SLA-Oriented Resource Provisioning for Cloud Computing: Challenges, Architecture, and Solutions

Cloud computing systems promise to offer subscription-oriented, enterprise-quality computing services to users worldwide. With the increased demand for delivering services to a large number of users, they need to offer differentiated services to users and meet their quality expectations. Existing resource management systems in data centers are yet to support Service Level Agreement (SLA)-oriented resource allocation, and thus need to be enhanced to realize cloud computing and utility computing. In addition, no work has been done to collectively incorporate customer-driven service management, computational risk management, and autonomic resource management into a market-based resource management system to target the rapidly changing enterprise requirements of Cloud computing. This paper presents vision, challenges, and architectural elements of SLA-oriented resource management. The proposed architecture supports integration of marketbased provisioning policies and virtualisation technologies for flexible allocation of resources to applications. The performance results obtained from our working prototype system shows the feasibility and effectiveness of SLA-based resource provisioning in Clouds.Comment: 10 pages, 7 figures, Conference Keynote Paper: 2011 IEEE International Conference on Cloud and Service Computing (CSC 2011, IEEE Press, USA), Hong Kong, China, December 12-14, 201

State-of-the-Art in Parallel Computing with R

R is a mature open-source programming language for statistical computing and graphics. Many areas of statistical research are experiencing rapid growth in the size of data sets. Methodological advances drive increased use of simulations. A common approach is to use parallel computing. This paper presents an overview of techniques for parallel computing with R on computer clusters, on multi-core systems, and in grid computing. It reviews sixteen different packages, comparing them on their state of development, the parallel technology used, as well as on usability, acceptance, and performance. Two packages (snow, Rmpi) stand out as particularly useful for general use on computer clusters. Packages for grid computing are still in development, with only one package currently available to the end user. For multi-core systems four different packages exist, but a number of issues pose challenges to early adopters. The paper concludes with ideas for further developments in high performance computing with R. Example code is available in the appendix

Power Bounded Computing on Current & Emerging HPC Systems

Power has become a critical constraint for the evolution of large scale High Performance Computing (HPC) systems and commercial data centers. This constraint spans almost every level of computing technologies, from IC chips all the way up to data centers due to physical, technical, and economic reasons. To cope with this reality, it is necessary to understand how available or permissible power impacts the design and performance of emergent computer systems. For this reason, we propose power bounded computing and corresponding technologies to optimize performance on HPC systems with limited power budgets. We have multiple research objectives in this dissertation. They center on the understanding of the interaction between performance, power bounds, and a hierarchical power management strategy. First, we develop heuristics and application aware power allocation methods to improve application performance on a single node. Second, we develop algorithms to coordinate power across nodes and components based on application characteristic and power budget on a cluster. Third, we investigate performance interference induced by hardware and power contentions, and propose a contention aware job scheduling to maximize system throughput under given power budgets for node sharing system. Fourth, we extend to GPU-accelerated systems and workloads and develop an online dynamic performance & power approach to meet both performance requirement and power efficiency. Power bounded computing improves performance scalability and power efficiency and decreases operation costs of HPC systems and data centers. This dissertation opens up several new ways for research in power bounded computing to address the power challenges in HPC systems. The proposed power and resource management techniques provide new directions and guidelines to green exscale computing and other computing systems

Proceedings of the Second International Workshop on Sustainable Ultrascale Computing Systems (NESUS 2015) Krakow, Poland

Proceedings of: Second International Workshop on Sustainable Ultrascale Computing Systems (NESUS 2015). Krakow (Poland), September 10-11, 2015

Towards an Energy-Aware Framework for Application Development and Execution in Heterogeneous Parallel Architectures

The Transparent heterogeneous hardware Architecture deployment for eNergy Gain in Operation (TANGO) project’s goal is to characterise factors which affect power consumption in software development and operation for Heterogeneous Parallel Hardware (HPA) environments. Its main contribution is the combination of requirements engineering and design modelling for self-adaptive software systems, with power consumption awareness in relation to these environments. The energy efficiency and application quality factors are integrated into the application lifecycle (design, implementation and operation). To support this, the key novelty of the project is a reference architecture and its implementation. Moreover, a programming model with built-in support for various hardware architectures including heterogeneous clusters, heterogeneous chips and programmable logic devices is provided. This leads to a new cross-layer programming approach for heterogeneous parallel hardware architectures featuring software and hardware modelling. Application power consumption and performance, data location and time-criticality optimization, as well as security and dependability requirements on the target hardware architecture are supported by the architecture

Diet-ethic: Fair Scheduling of Optional Computations in GridRPC Middleware

Most HPC platforms require users to submit a pre-determined number of computation requests (also called jobs). Unfortunately, this is cumbersome when some of the computations are optional, i.e., they are not critical, but their completion would improve results. For example, given a deadline, the number of requests to submit for a Monte Carlo experiment is difficult to choose. The more requests are completed, the better the results are, however, submitting too many might overload the platform. Conversely, submitting too few requests may leave resources unused and misses an opportunity to improve the results. This paper introduces and solves the problem of scheduling optional computations. An architecture which auto-tunes the number of requests is proposed, then implemented in the DIET GridRPC middleware. Real-life experiments show that several metrics are improved, such as user satisfaction, fairness and the number of completed requests. Moreover, the solution is shown to be scalable.La plupart des plate-formes HPC demandent à l'utilisateur de soumettre un nombre pré-déterminé de requêtes de calcul (aussi appelées " job "). Malheureusement, cela n'est pas pertinent quand une partie des calculs est optionnelle, c'est-à-dire, que l'exécution des requêtes n'est pas critique pour l'utilisateur, mais que leur complétion pourrait améliorer les résultats. Par exemple, étant donnée une date limite, le nombre de requêtes à soumettre pour une expérience Monte Carlo est difficile à choisir. Plus il y a des requêtes qui sont exécutées, meilleures sont les résultats. Cependant, en soumettant trop de requêtes, on risque de surcharger la plate-forme. À l'opposé, en ne soumettant pas assez de requêtes, les ressources sont sous-exploitées alors qu'elles auraient pu être utilisées pour améliorer les résultats. Cet article introduit et résout le problème d'ordonnancer des requêtes optionnelles. Une architecture qui choisit automatiquement le nombre de requêtes est proposée puis implémentée dans l'intergiciel GridRPC DIET. Les expériences faites sur de vraies plate-formes - telles que Grid'5000 - montrent que plusieurs métriques peuvent être améliorées, telles que la satisfaction des utilisateurs, l'équité et le nombre des requêtes exécutées. Enfin, la solution proposée passe à l'échelle

State of the Art in Parallel Computing with R

R is a mature open-source programming language for statistical computing and graphics. Many areas of statistical research are experiencing rapid growth in the size of data sets. Methodological advances drive increased use of simulations. A common approach is to use parallel computing. This paper presents an overview of techniques for parallel computing with R on computer clusters, on multi-core systems, and in grid computing. It reviews sixteen different packages, comparing them on their state of development, the parallel technology used, as well as on usability, acceptance, and performance. Two packages (snow, Rmpi) stand out as particularly suited to general use on computer clusters. Packages for grid computing are still in development, with only one package currently available to the end user. For multi-core systems five different packages exist, but a number of issues pose challenges to early adopters. The paper concludes with ideas for further developments in high performance computing with R. Example code is available in the appendix.

3rd EGEE User Forum

We have organized this book in a sequence of chapters, each chapter associated with an application or technical theme introduced by an overview of the contents, and a summary of the main conclusions coming from the Forum for the chapter topic. The first chapter gathers all the plenary session keynote addresses, and following this there is a sequence of chapters covering the application flavoured sessions. These are followed by chapters with the flavour of Computer Science and Grid Technology. The final chapter covers the important number of practical demonstrations and posters exhibited at the Forum. Much of the work presented has a direct link to specific areas of Science, and so we have created a Science Index, presented below. In addition, at the end of this book, we provide a complete list of the institutes and countries involved in the User Forum