Performance of distributed memory methods in multiprocessing clusters

The availability of multiprocessing workstations offers the opportunity to simultaneously apply both shared and distributed memory parallel processing techniques to a single application. It has been assumed that using the data sharing formalisms native to the specific machine would yield performance superior to those obtained with a more general message passing system. We compared the performance of pure message passing methods with a combination of message passing and shared memory data sharing techniques and found that the benefit of the added complexity of dual level programming is negligible or non-existent