Interference-Aware Scheduling

Overlapping communication with computation is a wellknown technique to increase application performance. While it is commonly assumed that communication and computation can be overlapped at no cost, in reality they interfere with each other. In this paper we empirically evaluate the interference rate of communication on computation via measurements on a single processor communicating on a heterogeneous collection of local and remote processors, in both Java and C. We then present a model of interference, which can be used for more effective application scheduling, as demonstrated by real-world experiments.