llnl / llnl/RAJAPerf

Matrix Vector Kernel Parallelism

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Jupyter Notebook
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135
Forks
55
Avg merge
4d 16h
Merged PRs (30d)
5

Description

The POLYBENCH_MVT, POLYBENCH_GESUMMV, POLYBENCH_GEMVER, and POLYBENCH_ATAX kernels (and potentially more) may be able to express more parallelism when computing dot products by using level block reductions or atomics.

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First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by locating the implementations of POLYBENCH_MVT, POLYBENCH_GESUMMV, POLYBENCH_GEMVER, and POLYBENCH_ATAX, then inspect how their dot products currently execute. Determine whether level block reductions or atomics expose more parallelism, and assess whether additional kernels have the same opportunity; done means the applicable kernels use a justified parallel approach.

Written by the indexing model from the issue text.

Assessment

Tech stack
cpp
Domain
performance
Issue type
Refactor
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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