[vectorIntrinsics] RFR: 8263149: Adding some algorithms optimized by Vector API into JMH benchmarks

[Wang Zhuo(Zhuoren)]

Hi,
Here are some code samples for panama-vector vectorIntrinsics JMH benchmarks.
These code were developed during our work on optimizing Alibaba applications with Vector API.
VectorDistance contains Cosine distance and Euclidean distance, scalar code from
https://github.com/opendistro-for-elasticsearch/k-NN/blob/aa5d1d40b136e2b3d33a14e80a2a374b2be015f9/src/main/java/com/amazon/opendistroforelasticsearch/knn/plugin/script/KNNScoringUtil.java#L61
In many scenarios, ElasticSearch engineers reported more than 4X E2E speedup using Vector API.
BooleanArrayCheck and ValueRangeCheckAndCastL2I were from OLAP applications.
Commit messages:
8263149: Adding some algorithms optimized by Vector API into JMH benchmarks
Co-authored-by: Joshua Zhu <jzhu at openjdk.org>

Changes: https://github.com/openjdk/panama-vector/pull/45/files
Webrev: https://openjdk.github.io/cr/?repo=panama-vector&pr=45&range=00
Issue:  https://bugs.openjdk.java.net/browse/JDK-8263149
PR: https://github.com/openjdk/panama-vector/pull/45

Regards,
Zhuoren