Dynamic load balancing schemes for computing accessible surface area of protein molecules

This paper presents an experimental study of dynamic load balancing methods for a parallelized solution to a well-known problem in computational molecular biology: computing the accessible surface areas (ASA) of proteins. The main contribution is a better understanding of how certain techniques for load estimation and redistribution must be combined carefully for effectiveness and how these combinations need to change during the course of a computation. In particular, the Shrake-Rupley ASA algorithm is implemented and three aspects of dynamic load balancing are studied: how to estimate load imbalance (the estimation problem); when to invoke load redistribution (the invocation problem); and how to load balance (the mapping problem). The results in this paper show that a dynamically-selected mix of algorithms in each category that adapts to changing structure within the protein works better than a static periodic application of a static mix of algorithms