8343689: AArch64: Optimize MulReduction implementation

[mikabl-arm]

Add a reduce_mul intrinsic SVE specialization for >= 256-bit long vectors. It multiplies halves of the source vector using SVE instructions to get to a 128-bit long vector that fits into a SIMD&FP register. After that point, existing ASIMD implementation is used.

Benchmarks results for an AArch64 CPU with support for SVE with 256-bit vector length:

  Benchmark                 (size)   Mode      Old        New  Units
  Byte256Vector.MULLanes      1024  thrpt  502.498  10222.717 ops/ms
  Double256Vector.MULLanes    1024  thrpt  172.116   3130.997 ops/ms
  Float256Vector.MULLanes     1024  thrpt  291.612   4164.138 ops/ms
  Int256Vector.MULLanes       1024  thrpt  362.276   3717.213 ops/ms
  Long256Vector.MULLanes      1024  thrpt  184.826   2054.345 ops/ms
  Short256Vector.MULLanes     1024  thrpt  379.231   5716.223 ops/ms

Benchmarks results for an AArch64 CPU with support for SVE with 512-bit vector length:

  Benchmark                 (size)   Mode      Old       New   Units
  Byte512Vector.MULLanes      1024  thrpt  160.129  2630.600  ops/ms
  Double512Vector.MULLanes    1024  thrpt   51.229  1033.284  ops/ms
  Float512Vector.MULLanes     1024  thrpt   84.617  1658.400  ops/ms
  Int512Vector.MULLanes       1024  thrpt  109.419  1180.310  ops/ms
  Long512Vector.MULLanes      1024  thrpt   69.036   704.144  ops/ms
  Short512Vector.MULLanes     1024  thrpt  131.029  1629.632  ops/ms

---

Progress

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Issue

• JDK-8343689: AArch64: Optimize MulReduction implementation (Enhancement - P4)

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[PaulSandoz]

@mikabl-arm you can create a PR with this change against https://github.com/openjdk/jdk. Since the Vector API is incubating in the jdk/master repo we prefer to target such changes as this to that repo.

The panama-vector repo is then used for larger more speculative changes, rather than accumulating smaller changes into a larger harder to review PR to jdk/master later on.