On Wed, 17 Dec 2025 12:56:01 GMT, Jatin Bhateja <[email protected]> wrote:
>> Add a new Float16lVector type and corresponding concrete vector classes, in >> addition to existing primitive vector types, maintaining operation parity >> with the FloatVector type. >> - Add necessary inline expander support. >> - Enable intrinsification for a few vector operations, namely >> ADD/SUB/MUL/DIV/MAX/MIN/FMA. >> - Use existing Float16 vector IR and backend support. >> - Extended the existing VectorAPI JTREG test suite for the newly added >> Float16Vector operations. >> >> The idea here is to first be at par with Float16 auto-vectorization support >> before intrinsifying new operations (conversions, reduction, etc). >> >> The following are the performance numbers for some of the selected >> Float16Vector benchmarking kernels compared to equivalent auto-vectorized >> Float16OperationsBenchmark kernels. >> >> <img width="1344" height="532" alt="image" >> src="https://github.com/user-attachments/assets/c8157c3c-22b0-4bc1-9de9-7a68cadb7b2a"; >> /> >> >> Initial RFP[1] was floated on the panama-dev mailing list. >> >> Kindly review the draft PR and share your feedback. >> >> Best Regards, >> Jatin >> >> [1] https://mail.openjdk.org/pipermail/panama-dev/2025-August/021100.html > > Jatin Bhateja has updated the pull request with a new target base due to a > merge or a rebase. The pull request now contains 23 commits: > > - Fix from Bhavana Kilambi for failing JTREG regressions on AARCH64 > - Merge branch 'master' of http://github.com/openjdk/jdk into JDK-8370691 > - Including test changes from Bhavana Kilambi (ARM) > - Merge branch 'master' of http://github.com/openjdk/jdk into JDK-8370691 > - Optimizing tail handling > - Merge branch 'master' of http://github.com/openjdk/jdk into JDK-8370691 > - Cleanups > - Fix failing jtreg test in CI > - Merge branch 'master' of http://github.com/openjdk/jdk into JDK-8370691 > - Cleanups > - ... and 13 more: https://git.openjdk.org/jdk/compare/5e7ae281...703f313d Hi, I have a minor question about the tests. test/jdk/jdk/incubator/vector/Float16Vector64Tests.java line 1893: > 1891: VectorMask<Float16> m = three.compare(VectorOperators.LE, > higher); > 1892: assert(m.allTrue()); > 1893: m = higher.min((short)-1).test(VectorOperators.IS_NEGATIVE); I find that `higher.min((short)-1)` produces a float16 vector of 4 NaNs. So are we testing for negative NaNs with `VectorOperators.IS_NEGATIVE`? Is it more reasonable to test `VectorOperators.IS_NAN` instead? ------------- PR Review: https://git.openjdk.org/jdk/pull/28002#pullrequestreview-3633583291 PR Review Comment: https://git.openjdk.org/jdk/pull/28002#discussion_r2667282723
