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arXiv · 1811.09271

Distributed Gradient Descent with Coded Partial Gradient Computations

Emre Ozfatura·Sennur Ulukus·Deniz Gunduz
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Abstract

Coded computation techniques provide robustness against straggling servers in distributed computing, with the following limitations: First, they increase decoding complexity. Second, they ignore computations carried out by straggling servers; and they are typically designed to recover the full gradient, and thus, cannot provide a balance between the accuracy of the gradient and per-iteration completion time. Here we introduce a hybrid approach, called coded partial gradient computation (CPGC), that benefits from the advantages of both coded and uncoded computation schemes, and reduces both the computation time and decoding complexity.

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BibTeXRIS

Emre Ozfatura, Sennur Ulukus, Deniz Gunduz. 2018-11-22. Distributed Gradient Descent with Coded Partial Gradient Computations. https://arxiv.org/abs/1811.09271

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