On the Effectiveness of Superconcurrent Computations on Heterogeneous Networks

Concurrent computing on networked collections of computer systems is rapidly evolving into a viable technology that is attractive from the economic, performance, and availability perspectives. Several software infrastructures that support such heterogeneous network-based concurrent computing have evolved, and are in use for production-quality high-performance computing. In this paper, we describe such a system, and present our experiences with its use for massively concurrent computing in the application domain of polymer physics. The application involves stochastic simulation of polymer chains for measuring scale-invariant phenomena at critical disorder. The parallelization is achieved through the EcliPSe toolkit, and conducted on a flexible, tree-structured virtual machine made up of arbitrary and heterogeneous computing nodes dispersed across the country. These nodes cooperate to perform the simulation and pool results together in real time, at intermediate nodes in a tree, culminating at a central node which controls the parallel simulation. The advantage of the tree-structure is that it allows for a fault-resilient, flexible environment for long-running parallel simulations. We present results on performance, price-performance, and toolkit-based parallelization, and compare these against equivalent computations on a Cray/Y-MP.