A Fast and High Quality Multilevel Scheme for Partitioning Irregular Graphs
SIAM Journal on Scientific Computing
Scalable, efficient epidemiological simulation
Proceedings of the 2002 ACM symposium on Applied computing
A flexible, large-scale, distributed agent based epidemic model
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Proceedings of the 2008 ACM/IEEE conference on Supercomputing
An interaction-based approach to computational epidemiology
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
BioWar: scalable agent-based model of bioattacks
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Indemics: an interactive data intensive framework for high performance epidemic simulation
Proceedings of the 24th ACM International Conference on Supercomputing
Clustering method incorporating network topology and dynamics
SpringSim '10 Proceedings of the 2010 Spring Simulation Multiconference
SBP'11 Proceedings of the 4th international conference on Social computing, behavioral-cultural modeling and prediction
Generation and analysis of large synthetic social contact networks
Winter Simulation Conference
Winter Simulation Conference
Reversible Parallel Discrete-Event Execution of Large-Scale Epidemic Outbreak Models
PADS '10 Proceedings of the 2010 IEEE Workshop on Principles of Advanced and Distributed Simulation
Optimizing epidemic protection for socially essential workers
Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium
Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium
Coevolution of epidemics, social networks, and individual behavior: a case study
SBP'10 Proceedings of the Third international conference on Social Computing, Behavioral Modeling, and Prediction
High performance informatics for pandemic preparedness
Proceedings of the Winter Simulation Conference
Proceedings of the Winter Simulation Conference
Efficient implementation of complex interventions in large scale epidemic simulations
Proceedings of the Winter Simulation Conference
Interaction-based HPC modeling of social, biological, and economic contagions over large networks
Proceedings of the Winter Simulation Conference
Information Sciences: an International Journal
Parallel algorithm for simulating the spatial transmission of influenza in EpiGraph
Proceedings of the 20th European MPI Users' Group Meeting
Indemics: An interactive high-performance computing framework for data-intensive epidemic modeling
ACM Transactions on Modeling and Computer Simulation (TOMACS) - Special issue on simulation in complex service systems
Designing an agent based model for the efficient removal of red imported fire ant colonies
Proceedings of the 2013 Summer Computer Simulation Conference
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Large scale realistic epidemic simulations have recently become an increasingly important application of high-performance computing. We propose a parallel algorithm, EpiFast, based on a novel interpretation of the stochastic disease propagation in a contact network. We implement it using a master-slave computation model which allows scalability on distributed memory systems. EpiFast runs extremely fast for realistic simulations that involve: (i) large populations consisting of millions of individuals and their heterogeneous details, (ii) dynamic interactions between the disease propagation, the individual behaviors, and the exogenous interventions, as well as (iii) large number of replicated runs necessary for statistically sound estimates about the stochastic epidemic evolution. We find that EpiFast runs several magnitude faster than another comparable simulation tool while delivering similar results. EpiFast has been tested on commodity clusters as well as SGI shared memory machines. For a fixed experiment, if given more computing resources, it scales automatically and runs faster. Finally, EpiFast has been used as the major simulation engine in real studies with rather sophisticated settings to evaluate various dynamic interventions and to provide decision support for public health policy makers.