Search Our Scientific Publications & Authors

ACM Trans Model Comput Simul 2017 Jul;27(2)

Department of Neurobiology, Yale University, New Haven, Connecticut, USA;

Cells exhibit stochastic behavior when the number of molecules is small. Hence a stochastic reaction-diffusion simulator capable of working at scale can provide a more accurate view of molecular dynamics within the cell. This paper describes a parallel discrete event simulator, Neuron Time Warp-Multi Thread (NTW-MT), developed for the simulation of reaction diffusion models of neurons. Read More

ACM Trans Model Comput Simul 2014 Jan;24(1)

Virginia Bioinformatics Institute, Virginia Tech, Department of Computer Science, Virginia Tech.

We describe the design and prototype implementation of Indemics (Interactive EpidemicSimulation)-a modeling environment utilizing high-performance computing technologies for supporting complex epidemic simulations. Indemics can support policy analysts and epidemiologists interested in planning and control of pandemics. Indemics goes beyond traditional epidemic simulations by providing a simple and powerful way to represent and analyze policy-based as well as individual-based . Read More

ACM Trans Model Comput Simul 2013 Jan;23(1)

Department of Statistics, Columbia University, New York, NY, USA.

Following a series of high-profile drug safety disasters in recent years, many countries are redoubling their efforts to ensure the safety of licensed medical products. Large-scale observational databases such as claims databases or electronic health record systems are attracting particular attention in this regard, but present significant methodological and computational concerns. In this paper we show how high-performance statistical computation, including graphics processing units, relatively inexpensive highly parallel computing devices, can enable complex methods in large databases. Read More

ACM Trans Model Comput Simul 2011 Dec;22(1)

The Johns Hopkins University.

The Global-Scale Agent Model (GSAM) is presented. The GSAM is a high-performance distributed platform for agent-based epidemic modeling capable of simulating a disease outbreak in a population of several billion agents. It is unprecedented in its scale, its speed, and its use of Java. Read More