Vicente Vidal

SLEPc: A scalable and flexible toolkit for the solution of eigenvalue problems

The Scalable Library for Eigenvalue Problem Computations (SLEPc) is a software library for computing a few eigenvalues and associated eigenvectors of a large sparse matrix or matrix pencil. It has been developed on top of PETSc and enforces the same programming paradigm.The emphasis of the software is on methods and techniques appropriate for problems in which the associated matrices are sparse, for example, those arising after the discretization of partial differential equations. Therefore, most of the methods offered by the library are projection methods such as Arnoldi or Lanczos, or other methods with similar properties. SLEPc provides basic methods as well as more sophisticated algorithms. It also provides built-in support for spectral transformations such as the shift-and-invert technique. SLEPc is a general library in the sense that it covers standard and generalized eigenvalue problems, both Hermitian and non-Hermitian, with either real or complex arithmetic.SLEPc can be easily applied to real world problems. To illustrate this, several case studies arising from real applications are presented and solved with SLEPc with little programming effort. The addressed problems include a matrix-free standard problem, a complex generalized problem, and a singular value decomposition. The implemented codes exhibit good properties regarding flexibility as well as parallel performance.

3D λ-modes of the neutron-diffusion equation

Abstract The paper deals with the calculation of the 3D harmonic lambda modes in a B.W.R. reactor. An algorithm to calculate the harmonic lambda modes corresponding to the steady state two-group 3D neutron-diffusion equation is presented. The algorithm uses subspace iteration method techniques combined with convergence acceleration based on variational principles. The methodology has been tested on two benchmark problems, and applied to obtain the 3D modes of the Cofrentes Nuclear Power Plant.

The implicit restarted Arnoldi method, an efficient alternative to solve the neutron diffusion equation

Abstract To calculate the neutronic steady state of a nuclear power reactor core and its subcritical modes, it is necessary to solve a partial eigenvalue problem. In this paper, an implicit restarted Arnoldi method is presented as an advantageous alternative to classical methods as the Power Iteration method and the Subspace Iteration method. The efficiency of these methods, has been compared calculating the dominant Lambda modes of several configurations of the Three Mile Island reactor core.

High order backward discretization of the neutron diffusion equation

Abstract Fast codes capable of dealing with three-dimensional geometries, are needed to be able to simulate spatially complicated transients in a nuclear reactor. We propose a new discretization technique for the time integration of the neutron diffusion equation, based on the backward difference formulas for systems of stiff ordinary differential equations. This method needs to solve a system of linear equations for each integration step, and for this purpose, we have developed an iterative block algorithm combined with a variational acceleration technique. We tested the algorithm with two benchmark problems, and compared the results with those provided by other codes, concluding that the performance and overall agreement are very good.

SLEPc: scalable library for eigenvalue problem computations

The eigenvalue problem is one of the most important problems in numerical linear algebra. Several public domain software libraries are available for solving it. In this work, a new petsc-based package is presented, which is intended to be an easy-to-use yet efficient object-oriented parallel framework for the solution of standard and generalised eigenproblems, either in real or complex arithmetic. The main objective is to allow the solution of real world problems in a straightforward way, especially in the case of large software projects.

Master Selection Policies for Inter-destination Multimedia Synchronization in Distributed Applications

This paper presents an enhanced version of a proposed extension of the RTP/RTCP standard protocols to acquire Inter-Destination Multimedia Synchronization (IDMS) in one-way distributed applications. Several dynamic policies for selecting the master reference play out point to synchronize are introduced and their suitability is analyzed, for specific network conditions and application requirements, according to the impact of the play out adjustments (such as skips and/or pauses) on the overall quality and the buffer fullness variation. Simulation results prove the ability of our approach, for all the proposed master selection algorithms, to maintain the play out asynchrony between distributed receivers within acceptable limits, by dynamically adjusting their play out timing every time an allowed play out time discrepancy between their play out states is detected.

3D Alpha Modes of a Nuclear Power Reactor

This work is focused on the determination of the dominant α-modes corresponding to three time-eigenvalue problems. A nodal collocation method is used for the discretization of the differential eigenvalue problem and a restarted Krylov method has been used to solve the algebraic eigenvalue problem. Also, the relation between the λ-modes and α-modes is studied through the concept of prompt neutron generation time, which has several interpretations. To present numerical results of the different α-modes, we have studied a benchmark reactor and a configuration associated with Ringhals NPP.

Medical image restoration with different types of noise

The images obtained by X-Ray or computed tomography (CT) in adverse conditions may be contaminated with noise that can affect the detection of diseases. A large number of image processing techniques (filters) have been proposed to remove noise. These techniques depend on the type of noise present in the image. In this work, we propose a method designed to reduce the Gaussian, the impulsive and speckle noise and combined noise. This filter, called PGNDF, combines a non-linear diffusive filter with a peer group with fuzzy metric technique. The proposed filter is able to reduce efficiently the image noise without any information about what kind of noise might be present. To evaluate the filter performance, we use mammographic images from the mini-MIAS database which we have damaged by adding Gaussian, impulsive and speckle noises of different magnitudes. As a result, the proposed method obtains a good performance in most of the different types of noise.

Information Retrieval and Text Categorization with Semantic Indexing

In this paper, we present the effect of the semantic indexing using WordNet senses on the Information Retrieval (IR) and Text Categorization (TC) tasks. The documents have been sense-tagged using a Word Sense Disambiguation (WSD) system based on Specialized Hidden Markov Models (SHMMs). The preliminary results showed that a small improvement of the performance was obtained only in the TC task.

Smooth control of Adaptive Media Playout to acquire IDMS in cluster-based applications

Many emerging multimedia applications enable independent groups (or clusters) of consumers to interact between them and share services within the context of simultaneous media content consumption. Owing to the semantic, spatial or temporal dependency among the involved media streams, concurrently synchronized playout points must be ensured so as not to spoil the user experience on such interaction. This paper presents the combination of an evolved Inter-Destination Multimedia Synchronization (IDMS) approach and a new designed Adaptive Media Playout (AMP) scheme that aims to smoothly adjust the playout timing of each one of the receivers in a specific cluster, if an asynchrony threshold between their playout states is exceeded. Simulation results prove the feasibility of such proposals, by employing several dynamic master selection policies, to maintain an overall synchronization status (within allowable limits) in each cluster, while minimizing the occurrence of long-term playout discontinuities (such as skips/pauses) which are subjectively more annoying to users than small variations in the media playout rate.