARK-35150
> URL: https://issues.apache.org/jira/browse/SPARK-35150
> Project: Spark
> Issue Type: Improvement
> Components: GraphX, ML, MLlib
> Affects Versions: 3.2.0
> Reporter: Ludovic Henry
> Assignee: Ludovic Henry
> Priority: Major
> Fix For: 3.2.0
>
>
> Following https://github.com/apache/spark/pull/30810, I've continued looking
> for ways to accelerate the usage of BLAS in Spark. With this PR, I integrate
> work done in the [{{dev.ludovic.netlib}}|https://github.com/luhenry/netlib/]
> Maven package.
> The {{dev.ludovic.netlib}} library wraps the original
> {{com.github.fommil.netlib}} library and focus on accelerating the linear
> algebra routines in use in Spark. When running the
> {{org.apache.spark.ml.linalg.BLASBenchmark}}benchmarking suite, I get the
> results at [1] on an Intel machine. Moreover, this library is thoroughly
> tested to return the exact same results as the reference implementation.
> Under the hood, it reimplements the necessary algorithms in pure
> autovectorization-friendly Java 8, as well as takes advantage of the Vector
> API and Foreign Linker API introduced in JDK 16 when available.
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