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TADSim: Discrete Event-Based Performance Prediction for Temperature-Accelerated Dynamics
Susan M. Mniszewski, Christoph Junghans, Arthur F. Voter, Danny Perez, Stephan J. Eidenbenz
Article No.: 15
Next-generation high-performance computing will require more scalable and flexible performance prediction tools to evaluate software--hardware co-design choices relevant to scientific applications and hardware architectures. We present a new class...
Predictions from simulations have entered the mainstream of public policy and decision-making practices. Unfortunately, methods for gaining insight into faulty simulations outputs have not kept pace. Ideally, an insight gathering method would...
Model Continuity in Discrete Event Simulation: A Framework for Model-Driven Development of Simulation Models
Deniz Çetinkaya, Alexander Verbraeck, Mamadou D. Seck
Article No.: 17
Most of the well-known modeling and simulation (M&S) methodologies state the importance of conceptual modeling in simulation studies, and they suggest the use of conceptual models during the simulation model development process. However, only a...
Calibration, Validation, and Prediction in Random Simulation Models: Gaussian Process Metamodels and a Bayesian Integrated Solution
Jun Yuan, Szu Hui Ng
Article No.: 18
Model calibration and validation are important processes in the development of stochastic computer models of real complex systems. This article introduces an integrated approach for model calibration, validation, and prediction based on Gaussian...
AIR: Application-Level Interference Resilience for PDES on Multicore Systems
Jingjing Wang, Nael Abu-Ghazaleh, Dmitry Ponomarev
Article No.: 19
Parallel discrete event simulation (PDES) harnesses parallel processing to improve the performance and capacity of simulation, supporting bigger and more detailed models simulated for more scenarios. The presence of interference from other users...
Overlapping Batches for the Assessment of Solution Quality in Stochastic Programs
David Love, Güzin Bayraksan
Article No.: 20
Overlapping Batch Means (OBM) has long been used in simulation as a method of reusing data to generate variance estimators with asymptotically lower variance. In this article, we apply the OBM method to stochastic programming by formulating a...