pydata / pydata/sparse

GPU/Parallelism support

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#379 9 comments 0 reactions 0 assignees View on GitHub

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enhancement
Dominant language
Python
Stars
668
Forks
141
Avg merge
2d 8h
Merged PRs (30d)
4

Description

According to the paper: https://arxiv.org/abs/2001.00532

Contributor guide

Open the contributing guide

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 reading the linked paper, https://arxiv.org/abs/2001.00532, and reviewing the sparse project structure to determine how GPU and parallel execution would fit. The issue does not name files, tests, an entry point, or acceptance criteria, so the desired scope and definition of done need to be established before implementation.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
performance
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
15/100

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