Existing partitioning algorithms provide limited support for load balancing simulations that are performed on heterogeneous parallel computing platforms. On such architectures, effective load balancing can only be achieved if the graph is distributed so that it properly takes into account the available resources (CPU speed, network bandwidth). With heterogeneous technologies becoming more popular, the need for suitable graph partitioning algorithms is critical. We developed such algorithms that can address the partitioning requirements of scientific computations, and can correctly model the architectural characteristics of emerging hardware platforms. © 2008 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Moulitsas, I., & Karypis, G. (2008). Architecture aware partitioning algorithms. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5022 LNCS, pp. 42–53). https://doi.org/10.1007/978-3-540-69501-1_6
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