Abstract

It is increasingly important for parallel applications to run together on the same machine. However, current performance is often poor: programs do not adapt well to dynamically varying numbers of cores, and the CPU time received by concurrent jobs can differ drastically.

During an internship with Tim Harris at Oracle Labs, Cambridge, we developed Callisto, a resource management layer for parallel runtime systems. In this talk, we describe Callisto and the implementation of two Callisto-enabled runtime systems — one for OpenMP, and another for a task-parallel programming model. We show how Callisto eliminates almost all of the scheduler-related interference between concurrent jobs, while still allowing jobs to claim otherwise-idle cores. We use examples from two recent graph analytics projects and from SPEC OMP .

Bio: Martin Maas is a third-year PhD student at UC Berkeley, working with Krste Asanović and John Kubiatowicz. His research interests include managed languages, computer architecture and operating systems. Before coming to Berkeley, Martin received his undergraduate degree from the University of Cambridge.