Efficient Algorithms for All-to-All Communications in Multiport Message-Passing Systems
By Jehoshua Bruck, C. T. Ho, Shlomo Kipnis, Eli Upfal, Derrick Weathersby. 1997
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Citations in the corpus
- Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training (2017, methodology): “With the all-reduce communication model [31, 32], the density of sparse data doubles at every aggregation step in the worst case.”
- Performance analysis of MPI collective operations (2005, methodology): “Bruck algorithm requires log 2 P communication steps.”
- Optimization of Collective Communication Operations in MPICH (2005, methodology): “2 Bruck Algorithm The Bruck algorithm for allgather [7] (referred to as concatenation) is a variant of the dissemination algorithm for barrier, described in [10].”
- Optimization of Collective Reduction Operations (2004, methodology): “Collective algorithms for wide-area cluster are developed in [5,7,8], further protocol tuning can be found in [3, 4 ,9,12], and automatic tuning in [13].”
- Tutel: Adaptive Mixture-of-Experts at Scale (2022, methodology): “3Message Passing Interface (MPI) [41] also has developed various Allto-All algorithms [5, 35, 42], but we only discuss NCCL in this work as it outperforms MPI in most DL scenarios.”
- A Unified Coded Deep Neural Network Training Strategy based on Generalized PolyDot codes (2018, methodology): “Using efficient all-to-all communication protocols [76], [78] popular in parallel computing, the communication cost of all nodes broadcasting its own sub-vector s̃p of length N m to all other nodes has a communication cost of α logP + 2β N m P = Θ( m P ) using All-Gather protocol.”
- The analysis of a plane wave pseudopotential density functional theory code on a GPU machine (2013, methodology): “In OpenMPI and othermajorMPI implementations, pairwise is commonly used for large message all-to-all communication, while some other algorithms such as the Bruck algorithm [22] should be used for short messages.”