Resource contention in shared-memory multiprocessors: A parameterized performance degradation model

A standard metric conventionally employed to compare the performance of different multiprocessor systems is speedup. Although providing a measure of the improvement in execution speed achievable on a system, this metric does not yield any insight into the factors responsible for limiting the potential improvement in speed. This paper studies the performance degradation in shared-memory multiprocessors as a result of contention for shared-memory resources. A replicate workload framework with a flexible mechanism for workload specification is proposed for measuring performance. Two normalized performance metrics—efficiency and overhead factor—are introduced to quantify the factors limiting performance and facilitate comparison across architectures. Finally, the proposed model is employed to measure and compare the performance of three contemporary shared-memory systems, with special emphasis on the newly released BBN Butterfly-II (TC2000), currently undergoing Beta test.     

Les enjeux économiques de ľinterconnexion des réseaux

The network interconnection and its regulation consist in solving the following dilemma: increase competition and preserve the universal service through access charges, which symbolizes today institutional organization within the telecommunication industry. This paper presents some of the economic and social factors that drive the interconnection policies namely ona (open network architecture) in the United States, or onp (open network provision) in Europe. In the first section, we list some social and economical issues related to open network policies. In the second section, we study the different answers brought up by the regulator through alternative interconnection price formulas. In conclusion, we discuss the stakes and risks of interconnection, while the technological evolution of network introduces intelligent software in switching équipement and implements the tremendous abilities of the digital broadband networks.     

Complex system reliability modelling with Dynamic Object Oriented Bayesian Networks (DOOBN)

Nowadays, the complex manufacturing processes have to be dynamically modelled and controlled to optimise the diagnosis and the maintenance policies. This article presents a methodology that will help developing Dynamic Object Oriented Bayesian Networks (DOOBNs) to formalise such complex dynamic models. The goal is to have a general reliability evaluation of a manufacturing process, from its implementation to its operating phase. The added value of this formalisation methodology consists in using the a priori knowledge of both the system's functioning and malfunctioning. Networks are built on principles of adaptability and integrate uncertainties on the relationships between causes and effects. Thus, the purpose is to evaluate, in terms of reliability, the impact of several decisions on the maintenance of the system. This methodology has been tested, in an industrial context, to model the reliability of a water (immersion) heater system.     

Microwave heating of poly(ethylene terephthalate) bottle preforms used in the thermoforming process

Thermoforming (free blowing) of poly(ethylene terephthalate) preforms was successfully and quickly performed in a rotating system designed for dielectric hysteresis heating. Temperature profile modeling was carried out with the amorphous poly(ethylene terephthalate) permittivity at different temperatures. The Maxwell and heat equations were used to determine the best profile and power tuning. The determination of the theoretical boundary conditions was accomplished by the adjustment of the numerical transient external surface wall temperature with experimental infrared pyrometry results. In comparison with infrared, microwaves allowed high power density absorption inside the perform wall without a dramatic temperature gradient. Consequently, the heat blowing stage could be accelerated, and the process took at least 5 times less energy than infrared heating. Industrial applications involve the integration of the molding step and the design of the overall process. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

Homogeneous Lyapunov function for homogeneous continuous vector field

The goal of this article is to provide a construction of a homogeneous Lyapunov function associated with a system of differential equations , under the hypotheses: (1) vanishes at x = 0 and is homogeneous; (2) the zero solution of this system is locally asymptotically stable. Moreover, the Lyapunov function tends to infinity with x, and belongs to , with as large as wanted. As application to the theory of homogeneous systems, we present two well known results of robustness, in a slightly extended form, and with simpler proofs.     

Intrinsic nonlinear multiscale image decomposition: A 2D empirical mode decomposition-like tool

Many works have been achieved for analyzing images with a multiscale approach. In this paper, an intrinsic and nonlinear multiscale image decomposition is proposed, based on partial differential equations (PDEs) and the image frequency contents. Our model is inspired from the 2D empirical mode decomposition (EMD) for which a theoretical study is quite nonexistent, mainly because the algorithm is based on heuristic and ad hoc elements making its mathematical study hard. This work has three main advantages. Firstly, we prove that the 2D sifting process iterations are consistent with the resolution of a nonlinear PDE, by considering continuous morphological operators to build local upper and lower envelopes of the image extrema. In addition to the fact that now differential calculus can be performed on envelopes, the introduction of such morphological filters eliminates the interpolation dependency that also terribly suffers the method. Also, contrary to former 2D empirical modes, precise mathematical definition for a class of functions are now introduced thanks to the nonlinear PDE derived from the consistency result, and their characterization on the basis of Meyer spaces. Secondly, an intrinsic multiscale image decomposition is introduced based on the image frequency contents; the proposed approach almost captures the essence and philosophy of the 2D EMD and is linked to the well known Absolutely Minimizing Lipschitz Extension model. Lastly, the proposed multiscale decomposition allows a reconstruction of images. The filterbank capability of the new multiscale decomposition algorithm is shown both on synthetic and real images, and results show that our proposed approach improves a lot on the 2D EMD. Moreover, the complexity of the proposed multiscale decomposition is very reduced compared to the 2D EMD by avoiding the surface interpolation approach, which is the core of all 2D EMD algorithms and is very time consuming. For that purpose also, our work will then be a great benefit; especially, in higher dimension spaces.