[GG] fix(exl3): prewarm mixed-Trellis route packing

[malaiwah]

What changed

• Retain the immutable mixed-Trellis runtime created by the first eager profile pass.
• Delegate route-pack specialization enumeration and materialization to the matching b12x backend.
• Invoke that warmup from vLLM's existing kernel-warmup phase, before the second profile pass and KV-cache sizing.
• Fail closed when a selected mixed-EXL3 layer was not planned or the matching backend API is absent.
• Log the warmed specialization count and observed device free-memory delta.

Why

The existing warmup_b12x_moe_dynamic() recognizes ordinary B12xExperts, but EXL3 mixed Trellis uses its own quant method and reaches b12x route packing directly. Profiling the maximum batch creates the runtime but leaves smaller route-capacity and scalar-alignment Triton specializations lazy.

An r28 GLM-5.2 EXL3 production process later loaded _pack_topk_routes_post_prefix_kernel during live traffic and failed inside Triton's CUDA binary loader with OOM. Active KV usage was low; the KV pool had already consumed the remaining device headroom. Running the backend warmup between the first and second profile passes makes persistent module residency visible before KV blocks are assigned and turns insufficient headroom into a startup failure rather than a serving crash.

Dependency and base

• Stacked on local-inference-lab/vLLM PR [GG] consolidate EXL3 runtime and prewarm mixed-Trellis routes #228, which owns the EXL3 mixed-Trellis integration.
• Depends on local-inference-lab/b12x PR #126.

Scope and duplicate check

This does not duplicate local-inference-lab/vLLM PR #248, which prewarms the CuTe PCIe one-shot collective, or vllm-project/vllm PR vllm-project#41481, which warms speculative-decoding helper kernels. It is the missing EXL3 mixed-Trellis route-pack provider hook. It is compatible with the broader vllm-project/vllm JIT warmup RFC vllm-project#47456.

The companion b12x PR also prewarms rank-sliced native-MTP draft plans from their backend-owned plan warmup. That draft runtime is not reachable from this vLLM target-model hook, so the two changes intentionally close the target and draft sides at their respective owners.

Validation

• ruff check and ruff format --check on all changed files
• py_compile on changed source/tests
• Exact r28 runtime image: 17 vLLM tests passed plus 6 focused b12x tests passed
• AIBoss RTX 5090 GPU qualification using GGv20r28 plus only vLLM [GG] fix(exl3): prewarm mixed-Trellis route packing #250 and b12x [gg-rebased] perf(dspark): port adaptive draft capacity experiments #126:
  • 32 mixed-Trellis variants materialized before KV sizing for the 2K profile; measured residency 2.0 MiB
  • logical KV changed 2,926,208 -> 2,925,952 (-256 tokens, -0.009%)
  • route-pack inference JIT changed from small_prefix + sort on control to none over a 1/2/5/8/9-token battery
  • identical generated output and 35.1 vs 36.0 tok/s CC1 (noise-level parity)
  • reverse-order warm-cache prefill A/B stayed within -1.22% to +1.44% at 256/1K/2K/4K/6K rows
  • 32K long-context gate passed with no route-pack inference JIT and successful planted-name retrieval
  • native MTP1 draft: post-start route-pack JIT changed from small_prefix + sort to none
  • MTP draft residency was exactly 2.0 MiB: logical FP8-KV capacity changed 1,865,920 -> 1,865,728 (-192 tokens, -0.010%)
  • native-MTP output and acceptance were unchanged: 451/571 accepted (79.0%), MAL 1.790, FRUIT-MTP-OK
  • the exact final head restarted from a populated compilation cache in 6.80 s with no route-pack inference JIT
  • read-only AIBeast production audit corroborated the incident: an MTP3 TP4/DCP4 r28 worker failed in Triton's load_binary() for _pack_topk_routes_post_prefix_kernel with CUDA: out of memory at only 1.18% active KV usage; the restarted engine later lazily loaded post_prefix and sort again

Exact hardware, image/model revisions, and measurements are posted in the GPU evidence comment below.

Production AIBeast remained online and untouched. Full TP4/DCP4 and CUDA-graph qualification remains pending, so this PR stays draft.

AI assistance was used. The submitter reviewed the complete diff, reproduced both the original and scalar-alignment misses, and ran the checks above.

[coderabbitai]

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[malaiwah]

AIBoss Blackwell GPU evidence (2026-08-07)

The corrected stack is GPU-qualified for both the real mixed-Trellis target path and its native rank-sliced MTP1 draft path on one RTX 5090.

Provenance

• GPU: NVIDIA GeForce RTX 5090, 32,607 MiB, driver 610.57.04, 400 W limit
• Base: GGv20r28 sha256:501e10e79b4bc854237804d215e454c531ac9c2d354a8fa1a93e450fe7ba6ce0 (CUDA 13.2.1)
• Model: malaiwah/GLM-5.2-SIQ-Fruit-Instruct@acd11237ebe808efb8fe688ee50bf24c7fd466a0
• Patch heads: b12x [gg-rebased] perf(dspark): port adaptive draft capacity experiments #126 6022e6e7c7ea1199a06a27cf5a777c2804b13cfb; vLLM [GG] fix(exl3): prewarm mixed-Trellis route packing #250 2a34b0760f4d9bbd5d2ff6809238593098bd46ff
• Derivative image ID: 49c108672a18fef0a0a0860d14e6ef0b7b4fc2746327ba95658430140ccbcedb
• r28's legacy sparkinfer package name was identifier-normalized only; both PR diffs passed git apply --check against the exact installed sources.

The first GPU run caught and fixed a real coverage miss

Warming only the maximum live row count for a power-of-two capacity bucket did not cover a five-row request: Triton also specializes the runtime live_numel scalar by divisibility/alignment. The first MTP extension then exposed a second false equivalence: the target uses int32 route IDs while the native draft uses int64. The final b12x head warms both scalar classes and both ID dtypes, and keys the prewarm cache by dtype. Exact-r28 focused tests are 6/6 green.

Matched 2K serving smoke (TP1/DCP1, eager, B12X sparse MLA, NVFP4 MLA KV, seqs=4, GMU=.75)

	r28 control	patched	delta
route variants pre-KV	0	32	+32
measured module residency	lazy/unmeasured	2.0 MiB	+2.0 MiB
logical KV tokens	2,926,208	2,925,952	-256 (-0.009%)
cold engine init	24.44 s	29.11 s	+4.67 s
CC1 decode smoke	35.1 tok/s	36.0 tok/s	no regression signal
post-start route-pack JIT	small-prefix + sort	none for 1/2/5/8/9 tokens	fixed

Generated outputs were byte-identical. On populated JIT caches, both engine initializations were 7.04 s.

Reverse-order warm-cache prefill repeat

Five post-warmup samples per cell:

rows	control	patched	delta
256	8,606	8,501 tok/s	-1.22%
1,024	33,789	34,274 tok/s	+1.44%
2,048	66,415	66,374 tok/s	-0.06%
4,096	74,905	74,997 tok/s	+0.12%
6,144	108,056	108,238 tok/s	+0.17%

This is steady-state parity within noise; the value is predictable residency and elimination of live-serving route-pack JIT, not throughput.

Long-context path gate

At max model length/batch 32,768, 40 variants warmed for 2.0 MiB, KV capacity was 2,343,680 tokens, and no _pack_topk_routes_* kernel JITed after engine start. A 4,026-token retrieval prompt returned the planted name Lily; FRUIT-LONG-SERVE-OK.

Native MTP-draft closure

The native MTP1 run uses FP8 MLA KV, TP1/DCP1, eager mode, max model length/batch 2,048, max sequences 4, and GMU 0.75. The control target-only patch still lazily loaded _pack_topk_routes_small_prefix_kernel and _pack_topk_routes_sort_kernel from the distinct rank-sliced draft runtime after engine start.

	target-only warmup	final target + draft warmup	delta
logical KV tokens	1,865,920	1,865,728	-192 (-0.010%)
accounted module residency	draft lazy/unmeasured	+2.0 MiB	+2.0 MiB
post-start draft route-pack JIT	small-prefix + sort	none	fixed
accepted drafts	451/571 (79.0%)	451/571 (79.0%)	identical
mean accepted length	1.790	1.790	identical
output	expected story	byte-identical story	unchanged

The cold final run took 43.04 s versus 30.27 s for the target-only image because the empty cache now compiles the draft specializations during initialization. With the compilation cache populated, the exact final image initialized in 6.80 s, served the same output, retained the same acceptance, emitted FRUIT-MTP-OK, and loaded no _pack_topk_routes_* kernels after engine start. The decode smoke was 58.8 versus 63.8 tok/s, but that single sample is clock/cache noise and is not presented as a speedup.

Raw-log SHA-256:

• cold final: aebc5c2df64641a22e60b349362e3fc48857ced59c096746adf906fe2f8a6bc7
• exact-head warm cache: 9628800b5137a1ecd1bb5f2a9f4fdf9f070b2fea448249ecc192b492809d9c11

Production corroboration

A read-only audit of the untouched AIBeast r28 production container found the exact failure family in an MTP3 TP4/DCP4 service. At 2026-08-07 10:11:29, TP3 entered _apply_mixed_rank_sliced -> run_mixed_trellis -> pack_topk_routes_by_expert -> _pack_topk_routes_post_prefix_kernel; Triton's load_binary() failed with RuntimeError: Triton Error [CUDA]: out of memory. Scheduler telemetry reported only 1.18% active KV usage and two running requests, excluding active-request KV pressure as the cause. The engine timed out and restarted. The new process then warned that post_prefix and sort were again JIT-loading during inference.

This trace establishes that late route-pack module residency is already capable of crashing the production MTP stack. It does not by itself identify that particular launch as target versus draft; the final patch closes both owners.

Qualification boundary

This closes the measured target and native-MTP route-pack residency gaps for the TP1 eager Blackwell path. TP4/DCP4 and CUDA-graph capture remain pending; AIBeast production was not interrupted.

[malaiwah]

Native MTP-draft allocation gap closed on AIBoss

The b12x head is now 6022e6e7c7ea1199a06a27cf5a777c2804b13cfb. The rank-sliced full-rotation plans used by native MTP drafts prewarm every reachable route-capacity/scalar class, both int32 and int64 route-ID specializations, and mapped/unmapped routes. Route-ID dtype is part of the prewarm cache key.

Exact GGv20r28 A/B on one RTX 5090, native MTP1, FP8 MLA KV, TP1/DCP1, eager, max model length/batch 2,048, max sequences 4, GMU 0.75:

• post-start draft route-pack JIT: small_prefix + sort -> none
• logical KV: 1,865,920 -> 1,865,728 (-192 tokens, -0.010%)
• newly accounted persistent residency: exactly 2.0 MiB
• accepted drafts: 451/571 (79.0%) -> identical
• mean accepted length: 1.790 -> identical
• generated output: byte-identical, FRUIT-MTP-OK
• cold initialization: 30.27 -> 43.04 s because an empty cache now compiles the bounded draft set before KV sizing
• exact final head, populated cache: 6.80 s initialization, still no post-start route-pack JIT

This is a reliability fix, not a throughput claim. It converts a small, previously invisible MTP draft allocation into startup-accounted residency before vLLM commits the remaining memory to KV. TP4/DCP4 and CUDA-graph capture remain the outstanding qualification gates; AIBeast production was not interrupted.

A subsequent read-only AIBeast audit confirmed this is an active production risk: the MTP3 TP4/DCP4 r28 stack failed inside Triton's load_binary() for _pack_topk_routes_post_prefix_kernel with CUDA: out of memory while active KV usage was only 1.18%. The engine restarted, then lazily loaded post_prefix and sort again. That trace establishes the route-pack residency failure family, while the final patch closes both the target and distinct native-draft owners.

The full evidence comment and PR descriptions have been updated with provenance and raw-log SHA-256 values.

[voipmonitor]

Superseded by the same warmup commit, preserving Michel's authorship, now applied directly to the current #228 branch at 5ec9357. This removes the stale stacked-base conflicts while keeping the three-file implementation intact. The focused adapter tests pass 3/3 on the current r30 runtime, and #228 remains based directly on dev/gilded-gnosis. The r31 release manifest therefore pins updated #228 rather than this stacked PR.