Volunteer computing (VC) or distributed computing projects are common in the citizen cyberscience (CCS) community and present extensive opportunities for scientists to make use of computing power donated by volunteers to undertake large-scale scientific computing tasks. VC is generally a noninteractive process for those contributing computing resources to a project, whereas volunteer thinking (VT) or distributed thinking allows volunteers to participate interactively in CCS projects to solve human computation tasks. In this paper, we describe the integration of three tools, the Virtual Atom Smasher (VAS) game developed by CERN, LiveQ, a job distribution middleware, and CitizenGrid, an online platform for hosting and providing computation to CCS projects. This integration demonstrates the combining of VC and VT to help address the scientific and educational goals of games like VAS. This paper introduces the three tools and provides details of the integration process along with further potential usage scenarios for the resulting platform.

Generating and managing input data for large-scale scientific computations has, for many classes of application, always been a challenging process. The emergence of new hardware platforms and increasingly complex scientific models compounds this problem as configuration data can change depending on the underlying hardware and properties of the computation. In this paper we present TemPSS (Templates and Profiles for Scientific Software), a web-based service for building and managing application input files using the concepts of software parameter templates and job profiles. Many complex, distributed applications require the expertise of more than one individual to allow an application to run efficiently on different types of hardware. TemPSS supports collaborative development of application configurations through the ability to save, edit and extend job profiles that define the inputs to an application. We describe the process of defining templates and profiles and the structures used to add an application template to the TemPSS service. We also detail the implementation of the service and describe its interfaces and functionality.

As the capabilities and diversity of computational platforms continue to grow, scientific software is becoming ever more complex in order to target resources effectively. In the libhpc project we are developing a suite of tools and services to simplify job description and execution on heterogeneous infrastructures. This paper presents Nekkloud, a web-based software environment, built on aspects of the libhpc framework, for running the Nektar++ high-order finite element code on both cluster and cloud platforms, while improving the accessibility of the software for end-users and improving the user experience. Nektar++ provides a suite of solvers which span a range of scientific domains, ensuring that Nekkloud has a broad range of use cases. We describe the Nekkloud environment, its use and its ability to target both local campus cluster infrastructure and cloud computing resources, enabling users to make better use of the facilities available to them.

BACKGROUND: Microarray experimentation requires the application of complex analysis methods as well as the use of non-trivial computer technologies to manage the resultant large data sets. This, together with the proliferation of tools and techniques for microarray data analysis, makes it very challenging for a laboratory scientist to keep up-to-date with the latest developments in this field. Our aim was to develop a distributed e-support system for microarray data analysis and management. RESULTS: EMAAS (Extensible MicroArray Analysis System) is a multi-user rich internet application (RIA) providing simple, robust access to up-to-date resources for microarray data storage and analysis, combined with integrated tools to optimise real time user support and training. The system leverages the power of distributed computing to perform microarray analyses, and provides seamless access to resources located at various remote facilities. The EMAAS framework allows users to import microarray data from several sources to an underlying database, to pre-process, quality assess and analyse the data, to perform functional analyses, and to track data analysis steps, all through a single easy to use web portal. This interface offers distance support to users both in the form of video tutorials and via live screen feeds using the web conferencing tool EVO. A number of analysis packages, including R-Bioconductor and Affymetrix Power Tools have been integrated on the server side and are available programmatically through the Postgres-PLR library or on grid compute clusters. Integrated distributed resources include the functional annotation tool DAVID, GeneCards and the microarray data repositories GEO, CELSIUS and MiMiR. EMAAS currently supports analysis of Affymetrix 3' and Exon expression arrays, and the system is extensible to cater for other microarray and transcriptomic platforms. CONCLUSION: EMAAS enables users to track and perform microarray data management and analysis tasks through a single easy-to-use web application. The system architecture is flexible and scalable to allow new array types, analysis algorithms and tools to be added with relative ease and to cope with large increases in data volume.

Abstract We present a proposal for a next‐generation Internet based on chargeable Web Services and Utility Computing realized by a series of open but interacting markets. We demonstrate through the U.K. e‐Science project ‘A Market for Computational Services’ the development of some of the fundamental building blocks for such a Grid computational marketplace. This paper describes the motivation behind this restructuring of the Internet and Web‐based activities as a series of markets and how Grid Computing technologies can contribute towards this goal. The paper details the work undertaken at the London e‐Science Centre to build a framework to create and support negotiable and chargeable Web Services. Copyright © 2007 John Wiley & Sons, Ltd.

Web service-oriented Grid is becoming a standard for achieving loosely coupled distributed computing. Grid services could easily be specified with web-service based interfaces. In this paper we first envisage a realistic Grid market with players such as end-users, brokers and service providers participating co-operatively with an aim to meet requirements and earn profit. End-users wish to use functionality of Grid services by paying the minimum possible price or price confined within a specified budget, brokers aim to maximise profit whilst establishing a SLA (Service Level Agreement) and satisfying end-user needs and at the same time resisting the volatility of service execution time and availability. Service providers aim to develop price models based on end-user or broker demands that will maximise their profit. In this paper we focus on developing stochastic approaches to end-user workflow scheduling that provides QoS guarantees by establishing a SLA. We also develop a novel 2-stage stochastic programming technique that aims at establishing a SLA with end-users regarding satisfying their workflow QoS requirements. We develop a scheduling (workload allocation) technique based on linear programming that embeds the negotiated workflow QoS into the program and model Grid services as generalised queues. This technique is shown to outperform existing scheduling techniques that don't rely on real-time performance information.

Grid Infrastructures are inherently dynamic and unpredictable environments where resource management and scheduling play an important part in ensuring that Grid applications execute while satisfying defined cost and performance constraints. Traditional Grid Scheduling approaches have focused on the scheduling and optimisation of single applications, typically without regard to the state of the other applications and the Grid in general. Advance Reservation-based approaches, in particular, have been quite popular and play a pivotal part in most Grid scheduling architectures. In this paper, we aim to demonstrate that advance reservation-based approaches show uncertainty and their performance is heavily defined by the workload characteristics and resource costs and that these approaches do not scale well as the size of the Grid increases. We demonstrate that an alternative scheduling approach, which borrows from Capacity Planning and Operations Research techniques, can improve upon the performance of the existing Grid schedulers.

This paper describes how the London e-Science Centre cluster MARS, a production 400+ Opteron CPU cluster, was integrated into the production Large Hadron Collider Compute Grid. It describes the practical issues that we encountered when deploying and maintaining this system, and details the techniques that were applied to resolve them. Finally, we provide a set of recommendations based on our experiences for grid software development in general that we believe would make the technology more accessible.

The Grid can be seen as a collection of services each of which performs some functionality. Grid users often submit their applications in the form of workflows with certain Quality of Service (QoS) requirements imposed on the workflows. These workflows detail the composition of Grid services and the level of service required from the Grid. This paper addresses workload allocation techniques for Grid workflows. We model a Grid service as a G/G/1 queue and minimise failures (QoS requirement violation) of jobs by solving a mixed-integer non-linear program (MINLP). The novel approach is evaluated through an experimental simulation and the results confirm that the proposed workload allocation strategy performs considerably better in terms of satisfying QoS requirements of Grid workflows than scheduling algorithms that don't employ such workload allocation techniques.

Unpredictable job execution environments pose a significant barrier to the widespread adoption of the Grid paradigm, because of the innate risk of jobs failing to execute at the time specified by the user. We demonstrate that predictability can be enhanced with a supporting infrastructure consisting of three parts: Performance modelling and monitoring, scheduling which exploits application structure and an advanced reservation resource management service. We prove theoretically that execution times using advanced reservations display less variance than those without. We also show that the costs of advanced reservations can be reduced by providing the system with more accurate performance models. Following the theoretical discussion, we describe the implementation of a fully functional workflow enactment framework that supports advanced reservations and performance modelling thereby providing predictable execution behavior. We further provide experimental results confirming our theoretical models.

The move towards Service Grids, where services are composed to meet the requirements of a user community within constraints specified by the resource provider, present many challenges to service provision and description. To support our research activities in the autonomous composition of services to form a Semantic Service Grid we describe the adoption within ICENI of web services to enable interoperability with the recently proposed Open Grid Services Architecture.

Effective exploitation of computational grids can only be achieved when applications are fully integrated with the grid middleware and the underlying computational resources. Fundamental to this exploitation is information. Information about the structure and behaviour of the application, the capability of the computational and networking resources, and the availability and access to these resources by an individual, a group or an organisation. This paper describes an integrated grid environment that is open, extensible and platform independent. We match a high-level application specification, defined as a network of components, to an optimal combination of the currently available component implementations within our grid environment. We demonstrate the effectiveness of this architecture through high-level specification and solution of a set of linear equations by automatic and optimal resource and implementation selection.

IP problems characterize combinatorial optimization problems where conventional numerical methods based on the hill-climbing technique can not be directly applied. Conventional methods for solving integer programming are based on searching algorithms where heuristics such as branch and bound are applied to reduce the search space. Recently, various algebraic IP solvers have been proposed based on the theory of Grobner bases. The key idea is to encode an IP problem IPA,C into a special ideal associated with the constraint matrix A and the cost (object) function C. An important property of such an encoding is that its Grobner basis corresponds directly to the test set of the IP problem. The main difficulty of these new methods is the size of the Grobner bases generated. In the proposed algorithms, large Grobner bases are caused by either introducing additional variables or by considering the generic IP problem IPA,C. Some improvements have been proposed such as the Hosten and Sturmfels method (GRIN) designed to avoid additional variables and the truncated Grobner basis method of Thomas which computes the Grobner basis for a specific IP problem IPA,C(b) (rather than its generalization IPA,C). In this paper we propose a new algebraic algorithm for solving integer programming problems. The new algorithm, called the Minimized Geometric Buchberger Algorithm (MGBA), combines the Hosten and Sturmfels method (GRIN) and Thomas's truncated GBA to compute the fundamental segments of a IP problem IPA,C directly in its original space and also the truncated Grobner basis for a specific IP problem IPA,C(b). We have carried out experiments to compare this algorithm with others such as the geometric Buchberger algorithm, the truncated geometric Buchberger algorithm, and the algorithm in GRIN. These experiments shows that the new algorithm offers significant performance improvement.

In this paper, we propose a straightforward solution to the problems of compositional parallel programming by using skeletons as the uniform mechanism for structured composition. In our approach parallel programs are constructed by composing procedures in a conventional base language using a set of high-level, pre-defined, functional, parallel computational forms known as skeletons. The ability to compose skeletons provides us with the essential tools for building further and more complex application-oriented skeletons specifying important aspects of parallel computation. Compared with the process network based composition approach, such as PCN, the skeleton approach abstracts away the fine details of connecting communication ports to the higher level mechanism of making data distributions conform, thus avoiding the complexity of using lower level ports as the means of interaction. Thus, the framework provides a natural integration of the compositional programming approach with the data parallel programming paradigm.

Abstract There are many problems associated with current methodologies employed for the development and maintenance of efficient computer systems. This has lead to an interest in both declarative programming languages and parallel computer architectures. These two areas can be combined to produce effective systems by the use of new program development philosophies. In particular, the mathematical basis and inherent parallelism of declarative languages enable formal techniques to be adopted for the development of programs tailored towards parallel machines. This paper provides an overview of one such methodology developed at Imperial College (IC) and presents a case study that illustrates its operation, using the IC Programming/Transformation Environment, and quantifies its benefits using performance prediction equations together with the results of experiments carried out on the ALICE parallel machine.

In recent, separate, work on program transformation and synthesis (Darlington, 1975; 1978; Clark & Sickel, 1977; Clark, 1977) the authors have discovered that a structure of a class of algorithms can be exposed by synthesising each algorithm in the class from a common high level specification, building up a ‘family tree’ of algorithms. In this paper we would like to illustrate this technique by a simple example outlining how four common sorting algorithms, Merge Sort, Quick Sort, Insertion Sort and Seletion Sort, can be synthesised from a common specification. We hope to encourage others to undertake this exercise for other domains.

A system of rules for transforming programs is described, with the programs in the form of recursion equations. An initially very simple, lucid, and hopefully correct program is transformed into a more efficient one by altering the recursion structure. Illustrative examples of program transformations are given, and a tentative implementation is described. Alternative structures for programs are shown, and a possible initial phase for an automatic or semiautomatic program-manipulation system is indicated.