Yuri A. Omelchenko

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A virtualization system is presented that is designed to help predict the performance of parallel/distributed discrete event simulations on massively parallel (supercomputing) platforms. It is intended to be useful in experimenting with and understanding the effects of execution parameters, such as different load balancing schemes and mixtures of model(More)
Efficient computer simulation of complex physical phenomena has long been challenging due to their multi-physics and multi-scale nature. In contrast to traditional time-stepped execution methods, we describe an approach using optimistic parallel discrete event simulation (PDES) and reverse computation techniques. We show that reverse computation-based(More)
Efficient computer simulation of complex physical phenomena has long been challenging due to their multiphysics and multiscale nature. In contrast to traditional time-stepped execution methods, the authors describe an approach using optimistic parallel discrete event simulation (PDES) and reverse computation techniques to execute plasma physics codes. They(More)
Particle-in-cell models have become standard computational tools for studying complex nonlinear phenomena in space and laboratory plasmas. These simulations are normally very compute-intensive since they require time integration of strongly coupled equations governing the field and particle dynamics. As a result, despite a significant progress in hardware(More)
The traditional technique to simulate physical systems modeled by partial differential equations is by means of a time-stepped methodology where the state of the system is updated at regular discrete time intervals. This method has inherent inefficiencies. Recently, we proposed [1] a new asynchronous formulation based on a discrete-event-driven (as opposed(More)
Self-adaptive discrete-event simulation is a general paradigm for time integration of discretized partial differential equations and particle models. This novel approach enables local time steps for equations describing time evolution of grid-based elements (fluids, fields) and macro-particles on arbitrary grids while preserving underlying conservation(More)
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