System-level power-performance tradeoffs for reconfigurable computing

In this paper, we propose a configuration-aware data-partitioning approach for reconfigurable computing. We show how the reconfiguration overhead impacts the data-partitioning process. Moreover, we explore the system-level power-performance tradeoffs available when implementing streaming embedded applications on fine-grained reconfigurable architectures. For a certain group of streaming applications, we show that an efficient hardware/software partitioning algorithm is required when targeting low power. However, if the application objective is performance, then we propose the use of dynamically reconfigurable architectures. We propose a design methodology that adapts the architecture and algorithms to the application requirements. The methodology has been proven to work on a real research platform based on Xilinx devices. Finally, we have applied our methodology and algorithms to the case study of image sharpening, which is required nowadays in digital cameras and mobile phones.     

Automatic acquisition of syntactic verb classes with basic resources

This paper describes a methodology aimed at grouping Catalan verbs according to their syntactic behavior. Our goal is to acquire a small number of basic classes with a high level of accuracy, using minimal resources. Information on syntactic class, expensive and slow to compile by hand, is useful for any NLP task requiring specific lexical information. We show that it is possible to acquire this kind of information using only a POS-tagged corpus. We perform two clustering experiments. The first one aims at classifying verbs into transitive, intransitive and verbs alternating with a se-construction. Our system achieves an average 0.84 F-score, for a task with a 0.33 baseline. The second experiment aims at further distinguishing among pure intransitives and verbs bearing a prepositional object. The baseline for the task is 0.51 and the upperbound 0.98. The system achieves an average 0.88 F-score.     

Dynamic utility and price based radio resource management for rate adaptive traffic

This paper explores analytical Radio Resource Management models where the relationship between users and services is mapped through utility functions. Compared to other applications of these models to networking, we focus in particular on specific aspects of multimedia systems with adaptive traffic, and propose a novel framework for describing and investigating dynamic allocation of resources in wireless networks. In doing so, we also consider economic aspects, such as the financial needs of the provider and the users’ reaction to prices. As an example of how our analytical tool can be used, in this paper we compare different classes of RRM strategies, e.g., Best Effort vs. Guaranteed Performance, for which we explore the relationships between Radio Resource Allocation, pricing, provider’s revenue, network capacity and users’ satisfaction. Finally, we present a discussion about Economic Admission Control, which can be applied in Best Effort scenarios to further improve the performance. Part of this work has been presented at the conference ACM/IEEE MSWiM 2004, Venice (Italy). Leonardo Badia received a Laurea degree (with honors) in electrical engineering and a Ph.D. in information engineering from the University of Ferrara, Italy, in 2000 and 2004, respectively. He was a Research Fellow at the University of Ferrara from 2001 to 2006. During these years, he also had collaborations with the University of Padova, Italy, and Wireless@KTH, Royal Institute of Technology, Stockholm, Sweden. In 2006, he joined the “Institutions Markets Technologies” (IMT) Institute for Advanced Studies, Lucca, Italy, where he is currently a Research Fellow. His research interests include wireless ad hoc and mesh networks, analysis of transmission protocols, optimization tools and economic models applied to radio resource management. Michele Zorzi received a Laurea degree and a Ph.D. in electrical engineering from the University of Padova in 1990 and 1994, respectively. During academic year 1992–1993, he was on leave at UCSD, attending graduate courses and doing research on multiple access in mobile radio networks. In 1993 he joined the faculty of the Dipartimento di Elettronica e Informazione, Politecnico di Milano, Italy. After spending three years with the Center for Wireless Communications at UCSD, in 1998 he joined the School of Engineering of the University of Ferrara, Italy, where he became a professor in 2000. Since November 2003 he has been on the faculty at the Information Engineering Department of the University of Padova. His present research interests include performance evaluation in mobile communications systems, random access in mobile radio networks, ad hoc and sensor networks, energy constrained communications protocols, and broadband wireless access. He was Editor-In-Chief of IEEE Wireless Communications, 2003–2005, and currently serves on the Editorial Boards of IEEE Transactions on Communications, IEEE Transactions on Wireless Communications, Wiley’s Journal of Wireless Communications and Mobile Computing, and ACM/URSI/Kluwer Journal of Wireless Networks, and on the Steering Committee of the IEEE Transactions on Mobile Computing. He has also been a Guest Editor of special issues in IEEE Personal Communications (Energy Management in Personal Communications Systems) and IEEE Journal on Selected Areas in Communications (Multimedia Network Radios).     

Performance of computationally intensive parameter sweep applications on Internet‐based Grids of computers: the mapping of molecular potential energy hypersurfaces

This work focuses on the use of computational Grids for processing the large set of jobs arising in parameter sweep applications. In particular, we tackle the mapping of molecular potential energy hypersurfaces. For computationally intensive parameter sweep problems, performance models are developed to compare the parallel computation in a multiprocessor system with the computation on an Internet‐based Grid of computers. We find that the relative performance of the Grid approach increases with the number of processors, being independent of the number of jobs. The experimental data, obtained using electronic structure calculations, fit the proposed performance expressions accurately. To automate the mapping of potential energy hypersurfaces, an application based on GRID superscalar is developed. It is tested on the prototypical case of the internal dynamics of acetone. Copyright © 2006 John Wiley & Sons, Ltd.     

Arabic stop consonants characterisation and classification using the normalized energy in frequency bands

In general, speech is made with sequences of consonants (fricatives, nasals and stops), vowels and glides. The classification of the stop consonants remains one of the most challenging problems in speech recognition. In this paper, we propose a new approach based on the normalized energy in frequency bands in the release and closure phases in order to characterize and classify the Arabic stop consonants (/b/, /d/, /t/, /k/ and /q/) and to recognize the CV syllable. Classification experiments were performed using decision algorithms on stop consonants C and CV syllables extracted from an Arabic corpus. The results yielded to an overall stop consonants classification of 90.27% and syllables CV recognition upper than 90% for all stops.     

COMPSs-Mobile: Parallel Programming for Mobile Cloud Computing

The advent of the Cloud and the popularization of mobile devices have led us to a shift in computing access where users have an interactive display, and heavy computations run remotely, in the Cloud servers. COMPSs-Mobile is a framework that aims to ease the development of energy-efficient and high-performing applications for this kind of environment. The framework provides an infrastructure-unaware programming model that allows developers to code regular Android applications whose computation is transparently parallelized and partially offloaded to remote resources. This paper gives an overview of the programming model and describes the internal components of the toolkit which supports it focusing on the offloading and checkpointing mechanisms. It also presents the results of some tests conducted to evaluate the behavior of the solution and to measure the potential benefits in Android applications.     

Algebraic Pressure Segregation Methods for the Incompressible Navier-Stokes Equations

This work is an overview of algebraic pressure segregation methods for the incompressible Navier-Stokes equations. These methods can be understood as an inexact LU block factorization of the original system matrix. We have considered a wide set of methods: algebraic pressure correction methods, algebraic velocity correction methods and the Yosida method. Higher order schemes, based on improved factorizations, are also introduced. We have also explained the relationship between these pressure segregation methods and some widely used preconditioners, and we have introduced predictor-corrector methods, one-loop algorithms where nonlinearity and iterations towards the monolithic system are coupled. The first author’s research was supported by the European Community through the Marie Curie contract NanoSim (MOIF-CT-2006-039522).     

Comparison of Bus Network Structures in Face of Urban Dispersion for a Ring-Radial City

Networks and Spatial Economics - This paper extends the discussion about the bus network design in face of the mobility patterns associated with different degrees of urban dispersion. Based on an...