Competitive parallelism: getting your priorities right

Abstract

Multi-threaded programs have traditionally fallen into one of two domains: cooperative and competitive. These two domains have traditionally remained mostly disjoint, with cooperative threading used for increasing throughput in compute-intensive applications such as scientific workloads and cooperative threading used for increasing responsiveness in interactive applications such as GUIs and games. As multicore hardware becomes increasingly mainstream, there is a need for bridging these two disjoint worlds, because many applications mix interaction and computation and would benefit from both cooperative and competitive threading.In this paper, we present techniques for programming and reasoning about parallel interactive applications that can use both cooperative and competitive threading. Our techniques enable the programmer to write rich parallel interactive programs by creating and synchronizing with threads as needed, and by assigning threads user-defined and partially ordered priorities. To ensure important responsiveness properties, we present a modal type system analogous to S4 modal logic that precludes low-priority threads from delaying high-priority threads, thereby statically preventing a crucial set of priority-inversion bugs. We then present a cost model that allows reasoning about responsiveness and completion time of well-typed programs. The cost model extends the traditional work-span model for cooperative threading to account for competitive scheduling decisions needed to ensure responsiveness. Finally, we show that our proposed techniques are realistic by implementing them as an extension to the Standard ML language.

Fairness in responsive parallelism

“…This model is sufficient to encode many threading models, such as fork-join, async-finish and futures, which are used in real-world parallelism libraries. In particular, the formal model and scheduling algorithm presented in this paper could be considered a blueprint for extending the PriML language [Muller et al 2018] with fairness. In PriML, programs are parallelized using a threading construct similar to futures.…”

“…processor instructions) and edges represent dependences between operations. Our model and related notations are built on those of Muller et al [2018], which we now briefly review.…”

“…Probably the most famous such result is Brent's Theorem [Brent 1974] which gives a schedule that is 2-optimal for standard DAGs without priorities or responsiveness requirements. Muller et al [2017Muller et al [ , 2018 proposed the prompt scheduling principle, which extends classic ideas like Brent's to prioritized DAGs. A prompt schedule is one that does not execute a thread if there is a higher-priority thread that is ready and not already being executed.…”

“…For example, a game might perform compute-intensive tasks to implement visual effects while it also interacts with the user. Recent work by Muller et al [2017Muller et al [ , 2018 has developed programminglanguage theory for such interactive parallel applications by considering languages that combine interaction and parallelism, and by allowing parallel tasks to have different priorities. Their work allows, for example, a parallel compute-intensive task to run in the łbackgroundž concurrently with a high-priority interactive task.…”

“…The prior work on responsive parallelism [Muller et al 2017[Muller et al , 2018 shows that it is theoretically possible to achieve both responsiveness and throughput. In this paper, we build on that work to account for fairness while maintaining provable guarantees on response time by presenting fairly prompt scheduling.…”