The implementation of a general purpose FORTRAN harness for an arbitrary network of transputers for computational fluid dynamics

Many Computational Fluid Dynamics (CFD) problems of interest require far greater computational power than is available on any sequential machine. In CFD problems, where a large number of similar operations are performed, a parallel machine can be utilised to exploit the inherent parallelism of the algorithm. Distributed memory machines, although requiring extra programming, can provide truly scalable performance, at a fraction of the cost of current vector supercomputers. At the University of Hertfordshire part of the current work programme involves the parallel implementation of a sequential 2-D Navier-Stokes multiblock aerofoil code. In order to utilise an arbitrary network of transputers, it is necessary to have software which can effect the communication of data between processors and also schedule this data for processing. This paper is concerned with the development and implementation of a general purpose FORTRAN harness for a distributed memory machine with an arbitrary number of processors and hardware configuration. The general purpose harness therefore will not confine its use to the CFD work, but to any problem where a large number of similar operations is performed. The harness, which comprises many concurrently executing processes, is replicated to all the transputers in the network. The data is sorted into order and distributed to the network, so that as nearly as possible each transputer is responsible for performing the same amount of work. This will ensure that the Transactions on Information and Communications Technologies vol 3, © 1993 WIT Press, www.witpress.com, ISSN 1743-3517 224 Applications of Supercomputers in Engineering distribution of computational load is even, thereby preventing the one with the most work from holding up the others. To illustrate the design and performance of the harness a simple five-point solution to the potential problem is considered in this paper.