Among existing grid middleware approaches, one simple, powerful, and flexible approach consists of using servers available in different administrative domains through the classic client-server or Remote Procedure Call (RPC) paradigm. Network Enabled Servers (NES) implement this model also called GridRPC. Clients submit computation requests to a scheduler whose goal is to find a server available on the grid. The aim of this paper is to give an overview of an NES middleware developed in the GRAAL team called DIET and to describe recent developments. DIET (Distributed Interactive Engineering Toolbox) is a hierarchical set of components used for the development of applications based on computational servers on the grid.

This paper presents the approach chosen within the DIET (Distributed Interactive Engineering Toolbox) project a Grid-RPC environment to allow a resource broker to be tuned for specific application classes. Our design allows the use of generic or application dependent performance measures in a simple and seamless way.

Broadcasting and gossiping are known to be NP(cid:0)hard problems(cid:1) This paper deals with approximation algorithms for such problems(cid:1) We consider both round(cid:0)complexity and step(cid:0)complexity in the telephone model(cid:1) After an overview of previously derived approximation algorithms(cid:2) we present new strategies for broadcasting and gossiping in any graphs(cid:1) Broadcasting strategies are based on the construction of edge(cid:0)disjoint spanning trees(cid:1) Gossiping strategies are based on on(cid:0)line computation of matchings along with the gossiping process(cid:1) Our approximation algorithms for broadcasting o(cid:3)er almost optimal complexity when the number of messages to be broadcasted is large(cid:1) We show that our best approximation algorithm for gossiping performs optimally in many cases(cid:1) We also show experimentally that it can perform faster than the best known handmade algorithms in some particular cases(cid:1)

Jet-impinging diffusion flames were produced and experimentally investigated. The impinging mechanism can enhance the turbulent fluctuations and increase the combustion efficiency greater than that in a single jet flame. Results show that the temperature profiles are consistent and less related with the impinging angles as the Reynolds numbers become greater than 180. The impinging flames exhibit an axial symmetrical column flame at a 45degrees impinging angle due to the flame stretch effect. When increasing the impinging angle to 72 or 90degrees, the radial flow momentum after the jet-to jet impingement may stretch the flame into a nonsymmetrieal shape. The impinging flame was exciting with pulsation to further enhance the mixing rate. Results show that pulsation induces both large and small impinging flame structures. The larger scale structures increase the oxidizer entrain flow to increase the mixing rate. Coupling with the small scale in the flow structure, the pulsation flame obtains higher combustion efficiency and a stable flame.

Recently, the requirements for cellular phones, portable computers, and digital cameras have increased dramatically. A portable electric power supply with long duration and high performance is needed for these products. A proton exchange membrane fuel cell (PEMFC) can meet these requirements and becomes one of the best candidates for a portable power source. It is impossible to install an extra humidifier into small-scale portable electric products for PEMFC water management. This article presents a series of experiments to investigate the performance of a single PEMFC. The effects of different operating conditions on cell performance, including the temperature, pressure, and inlet fuel/oxidant flow rate, are discussed. The test results confirm the positive effect of these parameters on cell performance and power output. The interaction effect of temperature--flow rate is related to the cell humidity, and is important for cell performance. The dry-out problem for a PEMFC is also significantly revealed in the experiments for higher cell temperature and flow rate. Current experimental results can provide useful information for investigating the cell performance and its operating effects under dry fuel/oxidant flow conditions and as a benchmark for simulation work in future studies.

Advances across many fields of study are driving changes in the basic nature of scientific computing applications. Scientists have recognized a growing need to study phenomena by explicitly modeling interactions among individual entities, rather than by simply modeling approximate collective behavior. This entity-level approach has emerged as a promising new direction in a number of scientific fields. One of the challenges inhibiting the entity-level approach is the substantial resource requirements it entails. Unfortunately, such applications exhibit characteristics and behaviors which render traditional parallel computing techniques ineffective. Well-defined methodologies for achieving scalable performance on distributed computing platforms are needed. As an important first step, we present an abstract application model for entity-level applications, and we instantiate it for a case-study immunology application. Our experiments confirm that this model tracks application performance trends sufficiently well to study scheduling issues pertaining to entity-level applications. We identify a scalability problem inherent to the entity-level approach and use our model to quantify the potential performance improvements that remapping strategies may yield.

Author(s): Faerman, Marcio; Su, Alan; Wolski, Richard; Berman, Francine | Abstract: The computational grid is becoming the platform of choice for large-scale distributed data-intensive applications. Accurately predicting the transfer times of remote data files, a fundamental component of such applications, is critical to achieving application performance. In this paper, we introduce a performance prediction method, ARM (Adaptive Regression Modeling), to determine data transfer times for network-bound distributed data-intensive applications. We demonstrate the effectiveness of the ARM method on two distributed data applications, SARA (Synthetic Aperture Radar Atlas) and SRB (Storage Resource Broker), and discuss how it can be used for application scheduling. Our experiments demonstrate that applying the ARM method to these applications predicted data transfer times in wide-area multi-user grid environments with accuracy of 88% or better.Pre-2018 CSE ID: CS1999-0619