123 lines
6.1 KiB
Markdown
123 lines
6.1 KiB
Markdown
# esh-ml1
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GPU LXC for the ESH home lab: **CT 110 on esh-pve**, holding the **NVIDIA RTX
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2000E Ada** (16 GB, 50 W, `01:00.0`). It serves the fleet's embedding and
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reranking models locally at ESH. Built 2026-09-24.
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| **IP** | `10.0.50.80/24`, VLAN 50, gateway `10.0.50.1` (static, outside the UDM's `.150–.250` DHCP pool) |
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| **DNS** | `esh-ml1.esh.internal` |
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| **SSH** | `ssh esh-ml1` → `infra-ops@10.0.50.80` (NOPASSWD sudo) · from the host: `pct enter 110` |
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| **OS** | Debian 12, unprivileged, `nesting=1,keyctl=1` |
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| **Size** | 6 cores, 16 GB RAM + 2 GB swap, 80 GB rootfs on `local-lvm` |
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| **Boot** | `onboot: 1`, `startup: order=30` — after esh-scale (1), esh-vm-db (10) and esh-vm-docker (20), so a GPU fault never delays ESH's DNS or mesh route |
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| **Backups** | **None, on purpose.** esh-pve's vzdump job lists vmids explicitly and 110 is not one. Everything is rebuilt from the playbooks and the stack; models re-download. |
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## What it serves
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`stacks/embed-rerank` (`/opt/docker/compose/embed-rerank`):
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| container | model | port | gateway name |
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| `vllm-embed` | `Qwen/Qwen3-Embedding-0.6B` | 8001 | `qwen3-embedding` (order 2) |
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| `vllm-rerank-bge` | `BAAI/bge-reranker-v2-m3` | 8013 | `reranker` (order 2) |
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The same models, vLLM version (`v0.24.0`, digest `251eba5cc7c1`) and flags as
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fv-ml1's `vllm` stack, so the two sites are interchangeable. In LiteLLM they
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are the **order-2 failover** behind fv-ml1: fv-ml1 serves every request while
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it is up.
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**Parity, measured 2026-09-24** (11 texts incl. CJK, code, a 6k-char passage;
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2 runs per site):
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| | median | min |
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| embed cosine FV vs ESH, same text | 0.999908 | 0.999772 |
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| noise floor FV vs FV | 0.999927 | 0.999791 |
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| noise floor ESH vs ESH | 0.999911 | 0.999809 |
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| negative control, different texts | 0.232 | 0.071 |
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The cross-site difference is inside each site's own run-to-run noise; this
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method cannot resolve a cosine gap below ~2×10⁻⁴. Reranker scores differed by
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at most 0.000145 (FV-vs-FV floor 0.000181), with identical ranking.
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**Speed vs fv-ml1, measured 2026-09-25 0628–0640 PT** (same vLLM v0.24.0 and
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flags; fv-ml1 GPU 1 is shared with other seats but read 0% util before and
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after; synthetic text; each cell = median of 6 reps = 2 interleaved runs × 3):
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| workload | on-box FV | on-box ESH | from ana-docker FV | from ana-docker ESH |
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| embed 1 query, p50 | ~12 ms | ~9 ms | ~29 ms | ~23 ms |
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| embed 1 × ~512 tok, p50 | ~15 ms | ~23 ms | ~31 ms | ~31 ms |
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| embed 1 × ~2k tok, p50 | ~25 ms | ~86 ms | ~48 ms | ~90 ms |
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| bulk embed, passages/s (64×512 tok, conc 4) | ~403 | ~50 | ~374 | ~51 |
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| rerank 20 docs, p50 | ~51 ms | ~170 ms | ~82 ms | ~175 ms |
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| rerank 20 docs, req/s at conc 8 | ~55 | ~5.7 | ~52 | ~5.9 |
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Read it as: **single queries are a wash** (ESH is ~6 ms faster from the gateway
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because it is closer — 6 ms RTT vs 17.6 ms), **anything bulk is 3–10× slower**
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on the 50 W Ada. Noise floor (run vs run, same site): ~3–5% on throughput, ±3 ms
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on small-query latency on fv-ml1, so the small-query rows cannot rank the sites.
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Positive control: 2k-token inputs were slower than 512-token ones on both
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sites. One fv-ml1 rep of the gateway-vantage rerank burst stalled to 1.0 req/s
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(64 requests in ~64 s); it did not recur in 11 other reps — unexplained, n=1.
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**Consequence: keep esh-ml1 as failover, don't load-share** — sharing would
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roughly double rerank latency for half the fleet's calls.
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**Whole-novel embedding, measured 2026-09-25 0653–0717 PT** — *The Stand*
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(uncut, ~1,150 pages): 470,783 words, 12,814 `<p>` paragraphs (median 22 words),
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617,833 tokens. Client on nh3-dev (where worldtree-gateway runs); 3 reps each:
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| how | fv-ml1 | esh-ml1 |
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| via gateway, 1 paragraph per request (1,000-para sample, scaled) | 59.8 ms/para → ~12.8 min | 55.3 ms/para → ~11.8 min |
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| via gateway, 64 per request, 1 at a time | 100–123 s | 91–100 s |
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| via gateway, 64 per request, 4 in flight | 46–54 s | 45–50 s |
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| direct to the seat, 64 per request, 4 in flight | 13.4–14.1 s | 28.8–29.6 s |
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Through the gateway the GPU is not the bottleneck: one-per-request is network +
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LiteLLM overhead, and batched runs pinned LiteLLM at ~76% CPU (64×1024-float
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JSON per response). Only the direct path shows the card: esh-ml1 is ~2.2×
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slower, ~21k vs ~45k tokens/s.
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**VRAM:** 0.20 × 16,380 MiB each; 4,823 MiB in use with both loaded, ~11 GB
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free.
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## How it is built
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1. [`playbooks/esh-pve-nvidia-host.yaml`](../../playbooks/esh-pve-nvidia-host.yaml)
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— driver **580.178.04** (open modules, DKMS) on the **hypervisor**, the
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`nvidia-persistenced` unit that creates the device nodes before
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`pve-guests`, and removal of the old VFIO/blacklist config.
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2. [`playbooks/esh-ml1-lxc.yaml`](../../playbooks/esh-ml1-lxc.yaml) — the CT,
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`dev0–3` GPU nodes, the NVIDIA userspace from the **same `.run`** with
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`--no-kernel-modules`, fleet ids (infra-ops 850, docker 851, vh 1000),
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docker-ce and nvidia-container-toolkit with `no-cgroups = true`.
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3. `scripts/deploy-stack.sh esh-ml1 embed-rerank`, then `docker compose up -d`.
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Both playbooks are idempotent; re-run them to repair.
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## ⚠ Driver version lock
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The kernel module lives on esh-pve; the libraries live in this container. They
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**must be the same version**, or every CUDA call fails with *"driver/library
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version mismatch"*. To upgrade: bump `driver_version` + `driver_sha256` in the
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host playbook and `driver_version` in the LXC playbook, run the host one, then
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the LXC one, then restart the stack.
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A PVE kernel update is handled by DKMS (`proxmox-headers-6.8` pulls headers
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for each new kernel). Moving esh-pve to a different kernel series (6.14 opt-in)
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needs that series' headers meta-package installed first, or the module will not
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build and this CT will fail to start at the next boot.
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## Not yet wired
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- **Homepage**: the compose carries labels, but esh-ml1 is not in
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`stacks/homepage/conf/docker.yaml` (it would need dockerd on tcp/2375 like
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the other hosts).
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- **Beszel**: no agent yet.
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- **ESH consumers** (Open WebUI RAG, Paperless) still go through the gateway
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at ana-docker, so they do not survive a mesh outage. See persistent-memory
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for the open decision.
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