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https://issues.apache.org/jira/browse/HADOOP-19666?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=18039307#comment-18039307
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ASF GitHub Bot commented on HADOOP-19666:
-----------------------------------------
leiwen2025 commented on PR #7912:
URL: https://github.com/apache/hadoop/pull/7912#issuecomment-3551600528
> @leiwen2025 can you take up reviewing @PeterPtroc's work and see if you
two can come up with the best design between you for performance. A joint
submission is more likely to work from testing alone.
Hi @steveloughran, I have commented on @PeterPtroc 's PR to express my
willingness to collaborate with him on refining the design for optimal
performance.
If someone could ping him there to make sure he sees it, that would be
great. Thanks!
> Add hardware-accelerated CRC32 support for riscv64 using the v,zbc,zvbc
> extension
> ---------------------------------------------------------------------------------
>
> Key: HADOOP-19666
> URL: https://issues.apache.org/jira/browse/HADOOP-19666
> Project: Hadoop Common
> Issue Type: Sub-task
> Components: native
> Affects Versions: 3.4.1
> Reporter: Lei Wen
> Priority: Major
> Labels: pull-request-available
>
> This PR implements vector-accelerated CRC32 using the RISC-V V, Zbc and Zvbc
> instruction sets, with full functional verification and performance testing
> completed.
> The implementation uses the vclmul.v and vclmulh.v (carry-less multiply)
> instructions for data folding and computes the final checksum via Barrett
> reduction.
> Key Features:
> 1. Runtime Hardware Detection
> The PR uses kernel hardware probing and cpuinfo parsing to dynamically detect
> hardware support for CRC32 acceleration (via v, zbc, and zvbc extensions) at
> runtime.
> 2. Performance Improvement
> Hardware-accelerated CRC32 achieves a performance boost of over *3x* compared
> to the software implementation.
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