List Scheduling Strategies for Task Graphs with Data Parallelism

This paper studies task scheduling algorithms which schedule a set of tasks on multiple cores so that the total scheduling length is minimized. Most of the algorithms developed in the past assume that a task is executed on a single core. Unlike the previous algorithms, the algorithms studied in this paper allow a task to be executed on multiple cores. This paper proposes six algorithms. All of the six algorithms are based on list scheduling, but the strategy for priority assignment is different. In our experiments, the six algorithms as well as an integer linear programming method are evaluated.