Motivated by the increasing shift to multicore computers, recent work has developed language support for responsive parallel applications that mix compute-intensive tasks with latency-sensitive, usually interactive, tasks. These developments include calculi that allow assigning priorities to threads, type systems that can rule out priority inversions, and accompanying cost models for predicting responsiveness. These advances share one important limitation: all of this work assumes purely functional programming. This is a significant restriction, because many realistic interactive applications, from games to robots to web servers, use mutable state, e.g., for communication between threads.

Many modern parallel applications, such as desktop software and cloud-based web services, are service-oriented, long running, and perform frequent interactions with the external world (e.g., responding to user input). We want such interactive applications to provide fast response times because typically at the other end of the external interaction there is a user waiting for a response. Existing parallel platforms designed for multicore hardware do not work well for such interactive applications, because they are designed to maximize throughput (rather than responsiveness). Interactive applications may have a mixture of interactive and compute-intensive tasks occurring concurrently, and the scheduler must be able to discern and prioritize tasks so that tasks which require faster response are prioritized over background tasks.