Topology-Aware Scheduling
A scheduling strategy that accounts for the physical topology of underlying hardware. By understanding GPU interconnect hierarchies (intra-node, inter-node, and cross-rack), it assigns communication-intensive tasks to physically proximate hardware, reducing communication overhead and improving cluster throughput efficiency.
Timeline (last 90 days)
The core of topology-aware scheduling is enabling the scheduling system to understand the physical connection hierarchy between GPUs, so that tasks with intensive communication can be consolidated onto hardware that is physically closer, reducing cross-domain traffic.
In topology-aware scheduling practice, GPUs in a tensor-parallel group should be preferentially placed within the same node, pipeline stages can span nodes but should ideally be on the same rack, and data-parallel replicas can be distributed flexibly.
All Facts (2)
The core of topology-aware scheduling is enabling the scheduling system to understand the physical connection hierarchy between GPUs, so that tasks with intensive communication can be consolidated onto hardware that is physically closer, reducing cross-domain traffic.
50%UnverifiedIn topology-aware scheduling practice, GPUs in a tensor-parallel group should be preferentially placed within the same node, pipeline stages can span nodes but should ideally be on the same rack, and data-parallel replicas can be distributed flexibly.
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