ALGORITHMS: Adaptive Stochastic Scheduling for Bulk Synchronous Computations and Its Application in Molecular Dynamics Simulations

Wayne State University, Detroit MI

Investigators

Abstract

This research investigates the parallel efficiency of an important class of bulk synchronous applications, as exemplified by computational molecular dynamics, in clusters of workstations. Bulk synchronous applications are often characteristic of non-deterministic computational requirements over time. In a multiprogramming environment, the nodal capacities allocated to an application may also change as other jobs join and leave. With respect to the dynamics of the computation and uncertainties of the cluster resources, this research aims at developing stochastic scheduling strategies in support of high performance computing in the clusters. It constructs a framework for modeling and analyses of adaptive scheduling algorithms by characterizing scheduling factors as random variables. It develops efficient application-level remapping policies by taking into account the dynamic systems of workload evolution and capacity change. The scheduling strategies are evaluated in the application of molecular dynamics computer simulations. The research will blend formal modeling/analyses, experimentation, and evaluation of stochastic scheduling algorithms. Success of this research will help increase the industrial acceptance of high performance cluster computing and advance computational molecular dynamics to simulations of large, multi-atom systems in a timely manner.