specific method · filed under optimization
Job-level eviction and reclaim
Making capacity decisions and reclaiming resources at job granularity rather than node granularity.
Also called Per-job eviction and reclaim.
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How sources treat it
One count per evidence span, weakest treatment to strongest.
used 1
Documented in
Evidence
1 span quoted from the sources, strongest treatment first.
Capacity decisions are made at the granularity of jobs, not nodes.
usedsoftware implementationin Model FactoryPoolside
Filed alongside
Other methods under optimization :: training runtime.
Offline checkpoint mergingAsynchronous checkpointingAsymmetric local-read and single-writer cache pathsAutotune configuration generationBatch-level embedding prefetchCaching the distributed checkpoint save planComposable activation storage policiesCPU-resident optimizer statesCross-rank remote activation offloadingDouble-buffered chunked streaming of reference-model weightsElement-wise activation recomputationGPU-to-GPU weight synchronization over GPUDirect RDMAHeartbeat-driven fault toleranceIn-flight recovery systemIn-flight weight updatesMinimal recomputation-graph extraction by backward traversalOverlapping NCCL transfers with device-to-host copiesPersistent checkpoint worker processesPersistent shared-storage cache for compiled artifactsPolicy-model gradient-buffer reuse for reference-model weightsPost-iteration NVMe offloading of training statesPre-admission hardware stress testingSame-node sticky pod respawnSeeding node-local storage from a warm shared cache