RFR: 8373026: C2 SuperWord and Vector API: vector algorithms test and benchmark [v14]

[Emanuel Peter]

> This is an exploratory work. I wanted to use auto vectorization and the Vector API to implement some SIMD algorithms. We don't have too many IR tests and benchmarks, so I'm proposing an initial set of them, to be extended in the future.
> 
> Note: for now they are all `int` based. And some of them may not use the Vector API optimally, so feel free to propose ideas and integrate them in a follow-up RFE ;)
> 
> **Discussion**
> 
> Observations:
> - If the loop can be auto vectorized, that is the fastest. If we cannot vectorize, we at least get reasonable scalar performance.
> - If the Vector API code can be fully intrinsified, we get fast code. But somtimes, the Vector API is horribly slow, much slower than scalar loop performance.
>   - `linux_aarch64_server`: `filterI`, `scanAddI`, `reduceAddIFieldsX4` are very slow
>   - `macosx_aarch64`: `filterI`, `scanAddI`, `reduceAddIFieldsX4`, `findMinIndex` are very slow
>   - `linux_x64_oci_server`: Vector API leads to really nice speedups
>   - `windows_x64_oci_server`: the only one that gets good/better performance on all benchmarks
>   - `macosx_x64_sandybridge`: `scanAddI`!, `reduceAddIFieldsX4` are very slow. Other benchmarks benefit.
> - Compact Object Headers has some negative effect on some loop benchmarks.
>   - `linux_aarch64_server`: `reduceAddI`, `copyI`
>   - `macosx_aarch64`: `mapI`, `reduceAddI`, `copyI`
>   - `linux_x64_oci_server`: `reduceAddI`, `copyI`, `findI`?
>   - `windows_x64_oci_server`: `reduceAddI` and some others a little bit
>   - `macosx_x64_sandybridge`: `fillI`, `iotaI`, `mapI`, `reduceAddI`, `copyI`
> - Intrinsics can be much faster than auto vectoirzed or Vector API code.
>   - `linux_aarch64_server`: `copyI`
>   - `macosx_x64_sandybridge`: actually, `Arrays.fill` seems to suffer with Compact Object Headers as well.
> - `rearrange` often needs to do the `mask load` and `and` operation inside the loop. That has a slight performance impact, I filed [JDK-8373240](https://bugs.openjdk.org/browse/JDK-8373240).
> 
> **Benchmark Plots**
> 
> Units: nanoseconds per algorithm invocation.
> 
> Note: the `aarch64` machines all only have `NEON` support. Performance may be much better on `SVE`, I have not benchmarked that yet.
> 
> `linux_x64_oci`
> <img width="4500" height="6000" alt="algo_linux_x64_oci_server" src="https://github.com/user-attachments/assets/f2c5bbcb-e009-4c54-a1bf-91af45326cb9" />
> 
> `windows_x64_oci`
> <img width="4500" height="6000" alt="algo_windows_x64_oci_server" src="https://github.com/user-attachments/assets/8946d248-4d75-4b16-8f17-627...

Emanuel Peter has updated the pull request with a new target base due to a merge or a rebase. The incremental webrev excludes the unrelated changes brought in by the merge/rebase. The pull request contains 47 additional commits since the last revision:

 - Merge branch 'master' into JDK-8373026-vector-algorithms
 - some bug-fixes and lowerCaseB test/benchmark
 - updates for review
 - use firstTrue for XiaohongGong
 - Data refactor part 4
 - Data refactor part 3
 - Data refactor part 2
 - Data refactor part 1
 - fix flag handling for Vladimir
 - more hashCodeB
 - ... and 37 more: https://git.openjdk.org/jdk/compare/39b69a2e...3abe02a0

-------------

Changes:
  - all: https://git.openjdk.org/jdk/pull/28639/files
  - new: https://git.openjdk.org/jdk/pull/28639/files/5d96f781..3abe02a0

Webrevs:
 - full: https://webrevs.openjdk.org/?repo=jdk&pr=28639&range=13
 - incr: https://webrevs.openjdk.org/?repo=jdk&pr=28639&range=12-13

  Stats: 18882 lines in 607 files changed: 11405 ins; 2824 del; 4653 mod
  Patch: https://git.openjdk.org/jdk/pull/28639.diff
  Fetch: git fetch https://git.openjdk.org/jdk.git pull/28639/head:pull/28639

PR: https://git.openjdk.org/jdk/pull/28639