Kernels:

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marcsun13

/

topk

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topk

Top-k over a small row, for a MoE router. One threadgroup per row, one reduction pass per output: k*n comparisons, but k and n are small and the launch dominates either way. Optionally softmaxes the k it selected, which is what a router wants and saves a second dispatch.

Not a port. ggml has no top-k of its own — GGML_OP_TOP_K dispatches kernel_argsort_f32_i32_desc, a full bitonic sort — and torch's MPS topk is a full sort too. Selecting the largest 8 of 256 logits does not need the row ordered: 26 us here against 71 us for either sort, once per layer per token.

indices comes back as int32, which is what an expert-routed matmul wants, so routing them onward costs no cast.

Usage

import torch
from kernels import get_kernel

topk = get_kernel("marcsun13/topk", version=1)

logits = torch.randn(1, 256, device="mps")          # one row of router logits

values, indices = topk.top_k(logits, 8)             # (1, 8) f32, (1, 8) int32
weights, experts = topk.top_k(logits, 8, True)      # values softmaxed over the selected 8