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Coded Distributed Computing with Pre-set Assignments of Data and Output Functions

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arxiv 2201.06300 v3 pith:LOAWLBHM submitted 2022-01-17 cs.IT cs.DCmath.IT

classification cs.ITcs.DCmath.IT
keywords codedtransmissioncomputingdatadistributedschemesfsctnodes
verification ladder T0 review T1 audit T2 compute T3 formal
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Coded distributed computing can reduce the communication load for distributed computing systems by introducing redundant computation and creating multicasting opportunities. However, the existing schemes require delicate data placement and output function assignment, which is not feasible when distributed nodes fetch data without the orchestration of a master node. In this paper, we consider the general systems where the data placement and output function assignment are arbitrary but pre-set. We propose two coded computing schemes, One-shot Coded Transmission (OSCT) and Few-shot Coded Transmission (FSCT), to reduce the communication load. Both schemes first group the nodes into clusters and divide the transmission of each cluster into multiple rounds, and then design coded transmission in each round to maximize the multicast gain. The key difference between OSCT and FSCT is that the former uses a one-shot transmission where each encoded message can be decoded independently by the intended nodes, while the latter allows each node to jointly decode multiple received symbols to achieve potentially larger multicast gains. Furthermore, based on the lower bound proposed by Yu et al., we derive sufficient conditions for the optimality of OSCT and FSCT, respectively. This not only recovers the existing optimality results but also includes some cases where our schemes are optimal while others are not.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. A Novel Coded Computing Approach for Distributed Multi-Task Learning

    cs.IT 2025-07 reject novelty 6.0 of 10

    A coded multi-task learning scheme is claimed to achieve optimal communication loads under a mild data-placement condition, but the optimality proof applies a lower bound that is invalid for the general number of data...

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