Duration: 1:00:21

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A key challenge in scaling network control and data planes is to maintain access to shared state without comprimising performance. In this talk, I present Tasvir, a versioned distributed shared memory system, that achieves this goal by carrying out periodic bulk data-oriented synchornization and decoupling heavyweight synchronization from the fastpath. I describe Tasvir's design, performance benefits, and make a case for its general applicability to networks through a set of sample applications we built. I conclude by discussing our ongoing work on using Tasvir to handle distributed state management for key-value stores and distributed machine learning.

See more at https://www.microsoft.com/en-us/research/video/rethinking-distr…ment-in-networks/