Grupo de Física de Plasmas
http://hdl.handle.net/10016/7404
Tue, 28 Mar 2017 21:39:28 GMT2017-03-28T21:39:28ZDoes size matter?
http://hdl.handle.net/10016/18863
Does size matter?
Carreras, Benjamín A.; Newman, D.E.; Dobson, Ian
Failures of the complex infrastructures society depends on having enormous human and economic cost that poses the question: Are there ways to optimize these systems to reduce the risks of failure? A dynamic model of one such system, the power transmission grid, is used to investigate the risk from failure as a function of the system size. It is found that there appears to be optimal sizes for such networks where the risk of failure is balanced by the benefit given by the size.
Tue, 01 Apr 2014 00:00:00 GMThttp://hdl.handle.net/10016/188632014-04-01T00:00:00ZParallelization in time of numerical simulations of fully-developed plasma turbulence using the parareal algorithm
http://hdl.handle.net/10016/8911
Parallelization in time of numerical simulations of fully-developed plasma turbulence using the parareal algorithm
Samaddar, D.; Newman, David E.; Sánchez, Raúl
It is shown that numerical simulations of fully-developed plasma turbulence can be successfully parallelized in time using the parareal algorithm. The result is far from trivial, and even unexpected, since the exponential divergence of Lagrangian trajectories as well as the extreme sensitivity to initial conditions characteristic of turbulence set these type of simulations apart from the much simpler systems to which the parareal algorithm has been applied to this day. It is also shown that the parallel gain obtainable with this method is very promising (close to an order of magnitude for the cases and implementations described), even when it scales with the number of processors quite differently to what is typical for spatial parallelization.
16 pages, 12 figures.
Wed, 01 Sep 2010 00:00:00 GMThttp://hdl.handle.net/10016/89112010-09-01T00:00:00ZBCYCLIC: A parallel block tridiagonal matrix cyclic solver
http://hdl.handle.net/10016/8910
BCYCLIC: A parallel block tridiagonal matrix cyclic solver
Hirshman, S. P.; Perumalla, K. S.; Lynch, V. E.; Sánchez, Raúl
A block tridiagonal matrix is factored with minimal fill-in using a cyclic reduction algorithm that is easily parallelized. Storage of the factored blocks allows the application of the inverse to multiple right-hand sides which may not be known at factorization time. Scalability with the number of block rows is achieved with cyclic reduction, while scalability with the block size is achieved using multithreaded routines (OpenMP, GotoBLAS) for block matrix manipulation. This dual scalability is a noteworthy feature of this new solver, as well as its ability to efficiently handle arbitrary (non-powers-of-2) block row and processor numbers. Comparison with a state-of-the art parallel sparse solver is presented. It is expected that this new solver will allow many physical applications to optimally use the parallel resources on current supercomputers. Example usage of the solver in magneto-hydrodynamic (MHD), three-dimensional equilibrium solvers for high-temperature fusion plasmas is cited.
13 pages, 6 figures.
Wed, 01 Sep 2010 00:00:00 GMThttp://hdl.handle.net/10016/89102010-09-01T00:00:00ZPersistent dynamic correlations in self-organized critical systems away from their critical point
http://hdl.handle.net/10016/8906
Persistent dynamic correlations in self-organized critical systems away from their critical point
Woodard, Ryan; Newman, David E.; Sánchez, Raúl; Carreras, Benjamín A.
We show that correlated dynamics and long time memory persist in self-organized criticality (SOC) systems even when forced away from the defined critical point that exists at vanishing drive strength. These temporal correlations are found for all levels of external forcing as long as the system is not overdriven. They arise from the same physical mechanism that produces the temporal correlations found at the vanishing drive limit, namely the memory of past events stored in the system profile. The existence of these correlations contradicts the notion that a SOC time series is simply a random superposition of events with sizes distributed as a power law, as has been suggested by previous studies.
16 pages, 12 figures.-- PACS nrs.: 05.65.+b, 05.40.-a, 52.25.Fi, 96.60.Rd.-- ArXiv pre-print available at: http://arxiv.org/abs/cond-mat/0503159
Mon, 01 Jan 2007 00:00:00 GMThttp://hdl.handle.net/10016/89062007-01-01T00:00:00Z