Abstract

Emerging networking architectures are allowing for flexible and reconfigurable packet processing at line rate both on the switch and the NIC . Despite their promising new functionality, programmable switches and NICs are not all-powerful; they have limited state, support limited types of operations, and limit per-packet computation to operate at line rate. In this talk, I will describe how to mask resource limitations using approximation techniques and new scheduling algorithms and how to build a general framework for exposing in-network computing capability to distributed applications. In addition to presenting case studies of optimizing networked systems, I will reflect on the role of programmable dataplanes in datacenter computing.

Bio: Arvind Krishnamurthy is the Short-Dooley Professor in the Paul G. Allen School of Computer Science & Engineering. His research interests span various aspects of building effective and robust computer systems, in the context of both data centers and Internet-scale systems. More recently, his research has focussed on programmable networks and systems for machine learning. He is an ACM fellow, a past program chair of ACM SIGCOMM and Usenix NSDI and serves on their technical steering committees, is the Vice President of Usenix, and serves on the ICSI and CRA boards.