Large-Scale Computing Techniques for Complex System Simulations

Discover the Latest Computing Technology Needed to Design State-of-the-Art complex system simulations

Complex system simulations increasingly support informed decision-making in such fields as finance, economics, biology, astronomy, and many more. With this book as their guide, readers can master large-scale computing technologies and then use them to develop complex system simulations. Large-Scale Computing Techniques for Complex System Simulations not only presents the current state of the technology, it also points to new directions for research in the field as well as emerging applications.

This text examines a remarkably wide range of computing technologies and applications. Its presentation of computing technologies emphasizes distributed computing approaches, but also considers supercomputing and other novel technologies. On the applications side, the book discusses modeling and simulation of both natural and man-made complex systems. Specifically, the book presents such critical topics as:

• e-Infrastructure ecosystems

• Accelerated many-core GPU computing on three continents

• SimWorld agent-based grid experimentation systems

• Collaborative distributed multi-scale applications

• Large-scale data intensive computing

• QosCosGrid e-science infrastructure

Throughout the text, readers will find state-of-the-art software technologies alongside best practices, tools, and middleware services to help them perform advanced complex system research using simulations. Moreover, the authors have included numerous examples of actual applications and their performance results to help readers design and perform their own simulations.

Bridging the gap between computer technology and complex system simulation, Large-Scale Computing Techniques for Complex System Simulations serves as a design blueprint, user guide, and research agenda for all researchers, practitioners, scientists, and students interested in developing simulations that can accurately reflect and predict complex systems.