September 13, 2017
Conference Paper

Distributed-Memory Fast Maximal Independent Set

Abstract

The Maximal Independent Set (MIS) graph problem arises in many applications such as computer vision, information theory, molecular biology, and process scheduling. The growing scale of MIS problems suggests the use of distributed-memory hardware as a cost-effective approach to providing necessary compute and memory resources. Luby proposed four randomized algorithms to solve the MIS problem. All those algorithms are designed focusing on shared-memory machines and are analyzed using the PRAM model. These algorithms do not have direct efficient distributed-memory implementations. In this paper, we extend two of Luby’s seminal MIS algorithms, “Luby(A)” and “Luby(B),” to distributed-memory execution, and we evaluate their performance. We compare our results with the “Filtered MIS” implementation in the Combinatorial BLAS library for two types of synthetic graph inputs.

Revised: April 20, 2018 | Published: September 13, 2017

Citation

Kanewala Appuhamilage T.J., M.J. Zalewski, and A. Lumsdaine. 2017. Distributed-Memory Fast Maximal Independent Set. In IEEE High Performance Extreme Computing Conference (HPEC 2017), September 12-14, 2017, Waltham, Massachusetts, 1-7. Piscataway, New Jersey:IEEE. PNNL-SA-129122. doi:10.1109/HPEC.2017.8091032