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Computational methods for protein structure prediction allow us to determine a three-dimensional structure of a protein based on its pure amino acid sequence. These methods are a very important alternative to costly and slow experimental methods, like X-ray crystallography or Nuclear Magnetic Resonance. However, conventional calculations of protein structure are time-consuming and require ample computational resources, especially when carried out with the use of ab initio methods that rely on physical forces and interactions between atoms in a protein. Fortunately, at the present stage of the development of computer science, such huge computational resources are available from public cloud providers on a pay-as-you-go basis. We have designed and developed a scalable and extensible system, called Cloud4PSP, which enables predictions of 3D protein structures in the Microsoft Azure commercial cloud. The system makes use of the Warecki-Znamirowski method as a sample procedure for protein structure prediction, and this prediction method was used to test the scalability of the system. The results of the efficiency tests performed proved good acceleration of predictions when scaling the system vertically and horizontally. In the paper, we show the system architecture that allowed us to achieve such good results, the Cloud4PSP processing model, and the results of the scalability tests. At the end of the paper, we try to answer which of the scaling techniques, scaling out or scaling up, is better for solving such computational problems with the use of Cloud computing.

The European Grid Infrastructure (EGI) is providing a sustainable pan---European Computing Grid to support e---Science, integrating more than 350 computing resource centers worldwide. One of its main challenges is that the middleware driving this production infrastructure is constantly evolving, as it adapts to the changing needs of the EGI Community. Since the software is provided by external technology providers, it needs to pass through a quality verification process before it is included in the EGI official release called Unified Middleware Distribution (UMD). Therefore, all software components undergo a release process covering the definition of the functionality and quality criteria, the verification of those criteria, and the testing under production environments. This paper details the design, development and implementation of this software validation process. An analysis is performed on several metrics to evaluate the process impact on the stability of the production infrastructure, by capturing malfunctions and other issues at the initial testing phases.

The motivation of this work fits with the general vision to enable e-health for European citizens, irrespective of their social and financial status and their place of residence. Services to be provided include access to a high-quality early diagnostic and prognostic service for the Alzheimer Disease and other forms of dementia, based both on the European Research and Education Networks and the European Grid Infrastructure. The present paper reports on the architecture and services of a Science Gateway developed in the context of the DECIDE project, which aims to support the medical community in its daily duties of patients’ examination and diagnosis. The implementation of the Science Gateway is described with particular focus on the standard technologies adopted to ease the access by non IT-.expert users. The work leverages on an authentication and authorization infrastructure based on Identity Federations and robot certificates and on the adoption of the SAGA standard for middleware-independent Grid interaction. The architecture and the functionalities of the digital repository for medical image storage and analysis are also presented.

Science Gateways are web portal environments targeted for a given community and dedicated to specific scientific needs. Scientists require a different set of tools, applications, visualizations, data integration patterns, to be able to satisfy unique requirements of different research domains. To enable users to benefit from remote computational and storage resources, a web portal framework should support an easy integration and access to the e-Infrastructure. In this paper we present results of our research and development activities leading to the release of the Vine Toolkit framework integrated with Adobe Flex/BlazeDs technologies. It offers a set of unified and abstract APIs for different Grid middleware and a rich graphic presentation layer. Additionally, it automates the integration process with portal frameworks, such as Liferay or GridSphere. Vine Toolkit introduces a concept of subprojects which extend core APIs or define new low level components and web applications. This way, a Science Gateway prototyping process is definitely shortened. Consequently, it allows programmers to build software components that can be reused in a simple manner for different Science Gateways.

Several large-scale Grid infrastructures are currently in operation around the world, federating an impressive collection of computational resources, a wide variety of application software, and hundreds of user communities. To better serve the current and prospective users of Grid infrastructures, it is important to develop advanced software retrieval services that could help users locate software components suitable to their needs. In this paper, we present the design and implementation of Minersoft, a distributed, multi-threaded harvester for application software located in large-scale Grid infrastructures. Minersoft crawls the sites of a Grid infrastructure, discovers installed software resources, annotates them with keyword-rich metadata, and creates inverted indexes that can be used to support full-text software retrieval. We present insights derived from the implementation and deployment of Minersoft on EGEE, one of the largest Grid production services currently in operation. Experimental results show that Minersoft achieves a high performance in crawling EGEE sites and discovering software-related files, and a high efficiency in supporting software retrieval. © 2010 Springer Science+Business Media B.V. 8 2 281 304 Cited By :2

In this paper we present a CPU scavenging architecture suitable for desktop resources, and we study its appropriateness in exploiting the PC Laboratory resources of the Greek School Network and their integration to the existing HellasGrid national infrastructure. School laboratories form an extensive network equipped with computational systems and fast Internet connections. As this infrastructure is utilized at most 8 h per day and 5 days per week, it could be made available during its remaining idle time for computational purposes through the use of Grid technology. The structure and organization of the school laboratories and backbone network enables the CPU scavenging service, as an independent and additional service, which will not violate the operational rules and policies of the school network, while it will add additional resources to the current HellasGrid infrastructure with low adaptation cost.

Biologists, medical experts, biochemical engineers and researchers working on DNA microarray experiments are increasingly turning on Grid computing with the scope of leveraging the Grid’s computing power, immense storage resources, and quality of service to the expedient processing of a wide range of datasets. In this paper we present a combined experience of grid application experts and bioinformatics scientists in deploying a pilot service enabling computationally efficient processing and analysis of data stemming from microarray experiments. This pilot service is accessible over the Hellenic portion of the EGEE grid and has been demonstrated in the scope of several public events. We highlight the process of grid application enablement, grid deployment challenges, as well as lessons learnt from a bi-annual effort to port and deploy a MATLAB DNA microarray application on a production grid. In addition to describing the parallelization of the application, we also emphasize on the development of a distributed federated database for storing and post-processing the results of the microarray experiments. Overall we believe that our experience could be proven valuable not only to microarray data scientists but also to other Grid users that intend to Grid-enable and deploy their applications.