Parallel multiple sequence alignment with dynamic scheduling

Abstract

This paper proposes a parallel implementation of the multiple sequence alignment algorithm, known as ClustalW, on distributed memory parallel machines. The proposed algorithm divides a progressive alignment into subtasks and schedules them dynamically. A task tree is built according to the dependency of the generated phylogenetic tree. The computation and communication costs of the tasks are estimated at run-time and updated periodically. With dynamic scheduling, tasks are allocated to the processors considering the tasks' estimated computation and communication costs and the processors' workload in order to minimize the completion time. The experiment results show that the proposed parallel implementation achieves a considerable speedup over the sequential ClustalW.