A computer-implemented method for distributed synchronous training of a neural network model includes detecting gradient sets from a plurality of worker machines, each worker machine generating a gradient set in a current iteration of a training data set, and each gradient set of the gradient sets comprising a plurality of gradients. A lagging gradient set from a lagging worker machine is detected. The lagging gradient set is generated by the lagging worker machine in a prior iteration of the training data set. Aggregated gradients are generated based on the gradient sets and the lagging gradient set. The neural network model is updated based on the aggregated gradients.
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