June 3-5, 2019

Chicago, Illinois, USA

PADS Program Description and Scope

PADS program is described and the scope of the conference is defined.

High-Fidelity Battlefield Simulation Support Military Simulation Simulations Prepare Marine Corps for War Virtual Reality Simulation Virtual Reality Driving Simulator Virtual Reality Medical Simulator
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ACM SIGSIM Conference on Principles of Advanced Discrete Simulation (PADS)
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PADS Program Description


ACM SIGSIM PADS is the flagship conference for the ACM Special Interest Group on Simulation and Modeling (SIGSIM). It continues a long history and reputation for high quality papers. Building upon previous conferences that focused on parallel and distributed simulation, SIGSIM PADS broadens this scope to encompass all innovations that lie at the intersection of computer science and modeling and simulation, emphasizing discrete event simulation models. It spans both sequential as well as parallel and distributed simulation techniques. SIGSIM PADS builds upon the long history of PADS conferences dating back to 1985.

 

PADS Program Scope


SIGSIM PADS solicits high quality papers dealing with cutting-edge research that lies at the intersection of computer science and modeling and simulation, including (but not restricted to) the following areas:

  • Advanced modeling techniques, including reuse of models, new modeling languages, agent-based M&S, and spatially explicit M&S.
  • Algorithms and methods for parallel or distributed simulation, including synchronization, scheduling, memory management, load balancing, and scalability issues.
  • New simulation algorithms and techniques including hybrid simulation approaches, adaptive algorithms, approximations, GPU, FPGA and hybrid architecture acceleration.
  • Modeling and simulation for big data and big data analytics.
  • Simulation infrastructure and security issues for large scale distributed and/or cloud-based modeling and simulation.
  • Model and simulation persistence and recovery in the presence of hardware failures.
  • Integration of simulation with other IT systems, methods, and developments including simulation based decision-making, visual analytics, intelligent support in M&S, and simulation in cloud computing environments.
  • Mechanisms for efficient design of experiments, including dynamic verification and validation of models, and automatic simulation model generation and initialization.
  • M&S applied to manage and/or optimize operational systems and methodological challenges arising from these applications including online simulation, symbiotic simulation, dynamic data-driven application systems, real-time and embedded simulation, and emulation of real systems.
  • Tools and techniques for interoperability and composability of simulations including emerging standards and service-oriented approaches.
  • Case studies considering the application of new or advanced computational methods to applications of contemporary interest.

 

 

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