Ring All-Reduce Explainer
Ring all-reduce is an algorithm for performing all-reduce across a group of workers arranged in a logical ring. Each worker sends data to one neighbor and receives data from the other in a sequence of coordinated steps.
The data is divided into chunks. During reduce-scatter, chunks circulate and are combined so each worker ends with one reduced chunk. During all-gather, those reduced chunks circulate again until every worker holds the complete result.
For large messages, the ring can use available links efficiently because every worker sends and receives continuously and no central parameter server must handle all traffic. It became widely used in data-parallel deep learning.
The algorithm requires multiple sequential communication steps, so latency can hurt small messages or very large rings. One slow or failed link affects the cycle. Hierarchical or topology-aware variants may work better across nodes, switches, and data centers.
Ring all-reduce arranges workers in a logical circle and circulates data chunks so reduction and redistribution use network bandwidth efficiently.
Key terms include ring all-reduce, worker, chunk, reduce-scatter, all-gather, neighbor, bandwidth, latency and topology.
Reduce-scatter combines circulating chunks until each worker owns one reduced piece.
All-gather circulates those pieces again so every worker reconstructs the full aggregate.
Large transfers can keep every link busy, but each ring stage adds latency.
Physical network topology and slow participants determine whether the logical ring performs well.
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