luhenry opened a new pull request #30810:
URL: https://github.com/apache/spark/pull/30810
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### What changes were proposed in this pull request?
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This patch introduces a VectorizedBLAS class which implements such
hardware-accelerated BLAS operations. This feature is hidden behind the
"vectorized" profile that you can enable by passing "-Pvectorized" to sbt or
maven.
The Vector API has been introduced in JDK 16. Following discussion on the
mailing list, this API is introduced transparently and needs to be enabled
explicitely.
### Why are the changes needed?
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Whenever a native BLAS implementation isn't available on the system, Spark
automatically falls back onto a Java implementation. With the recent release of
the Vector API in the OpenJDK [1], we can use hardware acceleration for such
operations.
This change was also discussed on the mailing list. [2]
### Does this PR introduce _any_ user-facing change?
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It introduces a build-time profile called `vectorized`. You can pass it to
sbt and mvn with `-Pvectorized`. There is no change to the end-user of Spark
and it should only impact Spark developpers. It is also disabled by default.
### How was this patch tested?
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It passes `build/sbt mllib-local/test` with and without `-Pvectorized` with
JDK 16. This patch also introduces benchmarks for BLAS.
/cc @srowen @xkrogen
[1] https://openjdk.java.net/jeps/338
[2]
https://mail-archives.apache.org/mod_mbox/spark-dev/202012.mbox/%3cdm5pr2101mb11106162bb3af32ad29c6c79b0...@dm5pr2101mb1110.namprd21.prod.outlook.com%3e
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