Rethinking Distributed State Management in Networks

  • Amin Tootoonchian | Intel Labs, UC Berkeley

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.

Speaker Details

Amin Tootoonchian is a research scientist at Intel Labs and researcher-in-residence at UC Berkeley. He received his PhD and MSc from the University of Toronto, and BSc from Sharif University of Technology. He is broadly interested in understanding and building networked systems and has worked on scalability and performance issues in Software-Defined Networking and Network Function Virtualization.

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