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SDPA support for small batch (over sequence) queries #1922

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Merged
merged 2 commits into from
Mar 4, 2025
Merged

SDPA support for small batch (over sequence) queries #1922

merged 2 commits into from
Mar 4, 2025

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awni
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@awni awni commented Mar 4, 2025 •
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Benchmarks on M4 max with the following config:

L = 16384
Lq = 4
H = 32
H_k = H // 4
D = 128
V = 128

Timing sdpa ... 4.70581 msec
Timing attention ... 16.99894 msec

Also updated RoPE to route to a faster path for shapes like [1, H, L, D].

The intention here is mostly to speed up spec dec. Will share some benchmarks here: ml-explore/mlx-examples#1319

@awni awni force-pushed the batch_query_sdpa branch from bbb1e77 to 6aeb67b Compare March 4, 2025 16:06
@awni awni requested review from angeloskath and barronalex March 4, 2025 16:15
@awni awni mentioned this pull request Mar 4, 2025
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angeloskath
angeloskath approved these changes Mar 4, 2025
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Awesome!

The choice for query_transposed vs passing strides and so on was for performance reasons?

@awni
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awni commented Mar 4, 2025

The choice for query_transposed vs passing strides and so on was for performance reasons?

Good question.. I didn't try passing the query strides in so I couldn't say if there is much perf difference, probably minor.. the diff seemed simpler with the function constant. On the other hand it could be more general to allow arbitrary strides in the sequence and head dimension.

@awni awni merged commit e613d0e into main Mar 4, 2025
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@awni awni deleted the batch_query_sdpa branch March 4, 2025 18:59
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@angeloskath angeloskath angeloskath approved these changes

@barronalex barronalex Awaiting requested review from barronalex

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@awni @angeloskath