Leveraging simulation practice in industry through use of desktop grid middleware

This chapter focuses on the collaborative use of computing resources to support decision making in industry. Through the use of middleware for desktop grid computing, the idle CPU cycles available on existing computing resources can be harvested and used for speeding-up the execution of applications that have “non-trivial” processing requirements. This chapter focuses on the desktop grid middleware BOINC and Condor, and discusses the integration of commercial simulation software together with free-to-download grid middleware so as to offer competitive advantage to organizations that opt for this technology. It is expected that the low-intervention integration approach presented in this chapter (meaning no changes to source code required) will appeal to both simulation practitioners (as simulations can be executed faster, which in turn would mean that more replications and optimization is possible in the same amount of time) and the management (as it can potentially increase the return on investment on existing resources)

EDGeS: a bridge between desktop grids and service grids

Desktop grids and service grids widely used by their different users communities as efficient solutions for making full use of computing power and achieving loads balances across Intranet or Internet. Nevertheless,little work has been done to combine these two grids technologies together to establish a seamless and vast grid resources pool. In this paper we will present a new European FP7 infrastructure project:EDGeS (enabling desktop grids for e-science), which aim to build technological bridges to facilitate interoperability between desktop grid and service grid. We give also a taxonomy of existing grid systems: desktop grids such as BONIC and XtremWeb, service grids such as EGEE. Then we describe furtherly our solution for identifying translation technologies for porting applications between desktop grids and service grids, and vice versa. There are three themes in our solution, which discuss actual popular bridging technologies, user access issues, and distributed data issues about deployment and application development

High-Performance Cloud Computing: A View of Scientific Applications

Scientific computing often requires the availability of a massive number of computers for performing large scale experiments. Traditionally, these needs have been addressed by using high-performance computing solutions and installed facilities such as clusters and super computers, which are difficult to setup, maintain, and operate. Cloud computing provides scientists with a completely new model of utilizing the computing infrastructure. Compute resources, storage resources, as well as applications, can be dynamically provisioned (and integrated within the existing infrastructure) on a pay per use basis. These resources can be released when they are no more needed. Such services are often offered within the context of a Service Level Agreement (SLA), which ensure the desired Quality of Service (QoS). Aneka, an enterprise Cloud computing solution, harnesses the power of compute resources by relying on private and public Clouds and delivers to users the desired QoS. Its flexible and service based infrastructure supports multiple programming paradigms that make Aneka address a variety of different scenarios: from finance applications to computational science. As examples of scientific computing in the Cloud, we present a preliminary case study on using Aneka for the classification of gene expression data and the execution of fMRI brain imaging workflow.Comment: 13 pages, 9 figures, conference pape

04451 Abstracts Collection -- Future Generation Grids

The Dagstuhl Seminar 04451 "Future Generation Grid" was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl from 1st to 5th November 2004. The focus of the seminar was on open problems and future challenges in the design of next generation Grid systems. A total of 45 participants presented their current projects, research plans, and new ideas in the area of Grid technologies. Several evening sessions with vivid discussions on future trends complemented the talks. This report gives an overview of the background and the findings of the seminar

Grid and P2P middleware for scientific computing systems

Grid and P2P systems have achieved a notable success in the domain of scientific and engineering applications, which commonly demand considerable amounts of computational resources. However, Grid and P2P systems remain still difficult to be used by the domain scientists and engineers due to the inherent complexity of the corresponding middleware and the lack of adequate documentation. In this paper we survey recent developments of Grid and P2P middleware in the context of scientific computing systems. The differences on the approaches taken for Grid and P2P middleware as well as the common points of both paradigms are highlighted. In addition, we discuss the corresponding programming models, languages, and applications.Peer ReviewedPostprint (published version

MAPREDUCE CHALLENGES ON PERVASIVE GRIDS

International audienceThis study presents the advances on designing and implementing scalable techniques to support the development and execution of MapReduce application in pervasive distributed computing infrastructures, in the context of the PER-MARE project. A pervasive framework for MapReduce applications is very useful in practice, especially in those scientific, enterprises and educational centers which have many unused or underused computing resources, which can be fully exploited to solve relevant problems that demand large computing power, such as scientific computing applications, big data processing, etc. In this study, we pro-pose the study of multiple techniques to support volatility and heterogeneity on MapReduce, by applying two complementary approaches: Improving the Apache Hadoop middleware by including context-awareness and fault-tolerance features; and providing an alternative pervasive grid implementation, fully adapted to dynamic environments. The main design and implementation decisions for both alternatives are described and validated through experiments, demonstrating that our approaches provide high reliability when executing on pervasive environments. The analysis of the experiments also leads to several insights on the requirements and constraints from dynamic and volatile systems, reinforcing the importance of context-aware information and advanced fault-tolerance features to provide efficient and reliable MapReduce services on pervasive grids

Service-Oriented Ad Hoc Grid Computing

Subject of this thesis are the design and implementation of an ad hoc Grid infrastructure. The vision of an ad hoc Grid further evolves conventional service-oriented Grid systems into a more robust, more flexible and more usable environment that is still standards compliant and interoperable with other Grid systems. A lot of work in current Grid middleware systems is focused on providing transparent access to high performance computing (HPC) resources (e.g. clusters) in virtual organizations spanning multiple institutions. The ad hoc Grid vision presented in this thesis exceeds this view in combining classical Grid components with more flexible components and usage models, allowing to form an environment combining dedicated HPC-resources with a large number of personal computers forming a "Desktop Grid". Three examples from medical research, media research and mechanical engineering are presented as application scenarios for a service-oriented ad hoc Grid infrastructure. These sample applications are also used to derive requirements for the runtime environment as well as development tools for such an ad hoc Grid environment. These requirements form the basis for the design and implementation of the Marburg ad hoc Grid Environment (MAGE) and the Grid Development Tools for Eclipse (GDT). MAGE is an implementation of a WSRF-compliant Grid middleware, that satisfies the criteria for an ad hoc Grid middleware presented in the introduction to this thesis. GDT extends the popular Eclipse integrated development environment by components that support application development both for traditional service-oriented Grid middleware systems as well as ad hoc Grid infrastructures such as MAGE. These development tools represent the first fully model driven approach to Grid service development integrated with infrastructure management components in service-oriented Grid computing. This thesis is concluded by a quantitative discussion of the performance overhead imposed by the presented extensions to a service-oriented Grid middleware as well as a discussion of the qualitative improvements gained by the overall solution. The conclusion of this thesis also gives an outlook on future developments and areas for further research. One of these qualitative improvements is "hot deployment" the ability to install and remove Grid services in a running node without interrupt to other active services on the same node. Hot deployment has been introduced as a novelty in service-oriented Grid systems as a result of the research conducted for this thesis. It extends service-oriented Grid computing with a new paradigm, making installation of individual application components a functional aspect of the application. This thesis further explores the idea of using peer-to-peer (P2P networking for Grid computing by combining a general purpose P2P framework with a standard compliant Grid middleware. In previous work the application of P2P systems has been limited to replica location and use of P2P index structures for discovery purposes. The work presented in this thesis also uses P2P networking to realize seamless communication accross network barriers. Even though the web service standards have been designed for the internet, the two-way communication requirement introduced by the WSRF-standards and particularly the notification pattern is not well supported by the web service standards. This defficiency can be answered by mechanisms that are part of such general purpose P2P communication frameworks. Existing security infrastructures for Grid systems focus on protection of data during transmission and access control to individual resources or the overall Grid environment. This thesis focuses on security issues within a single node of a dynamically changing service-oriented Grid environment. To counter the security threads arising from the new capabilities of an ad hoc Grid, a number of novel isolation solutions are presented. These solutions address security issues and isolation on a fine-grained level providing a range of applicable basic mechanisms for isolation, ranging from lightweight system call interposition to complete para-virtualization of the operating systems

Towards a lightweight generic computational grid framework for biological research

Background: An increasing number of scientific research projects require access to large-scale computational resources. This is particularly true in the biological field, whether to facilitate the analysis of large high-throughput data sets, or to perform large numbers of complex simulations – a characteristic of the emerging field of systems biology. Results: In this paper we present a lightweight generic framework for combining disparate computational resources at multiple sites (ranging from local computers and clusters to established national Grid services). A detailed guide describing how to set up the framework is available from the following URL: http://igrid-ext.cryst.bbk.ac.uk/portal_guide/. Conclusion: This approach is particularly (but not exclusively) appropriate for large-scale biology projects with multiple collaborators working at different national or international sites. The framework is relatively easy to set up, hides the complexity of Grid middleware from the user, and provides access to resources through a single, uniform interface. It has been developed as part of the European ImmunoGrid project

Enhancing reliability with Latin Square redundancy on desktop grids.

Computational grids are some of the largest computer systems in existence today. Unfortunately they are also, in many cases, the least reliable. This research examines the use of redundancy with permutation as a method of improving reliability in computational grid applications. Three primary avenues are explored - development of a new redundancy model, the Replication and Permutation Paradigm (RPP) for computational grids, development of grid simulation software for testing RPP against other redundancy methods and, finally, running a program on a live grid using RPP. An important part of RPP involves distributing data and tasks across the grid in Latin Square fashion. Two theorems and subsequent proofs regarding Latin Squares are developed. The theorems describe the changing position of symbols between the rows of a standard Latin Square. When a symbol is missing because a column is removed the theorems provide a basis for determining the next row and column where the missing symbol can be found. Interesting in their own right, the theorems have implications for redundancy. In terms of the redundancy model, the theorems allow one to state the maximum makespan in the face of missing computational hosts when using Latin Square redundancy. The simulator software was developed and used to compare different data and task distribution schemes on a simulated grid. The software clearly showed the advantage of running RPP, which resulted in faster completion times in the face of computational host failures. The Latin Square method also fails gracefully in that jobs complete with massive node failure while increasing makespan. Finally an Inductive Logic Program (ILP) for pharmacophore search was executed, using a Latin Square redundancy methodology, on a Condor grid in the Dahlem Lab at the University of Louisville Speed School of Engineering. All jobs completed, even in the face of large numbers of randomly generated computational host failures