CS Colloquium - Malte Schwarzkopf (MIT CSAIL)

Event time: 
Monday, February 25, 2019 - 4:00pm
Location: 
AKW 200 See map
51 Prospect Street
New Haven, CT 06511
Event description: 

CS Colloquium - Malte Schwarzkopf, MIT CSAIL

Refreshments available at 3:45

Hosts: Zhong Shao and Ruzica Piskac

Title: Better Abstractions for High-Performance Datacenter Applications

Abstract:

Developing high-performance datacenter applications is complex and time-consuming today, as developers must understand and correctly implement subtle interactions between different backend systems. I describe a new approach that redesigns core datacenter systems around new abstractions: the right abstractions substantially reduce complexity while maintaining the same performance. This saves expensive developer time, uses the datacenter’s servers more efficiently, and can enable new, previously impossible systems and applications.

I illustrate the impact of such redesigns with Noria, which recasts web application backends—i.e., databases and caches—as a streaming dataflow computation based on a new abstraction of partial state. Noria’s partially-stateful dataflow brings classic databases’ familiar query flexibility to scalable dataflow systems, simplifying applications and improving the backend’s efficiency. For example, Noria increases the request load handled by a single server by 5–70 compared to state-of-the-art backends. Additional new abstractions from my research increase the efficiency of other datacenter systems (e.g., cluster schedulers), or enable new kinds of systems that, for example, may help protect user data against exposure through application bugs.

Bio:

Malte Schwarzkopf is a postdoc at MIT CSAIL, where he is a member of the Parallel and Distributed Operating Systems (PDOS) group. In his research, Malte designs and builds systems that aim to be both efficient and easy to use, and some of these systems have already impacted industry practice. Malte received both his B.A. and Ph.D. from the University of Cambridge, and his research has won an NSDI Best Paper Award and a EuroSys Best Student Paper Award.