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

Distributed Gradient Descent with Coded Partial Gradient Computations