Kay Ousterhout, PhD

Fellowship Awarded 2011
Kay Ousterhout
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Kay Ousterhout, PhD, is interested in the performance of large-scale distributed systems. She is a co-founder of Quilt, a startup that seeks to make it easy to deploy and run software on cloud infrastructure, and a committer for the Apache Spark project.

With the support of a Hertz Foundation Fellowship, Kay completed her PhD from UC Berkeley in 2017. Kay’s PhD research focused on enabling users to reason about performance bottlenecks in large-scale data analytics frameworks. She developed blocked time analysis, a methodology for quantifying performance bottlenecks in parallelized systems, and used blocked time analysis to illustrate that network and disk I/O are not as important to performance as previously believed. Given the challenges to reasoning about performance in current architectures, she explored a new architecture built specifically to provide performance clarity: the ability to understand where bottlenecks lie and the performance implications of various system changes. She demonstrated that structuring jobs as single-resource units of work called monotasks makes it simple to reason about performance without sacrificing fast runtimes.

Kay graduated from Princeton University in 2011 with a BSE in computer science. At Princeton, Kay was advised by Jennifer Rexford and Michael J. Freedman.

Graduate Studies

University of California, Berkeley
Computer Science
Architecting for Performance Clarity in Data Analytics Frameworks