New architectures: Performance highlights and new algorithms

Parallel computers are having a profound impact on computational science. Recently highly parallel machines have taken the lead as the fastest supercomputers, a trend that is likely to accelerate in the future. We describe some of these new computers, and issues involved in using them. We present elliptic PDE solutions currently running at 3.8 gigaflops, and an atmospheric dynamics model running at 1.7 gigaflops, on a 65 536-processor computer.

One intrinsic disadvantage of a parallel machine is the need to perform inter-processor communication. It is important to ensure that such communication time is maintained at a small fraction of computation time. We analyze standard multigrid algorithms in two and three dimensions from this point of view, indicating that performance efficiencies in excess of 95% are attainable under suitable conditions on moderately parallel machines. We also demonstrate that such performance is not attainable for multigrid on massively parallel computers, as indicated by an example of poor multigrid efficiency on 65 536 processors. The fundamental difficulty is the inability to keep 65 536 processors busy when operating on very coarse grids.

Most algorithms used for implementing applications on parallel machines have been derived directly from algorithms designed for serial machines. The previously mentioned multigrid example indicates that such ‘parallelized’ algorithms may not always be optimal. Parallel machines open the possibility of finding totally new approaches to solving standard tasks—intrinsically parallel algorithms. In particular, we present a class of superconvergent multiple scale methods that were motivated directly by massevely parallel machines. These methods differ from standard multigrid methods in an intrinsic way, and allow all processors to be used at all times, even when processing on the coarsest grid levels. Their serial versions are not sensible algorithms. The idea that parallel hardware—the Connection Machine in this case—can lead to discovery of new mathematical algorithms was surprising for us.