Miami, United States of America
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The 2020 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation (ACM SIGSIM PADS) will take place as a Virtual Conference with remote participation at Florida International University, Biscayne Bay Campus, Wolfe University Center on June 15-17, 2020 in Miami, Florida, U.S.A.
The annual PADS conference has a long history dating back to 1985. The conference was formerly known under the name Principles of Advanced and Distributed Simulation, and before that simply Parallel and Distributed Simulation. Over the years PADS has broadened its scope beyond its origins in parallel and distributed simulation and now encompasses virtually all research that lies at the intersection of the computer science and the modeling and simulation fields. Specifically, many research topics not related to parallel or distributed model execution are now included.
SIGSIM PADS provides a unique forum for reporting and discussing research results and important topics of interest to the M&S community. SIGSIM PADS is the flagship conference of ACM's Special Interest Group on Simulation and Modeling (SIGSIM) and is fully sponsored by that organization.
Topics
* 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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