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Bine Trees: Enhancing Collective Operations by Optimizing Communication Locality
Daniele De Sensi, Saverio Pasqualoni, Lorenzo Piarulli, Tommaso Bonato, Seydou Ba, Matteo Turisini, Jens Domke, Torsten Hoefler
Abstract
Communication locality plays a key role in the performance of collective operations on large HPC systems, especially on oversubscribed networks where groups of nodes are fully connected internally but sparsely linked through global connections. We present Bine (binomial negabinary) trees, a family of collective algorithms that improve communication locality. Bine trees maintain the generality of binomial trees and butterflies while cutting global-link traffic by up to . We implement eight Bine-based collectives and evaluate them on four large-scale supercomputers with Dragonfly, Dragonfly+, oversubscribed fat-tree, and torus topologies, achieving up to 5 × speedups and consistent reductions in global-link traffic across different vector sizes and node counts.
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- TACOS: Topology-Aware Collective Algorithm Synthesizer for Distributed Machine LearningWilliam Won, Midhilesh Elavazhagan, Sudarshan Srinivasan, Swati Gupta et al.MICRO 2024 · 36 citations
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