Model for dynamic grain sizing through compound parallelization for an optimization problem solving grid application

MHGrid (meta heuristics grid), a service oriented grid application offering global optimization solvers, allows developers to integrate their solvers and objective functions through an easy-to-use transparent mechanism . As a consequence of offering such a service, MHGrid hosts solvers and objective functions implementing diverse parallelization models leading later to different job grain size. Yet, the flexibility of the existing grid programming tools is limited if used individually. This paper proposes a model that uses a combination of grid parallel programming tools to enable the developers of MHGrid to specify their own parallelization model. Using this model the end user can choose the parallel model of the solver/objective function pair generating the grain size most appropriate to the problem in hand.