It is argued that the choice between the shared-memory and message-passing models depends on two factors: the relative cost of communication and computation as implemented by the hardware, and the degree of load imbalance inherent in the application. Two representative applications are used to illustrate the performance advantages of each programming model on several different shared-memory machines, including the BBN Butterfly, Sequent Symmetry, Encore Multimax and Silicon Graphics Iris multiprocessors. It is shown that applications implemented in the shared-memory model perform better on the previous generation of multiprocessors, while applications implemented in the message-passing model perform better on modern multiprocessors. It is argued that both models have performance advantages, and that the factors that influence the choice of model may not be known at compile-time. As a compromise solution, the authors propose an alternative programming model, which has the load balancing properties of the shared-memory model and the locality properties of the message-passing model, and show that this new model performs better than the other two alternatives.
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