Large-Scale Simulation: Models, Algorithms, and Applications gives you firsthand insight on the latest advances in large-scale simulation techniques. Most of the research results are drawn from the authors' papers in top-tier, peer-reviewed, scientific conference proceedings and journals.
The first part of the book presents the fundamentals of large-scale simulation, including high-level architecture and runtime infrastructure. The second part covers middleware and software architecture for large-scale simulations, such as decoupled federate architecture, fault tolerant mechanisms, grid-enabled simulation, and federation communities. In the third part, the authors explore mechanisms--such as simulation cloning methods and algorithms--that support quick evaluation of alternative scenarios. The final part describes how distributed computing technologies and many-core architecture are used to study social phenomena.
Reflecting the latest research in the field, this book guides you in using and further researching advanced models and algorithms for large-scale distributed simulation. These simulation tools will help you gain insight into large-scale systems across many disciplines.
About the Author: Dan Chen is a professor and director of the Scientific Computing Lab at the China University of Geosciences. His research interests include computer-based modeling and simulation, high performance computing, and neuroinformatics.
Lizhe Wang is a professor at the Center for Earth Observation and Digital Earth, Chinese Academy of Sciences. Dr. Wang is also a ChuTian Scholar Chair Professor at the China University of Geosciences, a senior member of IEEE, and a member of ACM. His research interests include high performance computing, grid/cloud computing, and data-intensive computing.
Jingying Chen is a professor in the National Engineering Centre for e-Learning at Huazhong Normal University. Her research interests include intelligent systems, computer vision, and pattern recognition.
