STRADS: a distributed framework for scheduled model parallel machine learning

@inproceedings{Kim2016STRADSAD,
  title={STRADS: a distributed framework for scheduled model parallel machine learning},
  author={Jin Kyu Kim and Qirong Ho and Seunghak Lee and Xun Zheng and Wei Dai and Garth A. Gibson and Eric P. Xing},
  booktitle={EuroSys},
  year={2016}
}
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 access and updates, and may periodically repartition the parameters to facilitate communication. Model parallelism is motivated by two… CONTINUE READING
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