DATA-PARALLEL PROGRAMMING ON A NETWORK OF HETEROGENEOUS WORKSTATIONS

We describe a compiler and run-time system that allow 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 or 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. We present experimental results that demonstrate the usefulness of dynamic load-balancing in a multi-user environment. These results suggest that initially allocating the same amount of work to each processor and letting the dynamic load balancing algorithm adjust the load during program execution yields very good performance. Hence neither the compiler nor the run-time system need a priori knowledge of the speeds or the machines that will participate in a program execution.