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Spiking neural networks (SNN) are among the most computationally intensive types of simulation models, with node counts on the order of up to 1011. Currently, there is intensive research into hardware platforms suitable to support large-scale SNN simulations, whereas several of the most widely...
Our world today increasingly relies on the orchestration of digital and physical systems to ensure the successful operations of many complex and critical infrastructures. Simulation-based testbeds are useful tools for engineering those cyber-physical systems and evaluating their efficiency,...
Fluid approximation results provide powerful methods for scalable analysis of models of population dynamics with large numbers of discrete states and have seen wide-ranging applications in modelling biological and computer-based systems and model checking. However, the applicability of these...
Ever since the conception of the statistical ranking-and-selection (R8S) problem, a predominant approach has been the indifference-zone (IZ) formulation. Under the IZ formulation, R8S procedures are designed to provide a guarantee on the probability of correct selection (PCS) whenever the...
Hardware architectures become increasingly complex as the compute capabilities grow to exascale. We present the Analytical Memory Model with Pipelines (AMMP) of the Performance Prediction Toolkit (PPT). PPT-AMMP takes high-level source code and hardware architecture parameters as input and...
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