PIPES: a language and compiler for task-based programming on distributed-memory clusters

Applications running on clusters of shared-memory computers are often implemented using OpenMP+MPI. Productivity can be vastly improved using task-based programming, a paradigm where the user expresses the data and control-flow relations between tasks, offering the runtime maximal freedom to place and schedule tasks. While productivity is increased, high-performance execution remains challenging: the implementation of parallel algorithms typically requires specific task placement and communication strategies to reduce internode communications and exploit data locality.