specific method · filed under inference & serving
Workload-aware routed-expert GEMM scheduling
A scheduler adapts routed-expert GEMM parameters to the current token distribution before launch and holds them fixed during execution.
Also called workload-aware scheduler.
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We therefore schedule the routed-expert GEMM with a workload-aware scheduler that adapts its parameters to the current token distribution before launch and keeps them fixed during execution.
coresoftware implementationin Kimi K3Moonshot AI
Filed alongside
Other methods under inference & serving :: inference scheduling.
Asynchronous schedulingNUMA binding of workers to GPU-local CPU socketsComposite-key sorting for topology-aware GPU rank assignmentContinuous batchingCross-group pinning of cache-hit blocksDual-cluster consistent-hash failover for cache affinityEnvoy-based proxy with custom orchestratorExacto routingGreedy feasible-rank placement by remaining capacityHost-side scheduling optimizationIncreasing batch size for inferenceLatency-sensitive execution class with priority isolationMax sequences tuningPer-node hard admission constraintPrefix-cache-aware session affinity schedulingRegistering NVLink domains as Ray custom resourcesRequest-class resource-budget admission controlRuntime-signal-based rollout concurrency auto-throttlingSub-NUMA partitioning with per-VM NUMA binding