Fine-grain synchronization in data-parallel jobs for distributed machine learning

摘要

A computer-implemented method and computer processing system are provided. The method includes synchronizing, by a processor, respective ones of a plurality of data parallel workers with respect to an iterative distributed machine learning process. The synchronizing step includes individually continuing, by the respective ones of the plurality of data parallel workers, from a current iteration to a subsequent iteration of the iterative distributed machine learning process, responsive to a satisfaction of a predetermined condition thereby. The predetermined condition includes individually sending a per-receiver notification from each sending one of the plurality of data parallel workers to each receiving one of the plurality of data parallel workers, responsive to a sending of data there between. The predetermined condition further includes individually sending a per-receiver acknowledgement from the receiving one to the sending one, responsive to a consumption of the data thereby.