Data-parallel programming on a network of heterogeneous workstations

Abstract

The authors describe a compiler and run-time system that allows data-parallel programs to execute on a network of heterogeneous UNIX workstations. The programming language supported is Dataparallel C, a SIMD language with virtual processors and a global name space. This parallel programming environment allows the user to take advantage of the power of multiple workstations without adding any message-passing calls to the source program. Because the performance of individual workstations in a multi-user environment may change during the execution of a Dataparallel C program, the run-time system automatically performs dynamic load balancing. The authors present experimental results that demonstrate the usefulness of dynamic load balancing in a multi-user environment.