Parallel and Distributed Computational Fluid Dynamics: Experimental Results and Challenges
This paper describes several results of parallel and distributed computing using a production flow solver program. A coarse grained parallelization based on clustering of discretization grids, combined with partitioning of large grids, for load balancing is presented. An assessment is given of its performance on tightly-coupled distributed and distributed-shared memory platforms using large-scale scientific problems. An experiment with this solver, adapted to a Wide Area Network environment, is also presented.