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Optimize random walks #3460

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jnke2016
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@jnke2016 jnke2016 commented Apr 8, 2023

Our current implementation of random walks exhibits poor performance at the python layer when converting the results to coalesced paths.

This PR

  1. Optimizes the conversion by leveraging cudf.
  2. Adds additional tests to ensure the accuracy of the conversion.
  3. Provide a better description of the API by updating the docstrings.
  4. Fixes the bug when setting legacy_result_type to False

Datasets

  • Number of vertices: 1244330
  • Number of edges: 33554432

Performance comparison before and after the optimization
image

Performance comparison between coalesced(optimized) and padded results
image

closes #3405

@jnke2016 jnke2016 requested a review from a team as a code owner April 8, 2023 17:52
@alexbarghi-nv alexbarghi-nv self-assigned this Apr 11, 2023
@alexbarghi-nv alexbarghi-nv added improvement Improvement / enhancement to an existing function non-breaking Non-breaking change labels Apr 11, 2023
@alexbarghi-nv alexbarghi-nv added this to the 23.06 milestone Apr 11, 2023
@alexbarghi-nv
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Great work on this PR, just one question @jnke2016 : are you going to apply these changes to the MG version as well?

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👍

@rlratzel
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/merge

@rapids-bot rapids-bot bot merged commit e23f587 into rapidsai:branch-23.06 Apr 18, 2023
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Successfully merging this pull request may close these issues.

[BUG]: low utilization and bad performance for GPU random walk on python API
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