This paper proposes a comprehensive modeling architecture for workloads on parallel computers using Markov chains in combination with state dependent empirical distribution functi...
Bayesian learning, widely used in many applied data-modeling problems, is often accomplished with approximation schemes because it requires intractable computation of the posterio...
Upper bounds on worst-case execution times, which are commonly called WCET, are a prerequisite for validating the temporal correctness of tasks in a real-time system. Due to the e...
—This paper describes the acceleration of virtual ecology models using field-programmable gate arrays (FPGAs). Our approach targets models generated by the Virtual Ecology Workb...
— In this paper, a novel approach for parallel kinematic machine control relying on a fast exteroceptive measure is implemented and validated on the Orthoglide robot. This approa...
Flavien Paccot, Philippe Lemoine, Nicolas Andreff,...