Positivity and conservation of superenergy tensors

Two essential properties of energy-momentum tensors T_{\mu\nu} are their positivity and conservation. This is mathematically formalized by, respectively, an energy condition, as the dominant energy condition, and the vanishing of their divergence \nabla^\mu T_{\mu\nu}=0. The classical Bel and Bel-Robinson superenergy tensors, generated from the Riemann and Weyl tensors, respectively, are rank-4 tensors. But they share these two properties with energy momentum tensors: the Dominant Property (DP) and the divergence-free property in the absence of sources (vacuum). Senovilla defined a universal algebraic construction which generates a basic superenergy tensor T{A} from any arbitrary tensor A. In this construction the seed tensor A is structured as an r-fold multivector, which can always be done. The most important feature of the basic superenergy tensors is that they satisfy automatically the DP, independently of the generating tensor A. In a previous paper we presented a more compact definition of T{A} using the r-fold Clifford algebra. This form for the superenergy tensors allowed to obtain an easy proof of the DP valid for any dimension. In this paper we include this proof. We explain which new elements appear when we consider the tensor T{A} generated by a non-degree-defined r-fold multivector A and how orthogonal Lorentz transformations and bilinear observables of spinor fields are included as particular cases of superenergy tensors. We find some sufficient conditions for the seed tensor A, which guarantee that the generated tensor T{A} is divergence-free. These sufficient conditions are satisfied by some physical fields, which are presented as examples.Comment: 19 pages, no figures. Language and minor changes. Published versio

Overlapping communication and computation by using a hybrid MPI/SMPSs approach

A previous version of this document was submitted for publication by october 2008.Communication overhead is one of the dominant factors that affect performance in high-performance computing systems. To reduce the negative impact of communication, programmers overlap communication and computation by using asynchronous communication primitives. This increases code complexity, requiring more effort to write parallel code and making less readable code. This paper presents the hybrid use of MPI and SMPSs (SMP superscalar), a task-based shared-memory programming model, enhanced with a restart mechanism allowing the programmer to introduce the asynchronism that is necessary to enable the effective communication/computation overlap in a productive way. We demonstrate the hybrid use of MPI/SMPSs with the high-performance LINPACK benchmark, which uses the lookahead technique to overlap communication and computation. MPI/SMPSs improves the performance of a pure MPI with look-ahead by 7,6% on a 1024 processors machine. In addition to better performance, hybrid MPI/SMPSs substantially reduces code complexity, it is less sensitive to network bandwidth and operating system noise, and improves the use of main memory.Postprint (published version

From the Editors: Making Intangible Capital a better review in its third year

Con este número, Intangible Capital inicia su tercer año. Es un buen momento para reflexionar sobre cómo podemos mejorar la revista en este tercer volumen, y de reconsiderar los objetivos marcados en el segundo volumen.With this issue, Intangible Capital reaches its third year. It is a good moment to reflect on how can we make this review better one along this year, and to asses if we have achieved the second year’s goal

Improving the integration of task nesting and dependencies in OpenMP

© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksThe tasking model of OpenMP 4.0 supports both nesting and the definition of dependences between sibling tasks. A natural way to parallelize many codes with tasks is to first taskify the high-level functions and then to further refine these tasks with additional subtasks. However, this top-down approach has some drawbacks since combining nesting with dependencies usually requires additional measures to enforce the correct coordination of dependencies across nesting levels. For instance, most non-leaf tasks need to include a taskwait at the end of their code. While these measures enforce the correct order of execution, as a side effect, they also limit the discovery of parallelism. In this paper we extend the OpenMP tasking model to improve the integration of nesting and dependencies. Our proposal builds on both formulas, nesting and dependencies, and benefits from their individual strengths. On one hand, it encourages a top-down approach to parallelizing codes that also enables the parallel instantiation of tasks. On the other hand, it allows the runtime to control dependencies at a fine grain that until now was only possible using a single domain of dependencies. Our proposal is realized through additions to the OpenMP task directive that ensure backward compatibility with current codes. We have implemented a new runtime with these extensions and used it to evaluate the impact on several benchmarks. Our initial findings show that our extensions improve performance in three areas. First, they expose more parallelism. Second, they uncover dependencies across nesting levels, which allows the runtime to make better scheduling decisions. And third, they allow the parallel instantiation of tasks with dependencies between them.This work is supported by the Spanish Government through Programa Severo Ochoa (SEV-2015-0493), by the Spanish Ministry of Science and Technology (project TIN2015-65316-P) and by the Generalitat de Catalunya (grant 2014-SGR-1051).Peer ReviewedPostprint (author's final draft

El diagnòstic social en els serveis socials bàsics. Fonaments teòrics, normatius i professionals d’una tasca clau

Aquesta publicació analitza els factors implicats en el diagnòstic social a Catalunya, a més del seu marc de referència i les possibles propostes de futur. Es tracta d’una recerca que ha de servir com a punt de partida per implementar noves eines, escales i metodologies que permetin continuar avançant en aquest àmbit. Per fer-ho, s’hi repassen, des d’un punt de vista conceptual, les necessitats socials com a marc de referència de l’objecte dels serveis socials; s’hi revisa l’encàrrec o mandat institucional que tenen els serveis socials, que serveix de referència per a l’actuació professional, fent atenció especial al diagnòstic; s’hi recull la literatura científica sobre els instruments estandarditzats aplicats en el diagnòstic social en treball social i les seves característiques principals; s’hi defineixen les característiques que hauria de tenir el diagnòstic social en els serveis socials bàsics, i s’hi descriu la participació dels usuaris en el procés d’elaboració d’aquest diagnòstic a més del resultat.Diputació de Barcelona. Servei d'Acció Social

A spring search algorithm applied to engineering optimization problems

At present, optimization algorithms are used extensively. One particular type of such algorithms includes random-based heuristic population optimization algorithms, which may be created by modeling scientific phenomena, like, for example, physical processes. The present article proposes a novel optimization algorithm based on Hooke’s law, called the spring search algorithm (SSA), which aims to solve single-objective constrained optimization problems. In the SSA, search agents are weights joined through springs, which, as Hooke’s law states, possess a force that corresponds to its length. The mathematics behind the algorithm are presented in the text. In order to test its functionality, it is executed on 38 established benchmark test functions and weighed against eight other optimization algorithms: a genetic algorithm (GA), a gravitational search algorithm (GSA), a grasshopper optimization algorithm (GOA), particle swarm optimization (PSO), teaching–learning-based optimization (TLBO), a grey wolf optimizer (GWO), a spotted hyena optimizer (SHO), as well as an emperor penguin optimizer (EPO). To test the SSA’s usability, it is employed on five engineering optimization problems. The SSA delivered better fitting results than the other algorithms in unimodal objective function, multimodal objective functions, CEC 2015, in addition to the optimization problems in engineering