b9866

cuda: enable topk-moe fusion for 288 experts (#25267)

• cuda: enable topk-moe fusion for 288 experts

The topk-moe fusion only accepted power-of-2 expert counts (or the
special-cased 576), so models with 288 experts (e.g. Step-3.7-Flash)
fell back to the unfused per-layer routing chain: softmax/sigmoid,
argsort, get_rows, sum_rows, div, clamp, scale. At batch size 1 that
is ~330 extra tiny graph nodes per token.

288 is a multiple of the warp size, so the existing kernel already
handles it; this adds the missing template instantiation and accepts
288 in the eligibility check.

Measured on gfx1151 with Step-3.7-Flash IQ4_XS (llama-bench,
-b 4096 -ub 4096 -fa 1 -dio 1 -ctk q8_0 -ctv q8_0; machine idle,
before/after paired so pp4096 stays matched as a load control):

test | before | after
----------------+----------------+----------------
pp4096 | 460.99 ± 0.45 | 462.47 ± 0.34 (unchanged)
tg128 | 19.10 ± 0.04 | 19.56 ± 0.03 (+2.4%)
tg128 @ d30000 | 12.68 ± 0.04 | 12.69 ± 0.03 (unchanged)

Prompt processing is unaffected (the fusion only touches decode
routing). The decode gain is ~+2.4% at shallow context and fades with
depth: by 30k tokens each step is attention-bound over the KV cache,
so removing the fixed routing overhead is no longer visible.

Assisted-By: Claude Fable 5 noreply@anthropic.com

• Update tests/test-backend-ops.cpp

Co-authored-by: Oliver Simons osimons@nvidia.com

• Add comment for case 288 in topk-moe.cu

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Co-authored-by: Oliver Simons osimons@nvidia.com

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