Predicting the Cost and Benefit of Adapting Data Parallel Applications in Clusters

Jon B. Weissman
2002 Journal of Parallel and Distributed Computing  
This paper examines the problem of adapting data parallel applications in a shared dynamic environment of PC or workstation clusters. We developed an analytic framework to compare and contrast a wide range of adaptation strategies: dynamic load balancing, migration, processor addition and removal. These strategies have been evaluated with respect to the cost and benefit they provide for three representative parallel applications: an iterative jacobi solver for Laplace's equation, gaussian
more » ... ation with partial pivoting, and a gene sequence comparison application. We found that the cost and benefit of each method can be predicted with high accuracy (within 10%) for all applications and show that the framework is applicable to a wide variety of parallel applications. We then show that accurate prediction allows the most appropriate method to be selected dynamically. Performance improvement for the three applications ranged from 25% to 45% using our adaptation library. In addition, we dispel the conventional wisdom that migration is too expensive, and show that it can be beneficial even for running parallel applications with non-trivial communication. # 2002 Elsevier Science (USA)
doi:10.1006/jpdc.2002.1838 fatcat:m5obcfh2m5ckzdpannf5xjw7jy