docs(LLM): the decode stall a prefill causes, and the knobs that turn it #27

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---
type: reference
title: LLM Performance Diagnosis
description: Probing why a served LLM is slow — the flat-depth probe, the expert-offload duty-cycle arithmetic, kernel-time attribution via the profiler window, live telemetry without benchmarking, RAM-bandwidth ceilings, IBS tensor attribution and prefix-cache-aware routing.
description: Probing why a served LLM is slow — the flat-depth probe, the expert-offload duty-cycle arithmetic, kernel-time attribution via the profiler window, live telemetry without benchmarking, RAM-bandwidth ceilings, IBS tensor attribution, prefix-cache-aware routing, and the step-shape census behind decode stalls under a prefill.
tags: [performance, profiling, moe, pcie, prefix-cache, routing, telemetry]
timestamp: 2026-10-05T00:00:00-07:00
timestamp: 2026-10-19T00:00:00-07:00
---
# LLM Performance Diagnosis
@@ -213,9 +213,76 @@ function directly with synthetic bodies (stdlib-only policy module);
conversation identity is the FIRST N KiB of prompt — a shorter tested prefix
hashes differently per turn and pinning silently never happens.
## 9. Decode cadence under a prefill (the step-shape census)
"Decode turns to sludge the moment a long prompt arrives, then recovers" is not a
link or a gather story — on a chunked-prefill engine the unit of interference is
**the step**. A step that carries a prefill chunk takes the chunk's time, and every
decode row sharing that step waits that long for its next token. Chunk size is
`min(remaining, --checkpoint-interval, --max-num-batched-tokens)`, so on a hybrid
model the interval caps it before the budget does.
Census it without touching the model — the engine's own counters (`/stats`,
`/metrics`, cumulative since boot):
```
decode-only step = step_ns_decode / steps_decode
shared step = (step_ns - step_ns_decode) / (steps_prefill + steps_mixed)
```
Then bucket a day of `decode_tokens_per_second` by `prefill_tokens_per_second`
(Prometheus `query_range`, step 120 s) and **check the lag**: correlate decode with
prefill at lag 0 and again at 2-14 minutes. Lag-0-only ⇒ step-time contention, the
chunk is holding the device. A lagged tail ⇒ residency churn — the prefill's working
set evicted something decode needs (expert slab, KV) and decode pays after the
prefill is over. `preemptions` separates the third shape: a preempted-and-recomputed
sequence stops producing entirely and then re-prefills from token 0, which is a
stall, not sludge.
Knobs, in the order worth trying them (radiance GUIDE §4.5):
- `--prefill-interleave N` — after a chunk step taken beside decoders, the next N
steps carry decode rows only and admit nothing. Decoders keep their cadence; the
prompt pays that in TTFT. Counts as `engine_steps_held_total`.
- `--busy-prefill-chunk MODE` — the chunk's share of a step that has other work:
`auto` (default) reserves a row plus the draft window per decode row behind it and
an eighth of the budget per waiting prefill/request, `off` lets the chunk take the
whole step (admission never runs while it does), `N` pins the share. Never under
the prefill stager's smallest pass — the startup line names it, and below it every
routed layer reads its pooled experts synchronously, which costs the prefill far
more than sharing saves. Counts as `engine_prefill_chunks_capped_total`.
- `--max-num-batched-tokens` — the blunt rung, and the only one older pins have. The
vendor's curve on a 48-layer MoE at 200k on two cards: chunk 512 → 1750 t/s, 1024
→ 2200, 2048 → 2706 (a 185k prompt: 138 s against 91 s), so halving the stall
costs ~19 % of prefill. Raising it past the interval buys nothing and loses expert
residency to the arena.
- `--prefill-span N` — the inverse trade: a *lone* prefill carries N intervals a step
while every shared step is planned at a smaller shared budget, which on an
expert-tiered box lends that arena back to the expert slab. Vendor TP2
expert-tiered TTFT deltas vs a plain 2048 budget: −6.1 % at 2k, +2.3 % at 18k,
+49.1 % at 250k — long prompts only.
Two traps. **The arena/slab coupling makes a shared step doubly expensive on an
expert-tiered shape**: the full-plan arena takes VRAM the resident expert slab would
have had (320 MiB/card at TP2 for a 4096 budget), so the decode rows inside that step
also read experts over the link — a smaller shared budget helps twice. And **re-check
`prefix_hit_rate` / `prefix_evictions` after any chunk change**: the arena and the KV
pool are the same memory, and the failure looks like turn two taking as long as turn
one.
Availability is a version question, not a config question: `--busy-prefill-chunk` and
`--prefill-interleave` are absent from older pins — prove it on the running container
(`podman exec <c> <binary> --help | grep -iE "prefill|chunk"`), never from the vendored
tree, and check the source clone's depth before dating a flag from `git log -S`
(a `--depth 1` clone reports its own tip for every search).
Run on: [[frank-archon]] (radiance 1.0.13, TP2 `expert_tiered`, budget 2048 = interval
2048) — the measured census and the verdict for this fleet's shape are that page's.
## Related
- [[LLM Bench Windows and Measurement]] — the window discipline and usage-counter law
- [[PCIe Link and Atomics]] — link probing and the streaming-vs-compute ceiling
- [[RDNA4 MoE Expert Offload VRAM Budget]] — the plan behind duty-cycle terms
- [[vLLM Porting and Compile Triage]] — the compile fix for the pointwise-glue bound
- [[frank-archon]] — the endpoint where §9's step-shape census was run
+23
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@@ -234,6 +234,29 @@ Before 2026-09-26 the port belonged to the **`frank-medium`** service: [[frank-m
- **MNBT 2048.** 2560 collapses decode to 2.6-7.7 t/s (MTP resonance); the w4 file tier streams
in place only at MNBT ≤ 2048 and the activation arena scales with the chunk (32768 → 33.3
GiB, refused).
- **Decode pays for the chunk it shares a step with.** Census of the live engine
(radiance 1.0.13, `/stats` + `/metrics`, cumulative over the 2026-10-15 boot):
1,435,585 decode-only steps at **18.7 ms** each against 127,991 prefill+mixed steps
at **317 ms** — 60 % of engine wall-clock spent inside 8 % of the steps, because the
chunk is `min(remaining, checkpoint interval 2048, MNBT 2048)` = 2048 rows and every
decode row in that step waits the whole chunk. Day of Prometheus (120 s step, 721
samples): `decode_tokens_per_second` median **13.3 t/s** in the 56 % of samples where
`prefill_tokens_per_second` ≥ 1000, against 106-240 t/s in the light-prefill buckets;
bucketed by mean step time it is 128.7 t/s at 0.02-0.05 s steps and 12.0 t/s at
0.15-0.4 s. The stall is **during**, not after — decode in windows 2-14 min after a
busy-prefill window sits at the idle baseline (58-64 vs 77-85 t/s, the residual
confounded by co-scheduling), so no lingering expert-residency penalty at 2-minute
resolution, and `preemptions: 0` rules out preempt-and-re-prefill. Method:
[[LLM Performance Diagnosis]] §9.
- **The knobs for it are not in this pin.** `--busy-prefill-chunk` and
`--prefill-interleave` (radiance GUIDE §4.5 — a shared chunk's cap, and N decode-only
steps after each chunk) are absent from 1.0.13: proven on the running container
(`podman exec frank-archon radiance --help` prints no `prefill`/`chunk` flag), and the
2026-10-18 source tree carries both. The only crank this pin has is MNBT, and that is
an arm and not an edit: the vendor prices a 1024 chunk at −19 % prefill to halve the
stall, and this page's own MNBT law already knows 2560 collapses decode (MTP
resonance). An image bump is gated by the 1.2.0 numerics dead end below, so any try
re-scores draft acceptance before it is trusted.
- **Slots cost KV and rows, never speed.** `--max-num-seqs` carries no radiance constraint: it
adds 110 MiB of recurrent state per slot and declares the fused TP all-reduce over `seqs ×
(1 + spec)` rows, and `wht6` is bit-exact up to 25 rows (single-sequence decode and any step