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CAGRA support arbitrary dim (number of features) #1458

Closed
Tracked by #1392
tfeher opened this issue Apr 24, 2023 · 0 comments · Fixed by #1505
Closed
Tracked by #1392

CAGRA support arbitrary dim (number of features) #1458

tfeher opened this issue Apr 24, 2023 · 0 comments · Fixed by #1505

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@tfeher
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tfeher commented Apr 24, 2023

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@tfeher tfeher mentioned this issue Apr 24, 2023
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@tfeher tfeher changed the title support arbitrary dim (number of features) CAGRA support arbitrary dim (number of features) Apr 24, 2023
@rapids-bot rapids-bot bot closed this as completed in #1505 Jun 9, 2023
rapids-bot bot pushed a commit that referenced this issue Jun 9, 2023
This PR adds padding to the dataset (if necessary) to make reading any of its rows compatible with 128bit vectorized loads. This change also enables handling arbitrary number of input features (before this PR each row had to be at least 64bit aligned, which constrained the acceptable number of input features).

Fixes #1458.

With this change, it is sufficient to keep a single "load type" specialization for the search kernels, which shall cut the binary size by half (#1459).

Authors:
  - Tamas Bela Feher (https://github.com/tfeher)

Approvers:
  - tsuki (https://github.com/enp1s0)
  - Corey J. Nolet (https://github.com/cjnolet)

URL: #1505
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