A Model for Task Repartioning under Data Replication
Cevdet Aykanat, Erkan Okuyan, Berkant Barla Cambazoglu · DROPS (Schloss Dagstuhl – Leibniz Center for Informatics) · 2009
We propose a two-phase model for solving the problem of task repartitioning under data replication with memory constraints. The hypergraph-partitioning-based model proposed for the first phase aims to minimize the total message volume that will be incurred due to the replication/migration of input data while maintaining balance on computational and receive-volume loads of processors. The network-flow-based model proposed for the second phase aims to minimize the maximum message volume handled by processors via utilizing the flexibility in assigning send-communication tasks to processors, which is introduced by data replication. The validity of our proposed model is verified on parallelization of a direct volume rendering algorithm.