High Performance Spectral Simulation of Turbulent Flows in Massively Parallel Machines With Distributed Memory

Here we have demonstrated the possibility of very high performance in the implementation of a global spectral methodology on a massively parallel architec ture with distributed memory. Spectral simulations of channel flow and thermal convection in a three-dimen sional Cartesian geometry have yielded a very high performance—up to 26 Gflops/s on a 512-node CM5. In general, implementation of spectral methodology in parallel processors with distributed memory requires nonlocal interprocessor data transfer that is not re stricted to being between nearest neighbors. In spite of their increased communication overhead, better per formance is possible in global methodologies owing to their dense matrix operations and organized data com munication. In this paper we outline a general method ology for the data-parallel implementation of spectral methods on massively parallel machines with distrib uted memory. Following the steps presented here, very high performance can be obtained on a wide vari ety of massively parallel architectures.