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Introduction of the raft::device_resources_snmg type #2487

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@viclafargue viclafargue commented Nov 8, 2024

Introduces the raft::device_resources_snmg type to hold all resources required for the NCCL clique.

Answers #2459
Removed call to raft::comms::build_comms_nccl_only (#2465)

@viclafargue viclafargue requested a review from a team as a code owner November 8, 2024 17:16
@github-actions github-actions bot added the cpp label Nov 8, 2024
@cjnolet cjnolet added improvement Improvement / enhancement to an existing function non-breaking Non-breaking change labels Nov 8, 2024
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codecov-commenter commented Nov 8, 2024

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 81.01%. Comparing base (fccf33e) to head (14e7551).
Report is 2 commits behind head on branch-24.12.

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@@               Coverage Diff                @@
##           branch-24.12    #2487      +/-   ##
================================================
- Coverage         87.17%   81.01%   -6.17%     
================================================
  Files                25       17       -8     
  Lines               546      511      -35     
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- Hits                476      414      -62     
- Misses               70       97      +27     

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@viclafargue viclafargue changed the title NCCL clique initialization function Introduction of the raft::device_resources_snmg type Nov 15, 2024

namespace raft {

class device_resources_snmg : public resources {
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Since this is a device_resources instance, I think it'll be better to extend device_resources. That way you can override important methods like get_stream and get_worker_stream to return a main stream. In general, we should expect the device_resources_snmg to behave the same as device_resources when passed into an algorithm that only operates single gpu while being able to operate in snmg mode when passed into an algorithm that supports single-node multi-gpu. I think it should store off and use the id of the GPU that is selected when creating the snmg handle by default when being used in single-gpu mode.

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