基于组播时间扩展图的集合通信编排算法OA

Collective communication latency has become a major performance bottleneck in large-scale distributed train-ing.To address the limitations of existing algorithms in terms of insufficient topology awareness and high computational complexity,a topology-aware collective communication scheduling algorithm based on multicast time-expanded graph was proposed.By constructing a multicast time-varying graph model,both network topology constraints and time-slot conflict constraints were explicitly captured.The collective communication scheduling problem was then transformed into a multicast path search problem on the time-varying graph,enabling joint optimization of routing and time slot plan-ning.Simulation results demonstrate that the proposed algorithm achieves near-optimal communication completion time while significantly reducing computational complexity,making it suitable for large-scale distributed training scenarios.