Session starts - 17:30

Stale Synchronous Parallel Iterations on Flink

While Bulk Synchronous Parallel is a model suitable for distributed bulk iterations, it has the overhead of synchronizing each worker with a fresh view of the working set between each iteration. It has however been shown that algorithms still converge when distributed workers hold an outdated or inconsistent view of the solution between iterations within defined bounds. This has led to the concept of Stale Synchronous Parallel iterations, in which workers work on cached model data from other workers covering previous iterations within defined bounds. This introduces two new notions: first the “clock” representing the smallest amount of work performed by a worker in an iteration, and second the “slack”, defining the maximum amount of clocks a worker can be ahead of the slowest.

In this project we implement the SSP iteration model on top of Flink iterations and introduce an important element of the model: the parameter server. We will present our contribution at the model level, our implementation within Flink using Apache Ignite and show the use cases benefitting from this iteration model.

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About the speaker

Nam-Luc Tran

Since joining EURA NOVA as a R&D researcher, Nam-Luc has published numerous times in the fields of big data and distributed computing, including storage, modeling and processing, with collaborations among the top Belgian universities (ULB, UCL, ULg).

EURA NOVA is a private company located in Belgium focused on solving industrial challenges with the most advanced technical innovations.



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