Parallel adaptive full-multigrid methods on message-based multiprocessors

This paper explores the macro data flow approach for solving numerical applications on distributed memory systems. We discuss the problems of this approach with a sophisticated ‘real life’ algorithm—the adaptive full multigrid method.

It is shown that the nonnumeric parts of the algorithm—the initialization, the termination and the mapping of processes to processors—are very important for the overall performance.

To avoid unnecessary global synchronization points we propose to use the distributed supervisors. We compare this solution with more centralized algorithms. The performance evaluation is done for nearest neighbour and bus connected multiprocessors using a simulation systems.