Exploiting Multicast for Accelerating Collective Communication

2026-05-21

AI Summary

This work addresses the network congestion and high latency in large model training and inference caused by redundant unicast transmissions in many-to-many collective communications such as AllGather and AlltoAll. To this end, the authors propose MultiWrite, a novel many-to-many transport semantic tailored for AI workloads. MultiWrite introduces a lightweight adaptation of multicast principles to collective communication, avoiding the management overhead and compatibility issues of traditional multicast while significantly reducing communication costs through hardware-aware multicast scheduling and redundancy elimination. A prototype implementation on Ascend NPUs demonstrates up to 33% reduction in collective communication latency on commercial hardware, with long-term stress tests confirming its stability and effectiveness.

Abstract

Reducing collective communication latency is a critical goal for large model training and inference in both academia and industry. Many-to-many communications, such as AllGather and AlltoAll (dispatch), are core components of modern parallelization strategies. State-of-the-art implementations of these communications rely on unicast-based writes and transmit duplicate copies of the same data across physical links for multiple receivers. This redundant transmission congests network bottlenecks and degrades end-to-end latency. We present MultiWrite, a novel many-to-many transmission semantic that eliminates redundant packets to directly reduce operator latency. MultiWrite adopts multicast principles while addressing critical limitations of traditional multicast for AI workloads. These limitations include heavy management plane overhead and ecosystem compatibility issues. We implement MultiWrite on Ascend NPUs. Long-term stress tests demonstrate that our MultiWrite-based operators achieve up to 33% latency reduction on commercially deployed devices.

Problem

• collective communication
• multicast
• latency reduction
• AllGather
• AlltoAll

Innovation

• MultiWrite
• multicast
• collective communication
• AllGather
• AlltoAll