Nonlinear dynamics of phase space zonal structures and energetic particle physics in fusion plasmas

A general theoretical framework for investigating nonlinear dynamics of phase space zonal structures is presented in this work. It is then, more specifically, applied to the limit where the nonlinear evolution time scale is smaller or comparable to the wave-particle trapping period. In this limit, both theoretical and numerical simulation studies show that non-adiabatic frequency chirping and phase locking could lead to secular resonant particle transport on meso- or macro-scales. The interplay between mode structures and resonant particles then provides the crucial ingredient to properly understand and analyze the nonlinear dynamics of Alfv\'en wave instabilities excited by non-perturbative energetic particles in burning fusion plasmas. Analogies with autoresonance in nonlinear dynamics and with superradiance in free electron lasers are also briefly discussed

Workload Decomposition Strategies for Shared Memory Parallel Systems with OpenMP

A crucial issue in parallel programming (both for distributed and shared memory architectures) is work decomposition. Work decomposition task can be accomplished without large programming effort with use of high-level parallel programming languages, such as OpenMP. Anyway particular care must still be payed on achieving performance goals. In this paper we introduce and compare two decomposition strategies, in the framework of shared memory systems, as applied to a case study particle in cell application. A number of different implementations of them, based on the OpenMP language, are discussed with regard to time efficiency, memory occupancy, and program restructuring effort

Parallel Implementation of a Lattice Boltzmann Algorithm for the Electrostatic Plasma Turbulence

. A parallel version of a Lattice Boltzmann Equation algorithm, which simulates the electrostatic plasma turbulence, has been developed using the High Performance Fortran language. The algorithm evolves a system of particle populations on a discrete lattice and dataparallel implementation has been performed by a regular domain decomposition. System evolution requires both completely local and non-local operations, involving communication between processors. Communication phase has been minimized using local HPF procedures. Efficiency tests of the parallel code, performed on a 9076 IBM-SP2 parallel computer, have given satisfactory results. 1 Lattice Boltzmann Algorithm for the Electrostatic Plasma Turbulence A Lattice Boltzmann algorithm was developed to simulate the electrostatic turbulence in a magnetized plasma, within the framework of the two-fluid model [1, 2]. The ion continuity, momentum and pressure equations are reproduced, with the electrons being described by the adiabatic ..

Simulazioni lattice Boltzmann della turbolenza elettrostatica in un plasma

Dottorato di ricerca in fisica. 8. ciclo. Tutore R. Benzi. Coordinatore P. PicozzaConsiglio Nazionale delle Ricerche - Biblioteca Centrale - P.le Aldo Moro, 7, Rome; Biblioteca Nazionale Centrale - P.za Cavalleggeri, 1, Florence / CNR - Consiglio Nazionale delle RichercheSIGLEITItal

Fogaccia G. Workload decomposition strategies for shared memory parallel systems with OpenMP

A crucial issue in parallel programming (both for distributed and shared memory architectures) is work decomposition. Work decomposition task can be accomplished without large programming effort with use of high-level parallel programming languages, such as OpenMP. Anyway particular care must still be payed on achieving performance goals. In this paper we introduce and compare two decomposition strategies, in the framework of shared memory systems, as applied to a case study particle in cell application. A number of different implementations of them, based on the OpenMP language, are discussed with regard to time efficiency, memory occupancy, and program restructuring effort

Workload decomposition strategies for shared memory parallel systems with OpenMP

A crucial issue in parallel programming (both for distributed and shared memory architectures) is work decomposition. Work decomposition task can be accomplished without large programming effort with use of high-level parallel programming languages, such as OpenMP. Anyway particular care must still be payed on achieving performance goals. In this paper we introduce and compare two decomposition strategies, in the framework of shared memory systems, as applied to a case study particle in cell application. A number of different implementations of them, based on the OpenMP language, are discussed with regard to time efficiency, memory occupancy, and program restructuring effort