Upstream ships dflash depth 7 as a content-dependent default measured for TP=2
on their corpus. Re-measured on one card here, two runs per setting, 16
repo-derived prompts at 512 output tokens:
SPEC=7 conc1 46.2 tok/s, TPOT 20.8 ms, 3.86 tok/update
conc4 118.7 / 127.0 tok/s
SPEC=5 conc1 41.5 tok/s, TPOT 23.1 ms, 3.41 tok/update
conc4 136.1 / 129.4 tok/s
Step time is nearly identical at both depths (~79 ms vs ~80 ms single stream):
7 wins by landing more tokens per step, 5 wins at conc 4 by ~8% because more
narrow verify steps pack better. Depth 7 stays — this fleet is interactive
agent loops where per-turn latency is what is felt — and the runbook now
records the numbers and the one-line switch for a batch-first workload.
15 KiB
type, title, description, tags, timestamp
| type | title | description | tags | timestamp | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| configuration | frank-medium vllm-radiance MXFP4 Runbook | vllm-radiance MXFP4 serving just1moremodel/Qwen3.8-27B-Uncensored-MXFP4-awq as frank-medium on Dankserver (2x AMD Radeon AI PRO R9700, gfx1201), as two single-GPU replicas behind an adaptive-routing proxy — and the PCIe-atomics reason TP=2 cannot run on this host. |
|
2026-09-16 |
frank-medium vllm-radiance MXFP4 Runbook
The ACTIVE frank-medium deployment (since 2026-09-15/16): the
stilldeadcode/vllm-radiance:0.9.3 image plus the ggz14/radiance-vllm-mxfp4
patches, serving just1moremodel/Qwen3.8-27B-Uncensored-MXFP4-awq on the two
Radeon AI PRO R9700 (gfx1201) cards. It replaced the charlie12345/ROCmFPX
llama.cpp deployment (frank-medium-rocmfpx).
Deployed shape: two single-GPU replicas behind an adaptive-routing proxy. The intended shape — one tensor-parallel process across both cards (TP=2) — cannot launch a collective on this host. The reason is a hardware property of the motherboard's PCIe topology, not the image, the RCCL build, or the kernel version. The evidence is in Why TP=2 cannot run here.
Architecture
graph LR
C[clients: Hermes, harness] --> P["frank-medium-proxy<br/>:7770 adaptive routing"]
P --> A["frank-medium-a<br/>R9700 #1, TP=1, :7771"]
P --> B["frank-medium-b<br/>R9700 #2, TP=1, :7772"]
Three rootless Quadlet units, all WantedBy=default.target + Restart=on-failure:
| Unit | Container | GPU | Port | Role |
|---|---|---|---|---|
frank-medium-a |
frank-medium-a |
HIP_VISIBLE_DEVICES=0 |
7771 | replica |
frank-medium-b |
frank-medium-b |
HIP_VISIBLE_DEVICES=1 |
7772 | replica |
frank-medium-proxy |
frank-medium-proxy |
— | 7770 | routing |
The fleet contract is unchanged: one endpoint on :7770, served model name
frank-medium, OpenAI /v1, streaming included. The vLLM OpenAI API is
stateless per request, so no session affinity is needed for correctness. Routing
is described in Routing.
Only HIP_VISIBLE_DEVICES is set per replica, never a matching
ROCR_VISIBLE_DEVICES: ROCR filters first and HIP then indexes into the
filtered list, so the single-valued pair (ROCR=1,HIP=1) leaves an empty
device set and the engine dies with hipErrorNoDevice.
frank-medium.container (TP=2, KV_MEM=18563072000, MAXLEN=262144) stays in
the repo as the target shape for a host whose second card sits on an
atomic-capable root port. deploy-remote.sh deliberately does not install it
and moves any stale copy into ~/.AGENTTRASH/, because a TP=2 unit on this
host would restart forever without ever becoming healthy.
Why TP=2 cannot run here
Symptom
Any two-rank collective dies at launch:
[FATAL ERROR]: HIP failure: 'the operation cannot be performed in the present state'
group.cc:337 -> group.cc:656 -> group.cc:801 -> enqueue.cc:3111
With the runtime's own API log (AMD_LOG_LEVEL=3) the failing call is explicit:
ShaderName : ncclDevKernel_Generic_4(ncclDevKernelArgsStorage<4096ul>)
:1:rocvirtual.cpp :4208: Pcie atomics not enabled, hostcall not supported
:1:rocvirtual.cpp :4636: AQL dispatch failed!
:3:hip_module.cpp :893 : hipLaunchKernel: Returned hipErrorIllegalState
ROCclr refuses to hand the kernel a hostcall buffer when the device has no
PCIe atomics (rocclr/device/rocm/rocvirtual.cpp:3963), and the launch aborts.
hipErrorIllegalState is that refusal, not a driver fault.
Chain of causation
- RCCL's collective kernels carry a hidden hostcall buffer parameter.
- ROCr passes that buffer only when
pcie_atomics_is true for the device; otherwise it returns "not supported" and the dispatch fails. pcie_atomics_is set once, at device init, from the HSA link info between the CPU agent and the GPU (rocclr/device/rocm/rocdevice.cpp:186,Device::checkAtomicSupport). It is not re-read per process.- The KFD driver populates that link info from
pci_enable_atomic_ops_to_root(), which — per the PCIe spec and the kernel's implementation — requires every upstream bridge between the device and its root port to advertiseAtomicOp Routingcapability (drivers/pci/pci.c).
The hardware difference between the two cards
| Card | PCIe chain (endpoint → root port) | AtomicOpsCap on every hop |
AtomicOpsCtl |
|---|---|---|---|
R9700 #1 (03:00.0) |
02:00.0 → 01:00.0 → 00:01.1 |
Routing+ / Routing+ / Routing+ | ReqEn+ (atomics ON) |
R9700 #2 (0b:00.0) |
0a:00.0 → 09:00.0 → 06:09.0 → 05:00.0 → 00:02.1 |
Routing+ / Routing+ / Routing− / Routing− / Routing+ | ReqEn− (atomics OFF) |
Card #1 is on a CPU root port; card #2 is behind the chipset bridges
05:00.0/06:09.0, which advertise AtomicOpsCap: Routing-. That capability
bit is read-only — no software can enable atomic routing through those
bridges — so the driver's atomic enablement call fails for card #2 and the KFD
marks the CPU↔GPU2 link NO_ATOMICS.
Writing the AtomicOp Requester bit into the endpoint's Device Control 2 by hand
(setpci -s 0b:00.0 CAP_EXP+28.w) does not help: the driver reads the chain at
probe time, and ROCr consumes the driver's cached answer. Only a re-probe (a
boot with the write already in place) would change it — and even then the two
Routing- bridges would still make pci_enable_atomic_ops_to_root() fail.
What was ruled out
| Suspect | Result |
|---|---|
| Kernel version | 7.0.0-28, -30 and -31 fail identically (full apt full-upgrade to the newest available kernel changed nothing) |
| IOMMU | identical before and after iommu=pt |
| P2P hardware | fine: 45.3 GB/s bidirectional copy between the two cards; both cards pass rocm-bandwidth-test |
| The shipped librccl | a from-source rebuild of ROCm/rccl develop (with local fixes for that branch's dangling references) reproduces the same failure at the same call path — the library is not at fault |
| vLLM/pynccl | a bare two-rank torch.distributed allreduce with no vLLM involved fails the same way; single-rank collectives succeed on both cards (NCCL short-circuits at world_size=1, which is why a one-card test proves nothing) |
| Transport knobs | NCCL_PROTO=Simple, NCCL_P2P_DISABLE, NCCL_SHM_DISABLE, NCCL_CUMEM_ENABLE=0, MSCCL off, channel counts, launch modes, HSA_ENABLE_SDMA=0 — all identical |
| Image/support matrix | the same image on a different host with the same kernel (Proxmox VM, Codeberg issue #22) fails byte-identically |
What would fix it
- Move card #2 to a slot whose path is atomic-capable (a CPU root port, as card #1 has). This is the only software-free fix and the one that restores true TP=2. On this AM5 platform the CPU provides the x16 slot plus x4 lanes, so a second x16-class card necessarily lands on the chipset path — a platform with more CPU lanes (Threadripper/EPYC) is the structural answer.
- Until then, two replicas are how both cards serve.
Routing
The proxy decides per request, from proxy/routing.py (policy) and
proxy/affinity-proxy.py (HTTP plumbing):
- A continuation — a request carrying more than one message, i.e. an agent
loop re-sending its context — is pinned to the replica that served the
prefix before, because
--enable-prefix-cachinghas that prefix warm there. - Anything else — a one-shot question, a batch member, a burst of parallel subagents — spreads across the cards by counter, so both prefill in parallel.
Measured on this host, 90k-token contexts and 15k-token prompts, vllm bench
plus a small sequential-turn client:
| strategy | cold 16-request burst | warm-turn TTFT (4 turns × 2 families) |
|---|---|---|
roundrobin (counter) |
18.6 s | 2676 ms — every other turn pays a cold prefill |
affinity (hash of prefix) |
30.1 s — one card does all the prefilling | 1096 ms |
adaptive (deployed) |
19.97 s | 1095 ms |
Two failures found by measuring rather than reasoning, both now covered by
tests/frank_medium_proxy.bats:
- Hashing a fresh prefix to pick a card sends every member of a same-prefix burst to one card (29.8 s for the burst above). Only continuations may be pinned; the spread has to come from a counter.
- The identity of a conversation is its first 4 KiB (
AFFINITY_BYTES). A prefix shorter than that window is indistinguishable from its own tail, so turns of the same conversation hash differently and never pin.
ROUTING=roundrobin and ROUTING=affinity remain available to re-measure the
choice; the default is adaptive.
Deployed configuration
Both replicas, uniform except GPU index and port:
| Knob | Value | Why |
|---|---|---|
TP |
1 | one card per replica |
MAXLEN |
114688 | the largest shape that boots on one card: 262144 needs 9.61 GiB of KV against 5.14 available, and 131072 needs 5.58 against 5.22 |
KV_MEM |
0 | passed through literally as --kv-cache-memory 0, which the image's patched KV sizing reads as "profile this shape"; the upstream pin (2x7551-32624) is a TP=2/262144 measurement and is invalid here. Do not blank the variable instead of passing 0: with the flag omitted vLLM sizes the cache from GPU_UTIL alone and the KV allocation dies with torch.OutOfMemoryError (measured: 2.16 GiB requested, 116 MiB free, 29.34 GiB already held) |
MAXSEQS |
4 | matches the per-replica share of the fleet's concurrency |
CHUNK |
8192 | prefill chunk (upstream default), coupled to the context: the prefill arena grows with the chunk size and shares the device budget with the KV cache. Measured: CHUNK=16384 leaves 4.22 GiB of KV against the 5.21 GiB that 114688 context needs, and the engine refuses to start (To serve at least one request with the model's max seq len (114688), 5.21 GiB KV cache is needed, which is larger than the available KV cache memory (4.22 GiB)). Raising CHUNK therefore means cutting MAXLEN; single-card prefill measured ≈2.5k tok/s at 8192 (~15k-token prompt, 5992 ms TTFT), so the trade was not worth taking |
GPU_UTIL |
0.98 | upstream default; the card is dedicated |
SPEC_METHOD / SPEC |
dflash / 7 | the DFlash2-FP8 block-diffusion drafter. Depth 7 is upstream's production default and was re-measured here on a code corpus built from this repo (see Speculative depth); depth 5 wins batch throughput, 7 wins single-stream latency, and this fleet is interactive |
SNAP / DRAFTER |
/models/Qwen3.8-27B-Uncensored-MXFP4-awq / /models/Qwen3.8-27B-DFlash2-FP8 |
the served checkpoint and its drafter |
Mounts are the TP=2 unit's minus nothing: /models, the HF cache, the shared
compile cache, /patches (the pinned radiance clone; its patches are applied
at every container start), /r4d (the patched libr4d — the image's shipped
r4d.so predates the gated-delta-net overflow fix and NaNs this model), and
the entrypoint/healthcheck/proxy scripts mounted read-only out of
/home/dank/serverAppConfigs.
The healthcheck reads PORT, so one probe serves the replicas (:7771/:7772),
the proxy (:7770) and the TP=2 target.
Deploy and verify
./tests/run.sh # unit/config seams
./scripts/deploy.sh dankserver --service frank-medium
The handler re-tags docker.io/stilldeadcode/vllm-radiance:0.9.3 as
localhost/radiance-vllm:0.9.3 (this host's quadlet path cannot resolve
registry-prefixed refs from local storage at create time), installs the three
units, retires any stale TP=2 unit into the trash, restarts the trio and waits
for http://127.0.0.1:7770/health.
Verification that means something:
curl -s http://192.168.0.235:7770/health # proxy: names any replica that is down
curl -s http://192.168.0.235:7770/v1/models # served name must be frank-medium
# and a real completion through the proxy:
curl -s http://192.168.0.235:7770/v1/chat/completions -H 'Content-Type: application/json' \
-d '{"model":"frank-medium","messages":[{"role":"user","content":"Say OK"}],"max_tokens":400}'
The same call works against either replica directly (:7771, :7772) — when
one of them is down the other still serves, which is why the proxy reports the
individual replica states instead of a single boolean.
Benchmarks
vllm bench serve against the proxy (both cards serving), random dataset,
--ignore-eos, 2026-09-16:
| Case | Output t/s | TTFT p50 | TPOT p50 | Acceptance |
|---|---|---|---|---|
| conc 1, in 1k / out 512 | 42.8 | 382 ms | 23.6 ms | 43.1 % |
| conc 4, in 1k / out 512 | 147.6 | 471 ms | 25.3 ms | 34.2 % |
| conc 8, in 1k / out 512 | 230.8 | 913 ms | 28.8 ms | 39.0 % |
| conc 1, in 32k / out 32 | 2.5 | 11837 ms | 29.6 ms | 25.0 % |
The 32k row is a prefill measurement: 32768 prompt tokens in 11.8 s is ≈2.8k tok/s of prefill on a single card. The replicas split the fleet's traffic, they do not pool capacity for one request, against the upstream reference's 4585 t/s at 32k on TP=2 — one card doing the whole prompt lands where you would expect.
Read these against the upstream repo's own reference table (2x R9700, TP=2, BetterBench corpus): step time 22.8-23.2 ms per update, combined decode 224 t/s, prefill 4585 t/s at 32k. Step time (TPOT) is the comparable number — tokens/s swings with draft acceptance, and synthetic random prompts accept far worse than the code/prose mix upstream measures (43 % here against 5.8 tokens/update there), so a lower token rate at the same step time is the dataset, not the deployment.
Bench caveat: the client must be given --tokenizer /models/Qwen3.8-27B-Uncensored-MXFP4-awq with /models mounted. Passing only
--model frank-medium makes the client try to resolve that alias on
HuggingFace and die before sending a request — a green-looking run that
produced no numbers at all.
Speculative depth
Upstream ships depth 7 for dflash and notes the choice is content-dependent; it was measured for TP=2 on their corpus. Re-measured here on one card against a code corpus built from this repository's own sources (16 prompts, 512 output tokens each, two runs per setting):
| Depth | conc 1 | conc 4 |
|---|---|---|
SPEC=7 (deployed) |
46.2 tok/s, TPOT 20.8 ms, 3.86 tok/update | 118.7 / 127.0 tok/s, TPOT 25.1-29.3 ms |
SPEC=5 |
41.5 tok/s, TPOT 23.1 ms, 3.41 tok/update | 136.1 / 129.4 tok/s, TPOT 25.3-26.6 ms |
The step time is nearly identical at both depths (≈79 ms against ≈80 ms at
conc 1) — depth 7 wins single-stream because it lands more tokens per step
(3.86 against 3.41), and depth 5 wins at conc 4 by ≈8 % because more, narrower
verify steps pack better. Depth 7 stays: this fleet serves about three people
in interactive agent loops, where per-turn latency is the number that is felt,
and it is also the better default on code at low concurrency. Switch a replica
to SPEC=5 if batch throughput ever matters more than turn latency — it is one
environment line in the unit, at the cost of a recompile (the spec depth is
part of the graph cache key).
Citations
ROCm/clrrocclr/device/rocm/rocvirtual.cpp:3963— the hostcall-buffer refusal;rocclr/device/rocm/rocdevice.cpp:186—checkAtomicSupport.- Linux
drivers/pci/pci.c—pci_enable_atomic_ops_to_root()and itsPCI_EXP_DEVCAP2_ATOMIC_ROUTErequirements on upstream bridges. - Codeberg
StillDeadcode/vllm-radianceissue #22 — an independent host with the same image and kernel 7.0.0-30 failing identically. ggz14/radiance-vllm-mxfp4— the patch set and the reference benchmark table this page compares against.