# Qwen3.8-27B Pipeline-Parallel Deployment (Dankclaw + Dankserver)

Split Qwen3.8-27B UD-Q8_K_XL across the Strix Halo iGPU (head) and the RTX
3090 (worker) using llama.cpp RPC. This page is the design record and the
morning-of runbook. Research background:
[Qwen3.8 Strix optimizations](../../qwen3.8-strix-optimizations.md).

## Topology

```
Dankclaw (head, 192.168.0.143)          Dankserver (worker, 192.168.0.235)
llama-server b10433                      ggml-rpc-server b10433
  --rpc 192.168.0.235:50052                 --host 192.168.0.235 --port 50052
  model file (31.5 GB)                     -d CUDA0 -c (tensor cache)
  [RPC0, ROCm0|Vulkan0]  layers            RTX 3090: layers 0..~31
  Strix:    layers ~32..64 + lm_head
  hidden state ~20 KiB crosses the link once per token, each direction
```

- **Layer-sequential split** (true pipeline parallelism): layers 0..N run on
  the worker, the rest on the head, in order. One hidden-state handoff per
  token step. RTT-bound, not bandwidth-bound.
- **Why the head is on Dankclaw:** the model file is already there; the
  worker streams its tensor share at load (no 31.5 GB copy to the server).
- **Both sides must run the identical build** (b10433 / 9b05354ec). The
  worker build lives in a worktree `/home/dank/llama-cpp-rpc` on Dankserver
  so the production b10121 build stays untouched. A version skew hangs the
  RPC handshake with no error.

## Files

| File | Machine | Purpose |
|------|---------|---------|
| `scripts/frank-pp-worker.env` | server | worker tunables (bind, port, device, cache) |
| `scripts/serve-pp-worker.sh` | server | runs `ggml-rpc-server` from the b10433 worktree build |
| `scripts/frank-pp-head.env` | claw | head tunables (split, ctx, spec, KV, I/O) |
| `scripts/serve-pp-head.sh` | claw | runs `llama-server --rpc ...` (see "Gotchas") |
| `scripts/frank-pp-head.service` / `frank-pp-worker.service` | both | optional systemd units (manual install) |
| `scripts/pp-test.sh` | any box with ssh to both | test orchestrator (preflight/start/verify/bench/stop-pp/restore) |
| `scripts/pp-bench.py` | claw | API driver; reports server-side `print_timing` |

## Gotchas (all verified in b10433 source / live tests, 2026-08-15)

1. **No `--device` on the head.** Setting `params.devices` makes
   `llama_prepare_model_devices` use exactly that list; the RPC device is
   silently dropped and `--rpc` becomes a no-op. Omit it; default selection
   puts RPC first.
2. **The iGPU side is ROCm by default.** Backends register in fixed order
   (HIP before Vulkan); the iGPU dedup rule keeps the first backend's view.
   Live check showed `[RPC0, ROCm0]`. For a Vulkan side, use the second
   head build `/home/dank/llama.cpp/build-vulkan-rpc` (HIP off) — set
   `HEAD_BIN` in the env. Trade: ROCm side = faster prefill, ~3% slower
   decode (measured on this box).
3. **Pin `--tensor-split 1,1`.** The default split is proportional to
   *reported free memory*: the Strix reports up to 96 GiB (GTT) vs the
   3090's 24 GB, so the default lands ~20/80 on the slow device (verified
   with a 4B smoke test). 1,1 = 50/50 = balanced per-layer latency.
4. **`-dio` on the head.** Large model + RPC hangs at load without direct
   I/O.
5. **RPC is unauthenticated and unencrypted.** LAN only. The worker binds
   0.0.0.0-equivalent by design (`--host 192.168.0.235`).
6. **Env var names.** Never `TEMP`, `HOST`, or `GPU_MAX_HEAP_SIZE`
   (HIP runtime reads them; the 2026-08-13 `TEMP` incident).
7. **Page-cache state confounds loads.** `pp-test.sh start` drops caches on
   the head before load (warm-cache loads crash fast; cold loads survive).

## Runbook (morning of 2026-08-16)

Run from any box with ssh access to both (repo path on claw:
`/home/dank/vllmScripts`, on server: `/home/dank/vLLM`).

```
# 0. one-time: pull the kit on both boxes
ssh dank@dankclaw   'cd /home/dank/vllmScripts  && git pull'
ssh dank@dankserver 'cd /home/dank/vLLM && git pull'

# 1. checks (read-only)
./scripts/pp-test.sh preflight

# 2. full run: stop prod -> start PP -> verify split -> bench -> restore
FRANK_SUDO_PW=<pw> ./scripts/pp-test.sh all

# or step by step:
FRANK_SUDO_PW=<pw> ./scripts/pp-test.sh start
./scripts/pp-test.sh verify          # layer split + worker VRAM
./scripts/pp-test.sh bench 4 256 2   # ~4k prompt, 256 out, 2 reps
./scripts/pp-test.sh bench 16 256 1
FRANK_SUDO_PW=<pw> ./scripts/pp-test.sh stop-pp
FRANK_SUDO_PW=<pw> ./scripts/pp-test.sh restore
```

Config variants: edit `scripts/frank-pp-head.env` on the claw (git commit +
pull if the bench runs from the repo), then re-run `start` + `bench`:

- No spec baseline: `SPEC_NONE=1`
- Vulkan head side: `HEAD_BIN=/home/dank/llama.cpp/build-vulkan-rpc/bin/llama-server`
- Q4_0 MTP draft head: add `--spec-draft-model /home/dank/models/Qwen3.8-27B-MTP-Q4_0.gguf` to the serve script's SPEC block (env hook: see `SPEC_DRAFT_MODEL` below)
- n_max sweep: `SPEC_DRAFT_N_MAX=3|4|5`
- Plain Q8_0: `MODEL_FILE=Qwen3.8-27B-Q8_0.gguf` (file must be on the claw)

Verification checklist after each `start`:

1. `verify` shows `using device RPC0 ... using device ROCm0|Vulkan0`.
2. Layer assignment lines (`-lv 10`): worker gets the first ~32 layers at a
   1,1 split.
3. `nvidia-smi` on the server shows ~15–16 GB used by the worker
   (production small service + worker share).
4. Head GTT usage (rocm-smi) well under 96 GiB; model fully on devices
   (`--gpu-layers all` offloads everything; CPU holds embeddings/lm_head glue).

## Expected numbers

Per-layer: 3090 ≈ 2–3× faster than the 8060S. 50/50 split → each token
step ≈ max(32 layers on 3090, 32 layers on Strix) + ~0.5 ms RTT.

- Production reference: 25 t/s @16k (Vulkan, spec, single node).
- Target: **≥ 30 t/s @4k, ≥ 20 t/s @16k** with spec.
- Decode floor: with ngram/mod acceptance, spec multiplies the raw rate;
  raw (no spec) rate should clear ~15–18 t/s @16k for the target to hold.

## Rollback

`pp-test.sh restore` starts both production services. If a PP test wedges a
box: `systemctl restart <unit>` after killing the stray processes
(`pkill -x llama-server` / `pkill -x ggml-rpc-server` — never `pkill -f`
with a pattern matching your own ssh command line).

## Open questions for the test day

1. Does the MTP head (which sits in the last layer group, iGPU side) draft
   cleanly with the verify pass crossing the RPC boundary? Watch acceptance
   in the head log (`draft acceptance = X`).
2. Two parallel slots on the split (PARALLEL=2, CTX 65536): RPC is
   serialized per compute — expect the 2-slot speedup to be weaker than
   single-node. Measure, do not assume.
3. Prefill parity: ROCm-side head should prefill ≥ single-node ROCm; if not,
   the ubatch crossing the RPC boundary is the suspect.