Story Crater Bot
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Layout on 4x Tesla V100 32GB (PCIe, no NVLink), all TP=1: GPU0+1 vLLM DeepSeek-R1-Distill-Qwen-32B bnb-nf4 (2 replicas) GPU2 Ollama ornith:35b + qwen2.5:3b-instruct (co-resident) GPU3 vLLM Qwen2.5-Math-PRM-7B (reward model) CPU TEI nomic-embed-text-v2-moe, bge-reranker-base Volta constraints, each verified against live output rather than config: - vLLM pinned v0.11.0: sm_70 dropped from CUDA_SUPPORTED_ARCHS at v0.11.1. - AWQ hard-rejected (needs sm_75). GPTQ passes vLLM's min_capability=60 gate but is NUMERICALLY WRONG on sm_70 — emits garbage logits. Proven by an fp16 control run producing correct text on an identical backend. bitsandbytes nf4 verified correct by output. - flashinfer's check_cuda_arch() crashes on any sm_7x (calls .isdigit() on an int) -> VLLM_USE_FLASHINFER_SAMPLER=0. - xformers has no sm_70 kernel for V1's paged-attention bias, and V0 was removed in v0.11.0 -> TRITON_ATTN. - Ornith is Qwen3.5-MoE hybrid-attention; vLLM added that arch after dropping Volta, so no build has both -> Ollama, which also multiplexes a second model on the same card for free. Cluster prereqs that were absent: - RuntimeClass nvidia: the Talos toolkit extension registers the containerd handler but not the k8s object; without it every pod is rejected at admission. - gpu-system pinned to privileged PSA: a device plugin cannot satisfy the cluster-default baseline, it must mount hostPath. - device-plugin affinity=null: the chart requires NFD labels that do not exist here, so it matched zero nodes and reported desiredNumberScheduled=0 silently. - Recreate strategy on GPU services: with GPUs allocated exactly 4/4, a RollingUpdate surge pod has no card and deadlocks the rollout. - longhorn-llm-local SC (1 replica, strict-local, disk tag llm): the default 3-replica class could not place the volume at all (every control-plane disk was at its over-provisioning ceiling), and this keeps ~60GB of weights on worker-1's own NVMe instead of reading them over the network. deploy-gpu-serving.sh sequences ArgoCD syncs (or helm/kubectl in --manual mode) and never applies a manifest absent from git; doctor/unstick/teardown stages exist so this is diagnosable without ad-hoc kubectl archaeology.
39 lines
1.7 KiB
YAML
39 lines
1.7 KiB
YAML
# Dedicated StorageClass for model weights on worker-1's local NVMe.
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#
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# Why not the default `longhorn` class (3 replicas, network-attached):
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#
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# 1. numberOfReplicas: 1 — model weights are re-downloadable from HuggingFace.
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# Replicating them 3x buys nothing; losing a replica costs a re-pull, not
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# data. The repo's "never delete a PVC without replicas/backups" rule exists
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# for irreplaceable data, which this is not.
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#
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# 2. dataLocality: strict-local — keeps the single replica on the SAME node as
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# the pod. All engines are pinned to worker-1, so weights are read from its
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# local 751GB NVMe instead of over the network from a control-plane node.
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# Removes ~60GB of network reads on every cold start.
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#
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# 3. diskSelector: llm — restricts this class to disks tagged `llm`, i.e. only
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# worker-1's disk. Equally important, worker-1's disk carries that tag so
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# UNTAGGED volumes (any ordinary cluster PVC) will not land on it. Before
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# tagging, worker-1 had been silently hosting a replica of cicd/runner-dind,
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# consuming GPU-node storage for general cluster workloads.
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#
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# The default 3-replica class also physically could not place this volume: all
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# three control-plane disks were already at their over-provisioning ceiling
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# (storage-over-provisioning-percentage=100, 30% reserved), so a 120Gi x3
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# request failed with ReplicaSchedulingFailure on every node.
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apiVersion: storage.k8s.io/v1
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kind: StorageClass
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metadata:
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name: longhorn-llm-local
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provisioner: driver.longhorn.io
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allowVolumeExpansion: true
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reclaimPolicy: Delete
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volumeBindingMode: Immediate
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parameters:
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numberOfReplicas: "1"
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dataLocality: "strict-local"
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diskSelector: "llm"
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staleReplicaTimeout: "30"
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fsType: "ext4"
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