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Zeno++: Robust Fully Asynchronous SGD

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arxiv 1903.07020 v5 pith:VD765KHZ submitted 2019-03-17 cs.LG cs.DCstat.ML

classification cs.LGcs.DCstat.ML
keywords zenoasynchronousbyzantinedescentworkersfailuresfullygradient
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We propose Zeno++, a new robust asynchronous Stochastic Gradient Descent~(SGD) procedure which tolerates Byzantine failures of the workers. In contrast to previous work, Zeno++ removes some unrealistic restrictions on worker-server communications, allowing for fully asynchronous updates from anonymous workers, arbitrarily stale worker updates, and the possibility of an unbounded number of Byzantine workers. The key idea is to estimate the descent of the loss value after the candidate gradient is applied, where large descent values indicate that the update results in optimization progress. We prove the convergence of Zeno++ for non-convex problems under Byzantine failures. Experimental results show that Zeno++ outperforms existing approaches.

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