Combining static analysis and profiling for estimating execution times in logic programs

Effective static analyses have been proposed which allow inferring functions which bound the number of resolutions or reductions. These have the advantage of being independent from the platform on which the programs are executed and such bounds have been shown useful in a number of applications, such as granularity control in parallel execution. On the other hand, in certain distributed computation scenarios where different platforms come into play, with each platform having different capabilities, it is more interesting to express costs in metrics that include the characteristics of the platform. In particular, it is specially interesting to be able to infer upper and lower bounds on actual execution time. With this objective in mind, we propose a method which allows inferring upper and lower bounds on the execution times of procedures of a program in a given execution platform. The approach combines compile-time cost bounds analysis with a one-time profiling of the platform in order to determine the values of certain constants for that platform. These constants calibrate a cost model which from then on is able to compute statically time bound functions for procedures and to predict with a significant degree of accuracy the execution times of such procedures in the given platform. The approach has been implemented and integrated in the CiaoPP system.

Issues in implementing ACE: A stack copying based and-or parallel system

We discuss several issues involved in the implementation of ACE, a model capable of exploiting both And-parallelism and Or-parallelism in Prolog in a unified framework. The Orparallel model that ACE employs is based on the idea of stack-copying developed for Muse, while the model of independent And-parallelism is based on the distributed stack approach of &-Prolog. We discuss the organization of the workers, a number of sharing assumtions, techniques for work load detection, and issues relaed to which parts need to be copied when a flexible and-scheduling strategy is used.

A review on probabilistic graphical models in evolutionary computation

Thanks to their inherent properties, probabilistic graphical models are one of the prime candidates for machine learning and decision making tasks especially in uncertain domains. Their capabilities, like representation, inference and learning, if used effectively, can greatly help to build intelligent systems that are able to act accordingly in different problem domains. Evolutionary algorithms is one such discipline that has employed probabilistic graphical models to improve the search for optimal solutions in complex problems. This paper shows how probabilistic graphical models have been used in evolutionary algorithms to improve their performance in solving complex problems. Specifically, we give a survey of probabilistic model building-based evolutionary algorithms, called estimation of distribution algorithms, and compare different methods for probabilistic modeling in these algorithms.

GreenDisc: a HW/SW energy optimization framework in globally distributed computation

In recent future, wireless sensor networks (WSNs) will experience a broad high-scale deployment (millions of nodes in the national area) with multiple information sources per node, and with very specific requirements for signal processing. In parallel, the broad range deployment of WSNs facilitates the definition and execution of ambitious studies, with a large input data set and high computational complexity. These computation resources, very often heterogeneous and driven on-demand, can only be satisfied by high-performance Data Centers (DCs). The high economical and environmental impact of the energy consumption in DCs requires aggressive energy optimization policies. These policies have been already detected but not successfully proposed. In this context, this paper shows the following on-going research lines and obtained results. In the field of WSNs: energy optimization in the processing nodes from different abstraction levels, including reconfigurable application specific architectures, efficient customization of the memory hierarchy, energy-aware management of the wireless interface, and design automation for signal processing applications. In the field of DCs: energy-optimal workload assignment policies in heterogeneous DCs, resource management policies with energy consciousness, and efficient cooling mechanisms that will cooperate in the minimization of the electricity bill of the DCs that process the data provided by the WSNs.

GreenDisc: a HW/SW energy optimization framework in globally distributed computation

In recent future, wireless sensor networks ({WSNs}) will experience a broad high-scale deployment (millions of nodes in the national area) with multiple information sources per node, and with very specific requirements for signal processing. In parallel, the broad range deployment of {WSNs} facilitates the definition and execution of ambitious studies, with a large input data set and high computational complexity. These computation resources, very often heterogeneous and driven on-demand, can only be satisfied by high-performance Data Centers ({DCs}). The high economical and environmental impact of the energy consumption in {DCs} requires aggressive energy optimization policies. These policies have been already detected but not successfully proposed. In this context, this paper shows the following on-going research lines and obtained results. In the field of {WSNs}: energy optimization in the processing nodes from different abstraction levels, including reconfigurable application specific architectures, efficient customization of the memory hierarchy, energy-aware management of the wireless interface, and design automation for signal processing applications. In the field of {DCs}: energy-optimal workload assignment policies in heterogeneous {DCs}, resource management policies with energy consciousness, and efficient cooling mechanisms that will cooperate in the minimization of the electricity bill of the DCs that process the data provided by the WSNs.

Molecular basis of salt tolerance in Physcomitrella Patens model plant: potassium homeostasis and physiological roles of chx transporters

El suelo salino impone un estrés abiótico importante que causa graves problemas en la agricultura ya que la mayoría de los cultivos se ven afectados por la salinidad debido a efectos osmóticos y tóxicos. Por ello, la contaminación y la escasez de agua dulce, la salinización progresiva de tierras y el aumento exponencial de la población humana representan un grave problema que amenaza la seguridad alimentaria mundial para las generaciones futuras. Por lo tanto, aumentar la tolerancia a la salinidad de los cultivos es un objetivo estratégico e ineludible para garantizar el suministro de alimentos en el futuro. Mantener una óptima homeostasis de K+ en plantas que sufren estrés salino es un objetivo importante en el proceso de obtención de plantas tolerantes a la salinidad. Aunque el modelo de la homeostasis de K+ en las plantas está razonablemente bien descrito en términos de entrada de K+, muy poco se sabe acerca de los genes implicados en la salida de K+ o de su liberación desde la vacuola. En este trabajo se pretende aclarar algunos de los mecanismos implicados en la homeostasis de K+ en plantas. Para ello se eligió la briofita Physcomitrella patens, una planta no vascular de estructura simple y de fase haploide dominante que, entre muchas otras cualidades, hacen que sea un modelo ideal. Lo más importante es que no sólo P. patens es muy tolerante a altas concentraciones de Na+, sino que también su posición filogenética en la evolución de las plantas abre la posibilidad de estudiar los cambios claves que, durante el curso de la evolución, se produjeron en las diversas familias de los transportadores de K+. Se han propuesto varios transportadores de cationes como candidatos que podrían tener un papel en la salida de K+ o su liberación desde la vacuola, especialmente miembros de la familia CPA2 que contienen las familias de transportadores KEA y CHX. En este estudio se intenta aumentar nuestra comprensión de las funciones de los transportadores de CHX en las células de las plantas usando P. patens, como ya se ha dicho. En esta especie, se han identificado cuatro genes CHX, PpCHX1-4. Dos de estos genes, PpCHX1 y PpCHX2, se expresan aproximadamente al mismo nivel que el gen PpACT5, y los otros dos genes muestran una expresión muy baja. La expresión de PpCHX1 y PpCHX2 en mutantes de Escherichia coli defectivos en el transporte de K+ restauraron el crecimiento de esta cepa en medios con bajo contenido de K+, lo que viii sugiere que la entrada de K+ es energizada por un mecanismo de simporte con H+. Por otra parte, estos transportadores suprimieron el defecto asociado a la mutación kha1 en Saccharomyces cerevisiae, lo que sugiere que podrían mediar un antiporte en K+/H+. La proteína PpCHX1-GFP expresada transitoriamente en protoplastos de P. patens co-localizó con un marcador de Golgi. En experimentos similares, la proteína PpCHX2-GFP localizó aparentemente en la membrana plasmática y tonoplasto. Se construyeron las líneas mutantes simples de P. patens ΔPpchx1 y ΔPpchx2, y también el mutante doble ΔPpchx2 ΔPphak1. Los mutantes simples crecieron normalmente en todas las condiciones ensayadas y mostraron flujos de entrada normales de K+ y Rb+; la mutación ΔPpchx2 no aumentó el defecto de las plantas ΔPphak1. En experimentos a largo plazo, las plantas ΔPpchx2 mostraron una retención de Rb+ ligeramente superior que las plantas silvestres, lo que sugiere que PpCHX2 promueve la transferencia de Rb+ desde la vacuola al citosol o desde el citosol al medio externo, actuando en paralelo con otros transportadores. Sugerimos que transportadores de K+ de varias familias están involucrados en la homeostasis de pH de orgánulos ya sea mediante antiporte K+/H+ o simporte K+-H+.ix ABSTRACT Soil salinity is a major abiotic stress causing serious problems in agriculture as most crops are affected by it. Moreover, the contamination and shortage of freshwater, progressive land salinization and exponential increase of human population aggravates the problem implying that world food security may not be ensured for the next generations. Thus, a strategic and an unavoidable goal would be increasing salinity tolerance of plant crops to secure future food supply. Maintaining an optimum K+ homeostasis in plants under salinity stress is an important trait to pursue in the process of engineering salt tolerant plants. Although the model of K+ homeostasis in plants is reasonably well described in terms of K+ influx, very little is known about the genes implicated in K+ efflux or release from the vacuole. In this work, we aim to clarify some of the mechanisms involved in K+ homeostasis in plants. For this purpose, we chose the bryophyte plant Physcomitrella patens, a nonvascular plant of simple structure and dominant haploid phase that, among many other characteristics, makes it an ideal model. Most importantly, not only P. patens is very tolerant to high concentrations of Na+, but also its phylogenetic position in land plant evolution opens the possibility to study the key changes that occurred in K+ transporter families during the course of evolution. Several cation transporter candidates have been proposed to have a role in K+ efflux or release from the vacuole especially members of the CPA2 family which contains the KEA and CHX transporter families. We intended in this study to increase our understanding of the functions of CHX transporters in plant cells using P. patens, in which four CHX genes have been identified, PpCHX1-4. Two of these genes, PpCHX1 and PpCHX2, are expressed at approximately the same level as the PpACT5 gene, but the other two genes show an extremely low expression. PpCHX1 and PpCHX2 restored growth of Escherichia coli mutants on low K+-containing media, suggesting they mediated K+ uptake that may be energized by symport with H+. In contrast, these genes suppressed the defect associated to the kha1 mutation in Saccharomyces cerevisiae, which suggest that they might mediate K+/H+ antiport. PpCHX1-GFP protein transiently expressed in P. patens protoplasts co-localized with a Golgi marker. In similar experiments, the PpCHX2-GFP protein appeared to localize to tonoplast and plasma x membrane. We constructed the ΔPpchx1 and ΔPpchx2 single mutant lines, and the ΔPpchx2 ΔPphak1 double mutant. Single mutant plants grew normally under all the conditions tested and exhibited normal K+ and Rb+ influxes; the ΔPpchx2 mutation did not increase the defect of ΔPphak1 plants. In long-term experiments, ΔPpchx2 plants showed a slightly higher Rb+ retention than wild type plants, which suggests that PpCHX2 mediates the transfer of Rb+ from either the vacuole to the cytosol or from the cytosol to the external medium in parallel with other transporters. We suggest that K+ transporters of several families are involved in the pH homeostasis of organelles by mediating either K+/H+ antiport or K+-H+ symport.

Transformation�based implementation and optimization of programs exploiting the basic Andorra model.

The characteristics of CC and CLP systems are in principle very dierent However a recent trend towards convergence in the implementation techniques for these systems can be observed While CLP and Prolog systems have been incorporating capabilities to deal with userdened suspension and coroutining CC compilers have been trying to coalesce negrained tasks into coarsergrained sequential threads This convergence of techniques opens up the possibility of having a general purpose kernel language and abstract machine to serve as a compilation target for a variety of userlevel languages We propose a transformation technique directed towards such an objective In particular we report on techniques to support the Andorra computational model essentially emulating the AndorraI system via program transformation into a sequential language with delay primitives The system is automatic comprising an optional program analyzer and a basic transformer to the kernel language It turns out that a simple parallel CLP or Prolog system with dynamic scheduling is sucient as a kernel language for this purpose The preliminary results are quite encouraging performance of the resulting system is comparable to the current AndorraI implementation.

Métodos acotados de aplicación de reglas de evolución para la implementación de Sistemas P de Transición

La característica fundamental de la Computación Natural se basa en el empleo de conceptos, principios y mecanismos del funcionamiento de la Naturaleza. La Computación Natural -y dentro de ésta, la Computación de Membranas- surge como una posible alternativa a la computación clásica y como resultado de la búsqueda de nuevos modelos de computación que puedan superar las limitaciones presentes en los modelos convencionales. En concreto, la Computación de Membranas se originó como un intento de formular un nuevo modelo computacional inspirado en la estructura y el funcionamiento de las células biológicas: los sistemas basados en este modelo constan de una estructura de membranas que actúan a la vez como separadores y como canales de comunicación, y dentro de esa estructura se alojan multiconjuntos de objetos que evolucionan de acuerdo a unas determinadas reglas de evolución. Al conjunto de dispositivos contemplados por la Computación de Membranas se les denomina genéricamente como Sistemas P. Hasta el momento los Sistemas P sólo han sido estudiados a nivel teórico y no han sido plenamente implementados ni en medios electrónicos, ni en medios bioquímicos, sólo han sido simulados o parcialmente implementados. Por tanto, la implantación de estos sistemas es un reto de investigación abierto. Esta tesis aborda uno de los problemas que debe ser resuelto para conseguir la implantación de los Sistemas P sobre plataformas hardware. El problema concreto se centra en el modelo de los Sistemas P de Transición y surge de la necesidad de disponer de algoritmos de aplicación de reglas que, independientemente de la plataforma hardware sobre la que se implementen, cumplan los requisitos de ser no deterministas, masivamente paralelos y además su tiempo de ejecución esté estáticamente acotado. Como resultado se ha obtenido un conjunto de algoritmos (tanto para plataformas secuenciales, como para plataformas paralelas) que se adecúan a las diferentes configuraciones de los Sistemas P. ABSTRACT The main feature of Natural Computing is the use of concepts, principles and mechanisms inspired by Nature. Natural Computing and within it, Membrane Computing emerges as an potential alternative to conventional computing and as from the search for new models of computation that may overcome the existing limitations in conventional models. Specifically, Membrane Computing was created to formulate a new computational paradigm inspired by the structure and functioning of biological cells: it consists of a membrane structure, which acts as separators as well as communication channels, and within this structure are stored multisets of objects that evolve according to certain evolution rules. The set of computing devices addressed by Membrane Computing are generically known P systems. Up to now, no P systems have been fully implemented yet in electronic or biochemical means. They only have been studied in theory, simulated or partially implemented. Therefore, the implementation of these systems is an open research challenge. This thesis addresses one of the problems to be solved in order to deploy P systems on hardware platforms. This specific problem is focused on the Transition P System model and emerges from the need of providing application rules algorithms that independently on the hardware platform on which they are implemented, meets the requirements of being nondeterministic, massively parallel and runtime-bounded. As a result, this thesis has developed a set of algorithms for both platforms, sequential and parallel, adapted to all possible configurations of P systems.

A stochastic model updating method for parameter variability quantification based on response surface models and Monte Carlo simulation

Stochastic model updating must be considered for quantifying uncertainties inherently existing in real-world engineering structures. By this means the statistical properties,instead of deterministic values, of structural parameters can be sought indicating the parameter variability. However, the implementation of stochastic model updating is much more complicated than that of deterministic methods particularly in the aspects of theoretical complexity and low computational efficiency. This study attempts to propose a simple and cost-efficient method by decomposing a stochastic updating process into a series of deterministic ones with the aid of response surface models and Monte Carlo simulation. The response surface models are used as surrogates for original FE models in the interest of programming simplification, fast response computation and easy inverse optimization. Monte Carlo simulation is adopted for generating samples from the assumed or measured probability distributions of responses. Each sample corresponds to an individual deterministic inverse process predicting the deterministic values of parameters. Then the parameter means and variances can be statistically estimated based on all the parameter predictions by running all the samples. Meanwhile, the analysis of variance approach is employed for the evaluation of parameter variability significance. The proposed method has been demonstrated firstly on a numerical beam and then a set of nominally identical steel plates tested in the laboratory. It is found that compared with the existing stochastic model updating methods, the proposed method presents similar accuracy while its primary merits consist in its simple implementation and cost efficiency in response computation and inverse optimization.

Computational model for local damage assesment of structures

In the last years many studies have been developed to analyze the seismic behavior throug the damage concept. In fact, the evaluation of the structural damage is important in order to quantify the safety of new and existing structures and, also, to establish a framework for seismic retrofitting decision making of structures. Most proposed models are based on a post-earthquake evaluation in such a way they uncouple the computation of the structural response from that of damage. However, there are other models which include explicity the existing coupling between the degradation and the structural mechanical beaviour. Those models are closer to the physical reality and its formulation is based on the principles of Continuum Damage Mechanics. In the present work, a coupled model is formulated using a simplified application of the Continuum Damage Mechanics to the analysis of frames and allows its representation in standard finite element programs. This work is part of the activities developed by the Structural Mechanics Department (UPM) within ICONS (European Research Project on Innovative Seismic Design Concepts for New and Existing Structures).

An Inexpensive Method for Kinematic Calibration of a Parallel Robot by Using One Hand-Held Camera as Main Sensor

This paper presents a novel method for the calibration of a parallel robot, which allows a more accurate configuration instead of a configuration based on nominal parameters. It is used, as the main sensor with one camera installed in the robot hand that determines the relative position of the robot with respect to a spherical object fixed in the working area of the robot. The positions of the end effector are related to the incremental positions of resolvers of the robot motors. A kinematic model of the robot is used to find a new group of parameters, which minimizes errors in the kinematic equations. Additionally, properties of the spherical object and intrinsic camera parameters are utilized to model the projection of the object in the image and thereby improve spatial measurements. Finally, several working tests, static and tracking tests are executed in order to verify how the robotic system behaviour improves by using calibrated parameters against nominal parameters. In order to emphasize that, this proposed new method uses neither external nor expensive sensor. That is why new robots are useful in teaching and research activities.

PIC computation of electron current collection to a moving bare tether in the mesothermal condition

In tethered satellite technology, it is important to estimate how many electrons a spacecraft can collect from its ambient plasma by a bare electrodynamic tether. The analysis is however very difficult because of the small but significant Geo-magnetic field and the spacecraft’s relative motion to both ions and electrons. The object of our work is the development of a numerical method, for this purpose. Particle-In-Cell (PIC) method, for the calculation of electron current to a positive bare tether moving at orbital velocity in the ionosphere, i.e. in a flowing magnetized plasma under Maxwellian collisionless conditions. In a PIC code, a number of particles are distributed in phase space and the computational domain has a grid on which Poisson equation is solved for field quantities. The code uses the quasi-neutrality condition to solve for the local potential at points in the plasma which coincide with the computational outside boundary. The quasi-neutrality condition imposes ne - ni on the boundary. The Poisson equation is solved in such a way that the presheath region can be captured in the computation. Results show that the collected current is higher than the Orbital Motion Limit (OML) theory. The OML current is the upper limit of current collection under steady collisionless unmagnetized conditions. In this work, we focus on the flowing effects of plasma as a possible cause of the current enhancement. A deficit electron density due to the flowing effects has been worked and removed by introducing adiabatic electron trapping into our model.

Numerical model for the study of hydrodynamics on bays and estuaries

A nonlinear implicit finite element model for the solution of two-dimensional (2-D) shallow water equations, based on a Galerkin formulation of the 2-D estuaries hydrodynamic equations, has been developed. Spatial discretization has been achieved by the use of isoparametric, Lagrangian elements. To obtain the different element matrices, Simpson numerical integration has been applied. For time integration of the model, several schemes in finite differences have been used: the Cranck-Nicholson iterative method supplies a superior accuracy and allows us to work with the greatest time step Δt; however, central differences time integration produces a greater velocity of calculation. The model has been tested with different examples to check its accuracy and advantages in relation to computation and handling of matrices. Finally, an application to the Bay of Santander is also presented.

A dynamic factor model for mid-term forecasting of wind power generation

The main objective of this paper is the development and application of multivariate time series models for forecasting aggregated wind power production in a country or region. Nowadays, in Spain, Denmark or Germany there is an increasing penetration of this kind of renewable energy, somehow to reduce energy dependence on the exterior, but always linked with the increaseand uncertainty affecting the prices of fossil fuels. The disposal of accurate predictions of wind power generation is a crucial task both for the System Operator as well as for all the agents of the Market. However, the vast majority of works rarely onsider forecasting horizons longer than 48 hours, although they are of interest for the system planning and operation. In this paper we use Dynamic Factor Analysis, adapting and modifying it conveniently, to reach our aim: the computation of accurate forecasts for the aggregated wind power production in a country for a forecasting horizon as long as possible, particularly up to 60 days (2 months). We illustrate this methodology and the results obtained for real data in the leading country in wind power production: Denmark

Diseño de un Procesador de Membranas Paralelo para los Sistemas P de Transición

La computación con membranas surge como una alternativa a la computación tradicional. Dentro de este campo se sitúan los denominados Sistemas P de Transición que se basan en la existencia de regiones que contienen recursos y reglas que hacen evolucionar a dichos recursos para poder llevar a cada una de las regiones a una nueva situación denominada configuración. La sucesión de las diferentes configuraciones conforman la computación. En este campo, el Grupo de Computación Natural de la Universidad Politécnica de Madrid lleva a cabo numerosas investigaciones al amparo de las cuales se han publicado numerosos artículos y realizado varias tesis doctorales. Las principales vías de investigación han sido, hasta el momento, el estudio del modelo teórico sobre el que se definen los Sistemas P, el estudio de los algoritmos que se utilizan para la aplicación de las reglas de evolución en las regiones, el diseño de nuevas arquitecturas que mejoren las comunicaciones entre las diferentes membranas (regiones) que componen el sistema y la implantación de estos sistemas en dispositivos hardware que pudiesen definir futuras máquinas basadas en este modelo. Dentro de este último campo, es decir, dentro del objetivo de construir finalmente máquinas que puedan llevar a cabo la funcionalidad de la computación con Sistemas P, la presente tesis doctoral se centra en el diseño de dos procesadores paralelos que, aplicando variantes de algoritmos existentes, favorezcan el crecimiento en el nivel de intra-paralelismo a la hora de aplicar las reglas. El diseño y creación de ambos procesadores presentan novedosas aportaciones al entorno de investigación de los Sistemas P de Transición en tanto en cuanto se utilizan conceptos que aunque previamente definidos de manera teórica, no habían sido introducidos en el hardware diseñado para estos sistemas. Así, los dos procesadores mantienen las siguientes características: - Presentan un alto rendimiento en la fase de aplicación de reglas, manteniendo por otro lado una flexibilidad y escalabilidad medias que son dependientes de la tecnología final sobre la que se sinteticen dichos procesadores. - Presentan un alto nivel de intra-paralelismo en las regiones al permitir la aplicación simultánea de reglas. - Tienen carácter universal en tanto en cuanto no depende del carácter de las reglas que componen el Sistema P. - Tienen un comportamiento indeterminista que es inherente a la propia naturaleza de estos sistemas. El primero de los circuitos utiliza el conjunto potencia del conjunto de reglas de aplicación así como el concepto de máxima aplicabilidad para favorecer el intra-paralelismo y el segundo incluye, además, el concepto de dominio de aplicabilidad para determinar el conjunto de reglas que son aplicables en cada momento con los recursos existentes. Ambos procesadores se diseñan y se prueban mediante herramientas de diseño electrónico y se preparan para ser sintetizados sobre FPGAs. ABSTRACT Membrane computing appears as an alternative to traditional computing. P Systems are placed inside this field and they are based upon the existence of regions called “membranes” that contain resources and rules that describe how the resources may vary to take each of these regions to a new situation called "configuration". Successive configurations conform computation. Inside this field, the Natural Computing Group of the Universidad Politécnica of Madrid develops a large number of works and researches that provide a lot of papers and some doctoral theses. Main research lines have been, by the moment, the study of the theoretical model over which Transition P Systems are defined, the study of the algorithms that are used for the evolution rules application in the regions, the design of new architectures that may improve communication among the different membranes (regions) that compose the whole system and the implementation of such systems over hardware devices that may define machines based upon this new model. Within this last research field, this is, within the objective of finally building machines that may accomplish the functionality of computation with P Systems, the present thesis is centered on the design of two parallel processors that, applying several variants of some known algorithms, improve the level of the internal parallelism at the evolution rule application phase. Design and creation of both processors present innovations to the field of Transition P Systems research because they use concepts that, even being known before, were never used for circuits that implement the applying phase of evolution rules. So, both processors present the following characteristics: - They present a very high performance during the application rule phase, keeping, on the other hand, a level of flexibility and scalability that, even known it is not very high, it seems to be acceptable. - They present a very high level of internal parallelism inside the regions, allowing several rule to be applied at the same time. - They present a universal character meaning this that they are not dependent upon the active rules that compose the P System. - They have a non-deterministic behavior that is inherent to this systems nature. The first processor uses the concept of "power set of the application rule set" and the concept of "maximal application" number to improve parallelism, and the second one includes, besides the previous ones, the concept of "applicability domain" to determine the set of rules that may be applied in each moment with the existing resources.. Both processors are designed and tested with the design software by Altera Corporation and they are ready to be synthetized over FPGAs.