STRADS: a distributed framework for scheduled model parallel machine learning

Abstract

Machine learning (ML) algorithms are commonly applied to big data, using distributed systems that partition the data across machines and allow each machine to read and update all ML model parameters --- a strategy known as data parallelism. An alternative and complimentary strategy, model parallelism, partitions the model parameters for non-shared parallel… (More)
DOI: 10.1145/2901318.2901331

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Citation Velocity: 19

Averaging 19 citations per year over the last 2 years.

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