TY - GEN
T1 - Overcoming the scalability challenges of epidemic simulations on blue waters
AU - Yeom, Jae Seung
AU - Bhatele, Abhinav
AU - Bisset, Keith
AU - Bohm, Eric
AU - Gupta, Abhishek
AU - Kale, Laxmikant V.
AU - Marathe, Madhav
AU - Nikolopoulos, Dimitrios S.
AU - Schulz, Martin
AU - Wesolowski, Lukasz
PY - 2014
Y1 - 2014
N2 - Modeling dynamical systems represents an important application class covering a wide range of disciplines including but not limited to biology, chemistry, finance, national security, and health care. Such applications typically involve large-scale, irregular graph processing, which makes them difficult to scale due to the evolutionary nature of their workload, irregular communication and load imbalance. EpiSimdemics is such an application simulating epidemic diffusion in extremely large and realistic social contact networks. It implements a graph-based system that captures dynamics among co-evolving entities. This paper presents an implementation of EpiSimdemics in Charm++ that enables future research by social, biological and computational scientists at unprecedented data and system scales. We present new methods for application-specific processing of graph data and demonstrate the effectiveness of these methods on a Cray XE6, specifically NCSA's Blue Waters system.
AB - Modeling dynamical systems represents an important application class covering a wide range of disciplines including but not limited to biology, chemistry, finance, national security, and health care. Such applications typically involve large-scale, irregular graph processing, which makes them difficult to scale due to the evolutionary nature of their workload, irregular communication and load imbalance. EpiSimdemics is such an application simulating epidemic diffusion in extremely large and realistic social contact networks. It implements a graph-based system that captures dynamics among co-evolving entities. This paper presents an implementation of EpiSimdemics in Charm++ that enables future research by social, biological and computational scientists at unprecedented data and system scales. We present new methods for application-specific processing of graph data and demonstrate the effectiveness of these methods on a Cray XE6, specifically NCSA's Blue Waters system.
KW - contagion simulations
KW - graph processing
KW - performance
KW - scalability
KW - social contact networks
UR - http://www.scopus.com/inward/record.url?scp=84906673141&partnerID=8YFLogxK
U2 - 10.1109/IPDPS.2014.83
DO - 10.1109/IPDPS.2014.83
M3 - Conference contribution
AN - SCOPUS:84906673141
SN - 9780769552071
T3 - Proceedings of the International Parallel and Distributed Processing Symposium, IPDPS
SP - 755
EP - 764
BT - Proceedings - IEEE 28th International Parallel and Distributed Processing Symposium, IPDPS 2014
PB - IEEE Computer Society
T2 - 28th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2014
Y2 - 19 May 2014 through 23 May 2014
ER -