[HiSparse] Add MHA hisparse support for MiniMax M3 (#31446)

Co-authored-by: Guangda Liu <bingps@users.noreply.github.com>
This commit is contained in:
Guangda Liu
2026-09-22 13:28:03 +08:00
committed by GitHub
co-authored by Guangda Liu
parent 095e45100b
commit 04c0913434
27 changed files with 1016 additions and 118 deletions
@@ -129,6 +129,7 @@ The NVIDIA Blackwell recipes are validated single-node: **B200 at `--tp 8`** and
- **Memory**: `--mem-fraction-static` reserves GPU memory for weights + KV pool; the rest is prefill **activation headroom**. The value scales with *free* memory per GPU (card capacity minus per-GPU weight), so it tracks the card more than the TP degree: **`0.65` on B200** (180 GB — less headroom once weights are resident) and **`0.75` on the larger-memory B300 / GB300** (`0.80` on AMD). Lower TP packs more weight per GPU, so a tighter config needs a *lower* value — B200 needs `0.65` even at `--tp 4`. Raising it past the validated value is fine only for low-concurrency single-stream serving; it OOMs under high concurrency or long context.
- **Long context (32K+)**: keep `--mem-fraction-static` at the platform default and raise `--chunked-prefill-size` to `16384`. Decode TPOT stays roughly flat in context length thanks to sparse attention; 1K–128K prompts are validated.
- **HiSparse for decode capacity**: on NVIDIA CUDA, HiSparse keeps the three dense layers on GPU, moves the 57 sparse-layer K/V caches to pinned host memory, and feeds selected block IDs directly to the swap-in kernel. For the released four-KV-head model, use `--tp 4` or greater, `--disable-radix-cache`, and `device_buffer_size >= 2048`. Enable it with `--enable-hisparse --hisparse-config='{"device_buffer_size":4096,"host_to_device_ratio":2}'` on the Triton launch command.
- **Scaling TP**: B200 is documented at `--tp 8`; B300 / GB200 / GB300 at `--tp 4` (the single-node cross-family common denominator). On an 8-GPU B300 host you can also raise to `--tp 8` for more throughput / KV headroom.
- **Expert parallelism**: to trade latency for throughput add `--ep` (see [Expert Parallelism Deployment](../../../docs/advanced_features/expert_parallelism)). On AMD, set `--ep` equal to `--tp`. Shared-experts fusion is automatically disabled when EP > 1; on AMD standard EP the server also disables `--enable-aiter-allreduce-fusion` automatically to preserve accuracy.
- `--trust-remote-code` is required to load the MiniMax config / processor classes.