vh/esh-pfi-infrastructure
1
0
Fork 0
Code Issues 7 Pull Requests Actions Packages Projects Releases Wiki Activity

feat(fv-ml1): rebalance GPUs 0/1 by usage; contexts to published maximums; gen-small default output cap

Browse Source 
Layout: GPU 0 = cyberprev (KV 16 -> 15 GiB, 1.29x), erp-seat (moved from
GPU 1, KV 8.49 -> 5.5 GiB, 1.32x), voices (ctx 8,192 -> 40,960, its native
maximum, KV 6 GiB, 1.07x), coder (moved from GPU 1, ctx 16,384 -> 32,768,
the card maximum, 2.35x), parakeet-nemo. GPU 1 = gen-small (moved from
GPU 0, 5.5 GiB, 1.76x), meromero-rp (22 GiB, 1.32x), intern-decision.

Sizing rule: KV >= 1.25x max context rounded up to 0.5 GiB, checked against
7 days of LiteLLM traffic and the engines' own KV-usage logs. Each card keeps
spare memory for its bursty tenant (parakeet's cap on GPU 0, intern-decision's
32k call on GPU 1). YaRN extensions are not enabled: they do not fit, and the
Qwen cards warn static YaRN degrades short prompts.

gen-small gets --override-generation-config max_new_tokens 32768. It applies
only to requests that omit max_tokens (vLLM get_max_tokens) and answers 9
runaway ~260k-token replies in 7 days; the longest normal reply was 6,357.

Applied with playbooks/fv-ml1-rebalance-20261005.yaml (boot-check guard and
health/KV verification per seat); all nine seats healthy, gateway smoke
tests pass.
This commit is contained in:
vh
2026-10-05 22:51:17 -07:00
parent 6851ecbd0b
commit c35f6510bf
15 changed files with 319 additions and 25 deletions
Download Patch File Download Diff File Expand all files Collapse all files
stacks/erp-seat/.env.example
+4 -3
View File
@@ -4,12 +4,13 @@ ERP_MODEL=/tank/aimodels/G4-MeroMero-26B-A4B-it-uncensored-heretic-NVFP4A16
ERP_SERVED_NAME=G4-MeroMero-26B-A4B-it-uncensored-heretic-NVFP4A16
ERP_CHAT_TEMPLATE=/tank/aimodels/G4-MeroMero-26B-A4B-it-uncensored-heretic-NVFP4A16/chat_template.jinja
ERP_PORT=8021
ERP_GPU_ID=1
# 2026-10-05 rebalance: GPU 0, KV pinned 5.5 GiB (~346k tokens, 1.32x); util = boot check only.
ERP_GPU_ID=0
# 0.35 x 97.9 GiB = 34 GiB. GPU1 had ~47 GiB free on 2026-09-08 (scriberr/embed/rerank/coder/reward resident).
ERP_GPU_MEM_UTIL=0.30
ERP_GPU_MEM_UTIL=0.25
ERP_MAX_MODEL_LEN=262144
ERP_MAX_NUM_SEQS=32
API_KEY=
# 8.49 GiB -> 534,649 KV tokens -> 2.04x a 262,144 context (operator's KV = 2x rule).
ERP_KV_CACHE_MEMORY=9114000000
ERP_KV_CACHE_MEMORY=5905580032
ERP_MOE_BACKEND=auto
stacks/erp-seat/README.md
+2 -2
View File
@@ -1,4 +1,4 @@
# erp-seat — ERP-tune seat on ana-ml2 (GPU1, `:8021`)
# erp-seat — ERP-tune seat on fv-ml1 (ex ana-ml2; GPU0 since 2026-10-05, `:8021`)
Serves the latest gated ERP LoRA merge as an **NVFP4A16** (weight-only) compressed-tensors
checkpoint so the GX10 is free to train the next run.
@@ -38,7 +38,7 @@ flip plus `docker compose up -d`.*
json_schema` (guided decoding) 18/18 on this seat** — that is the deterministic path for a
forced call; `tool_choice: auto` works normally. A parser plugin that re-enables guided JSON
would also need JSON extraction in the engine-parser path; not attempted.
- **GPU1 is shared** — check real usage (`nvidia-smi --query-compute-apps=pid,used_memory`) before
- **GPU0 is shared** (since 2026-10-05: cyberprev, voices, coder, parakeet-nemo; KV pinned 5.5 GiB = 346,436 tokens, 1.32×) — check real usage (`nvidia-smi --query-compute-apps=pid,used_memory`) before
raising `ERP_GPU_MEM_UTIL`; the flag sizes KV, not CUDA context.
- **Rollback / next run:** point `ERP_MODEL` + `ERP_SERVED_NAME` at the next quant dir, keep the
previous on disk. Deploy with `scripts/deploy-stack.sh ana-ml2 erp-seat`.
stacks/erp-seat/compose.yaml
+1 -1
View File
@@ -151,7 +151,7 @@ services:
- homepage.group=AI - Inference
- homepage.name=char-rp-fast (MeroMero 26B-A4B, NVFP4A16 MoE)
- homepage.icon=mdi-fire
- homepage.description=MeroMero A4B abliterated RP seat, NVFP4A16 weight-only, vision intact (fv-ml1 GPU1)
- homepage.description=MeroMero A4B abliterated RP seat, NVFP4A16 weight-only, vision intact (fv-ml1 GPU0)
- homepage.href=http://10.251.50.54:${ERP_PORT:-8021}/docs
networks: