A Multi - Threaded Implementation of

Data-Parallelism Dean Engelhardt and Andrew Wendelborn Department of Computer Science University of Adelaide Adelaide, SA 5005, Australia. E-mail: fdean,[email protected] Abstract In previous work, we have proposed a multithreaded execution model for describing nested data-parallelism on distributed multiprocessors in a fashion generic upon the partitioning of data aggregates within the system. This paper demonstrates an approach which uses this abstract model as the basis for a runtime system for a data-parallel functional language. We describe an active message based implementation of the model on the Thinking Machines CM-5 and also consider various issues related to e cient compilation targetting such a platform. Several issues central to the performance of the model are addressed. A hybrid scheme for thread synchronization and data ow is presented which incorporates a highly e cient mode of matching and one permitting the most general forms of interaction. We also describe a generic thread library of data-parallel primitive operations which operate independently of data partitioning. Finally, we detail work undertaken to instrument our execution environment for visualization and tracing.