Evaluation of the asynchronous iterative algorithms in the context of distant heterogeneous clusters

The subject of this paper is to show the high efficiency of asynchronism for parallel iterative algorithms in the context of grid computing, that is to say, with machines scattered on a broad geographical scale. The question is: does asynchronism help to reduce the communication penalty and the overall computation time of such a given algorithm? The asynchronous programming model is evaluated on two test problems representing two important classes of scientific applications: a stationary linear problem and a non-stationary non-linear problem. They are implemented with a multi-threaded environment and tested on a set of distant heterogeneous machines. Several experiments have been performed allowing us to compare the performances of such asynchronous algorithms and also to analyze their behavior and extract the main possible optimizations for their use in a grid computing context.