feat: Add scheduler scoringStrategy Helm value for GPU spread - #449
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Expose scheduler.scoringStrategy in chart values so the NodeResourcesFit GPU scoring can switch from bin-pack (RequestedToCapacityRatio, default) to spread (LeastAllocated) without a code change. Default preserves current behavior.
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July 9, 2026 13:48
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Tested in a two node MI350X cluster (further testing will be done later when more nodes available):
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salexo
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Thanks! Looks good, just one change request, we could try to fail fast on unknown values, for example
{{- $strategy := .Values.scheduler.scoringStrategy }}
{{- if not (or (eq $strategy "RequestedToCapacityRatio") (eq $strategy "LeastAllocated")) }}
{{- fail (printf "scheduler.scoringStrategy must be RequestedToCapacityRatio or LeastAllocated, got %q" $strategy) }}
{{- end }}
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@salexo how about now? |
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July 10, 2026 11:36
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Summary
scheduler.scoringStrategyin the operator chart values so theNodeResourcesFitGPU scoring can switch between bin-pack and spread without a code change.RequestedToCapacityRatio(bin-pack), which reproduces current behavior exactly. Set toLeastAllocatedto spread GPU workloads across nodes.config/static/scheduler/*is left untouched (non-Helm default stays bin-pack).Why
For the AMD Advancing AI demo on MI350X nodes we want GPU workloads spread across nodes rather than bin-packed next to each other (heat/locality). This adds a values toggle so deployments (e.g. via GitOps values override) can pick the spread strategy without waiting on a code change.
Implementation
chart/templates/scheduler.yamlincludes the rawscheduler-resources.yamlConfigMap via.Files.Get. Whenscheduler.scoringStrategy=LeastAllocated, the template rewrites theRequestedToCapacityRatioblock toLeastAllocated(same GPU resource weights). Uses backtick raw strings for readability.Test plan
helm template .renders bin-pack by default (identical to current main)helm template . --set scheduler.scoringStrategy=LeastAllocatedrenderstype: LeastAllocatedkaiwo-scheduler-configConfigMap reflects the selected strategy (kube-scheduler needs a rollout restart, no hot-reload)Note: this is node-level spread only. Intra-node GPU/PCIe placement is out of scope (would need the DRA driver).
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