A methodology for user-oriented scalability analysis

Scalability analysis provides information about the effectiveness of increasing the number of resources of a parallel system. Several methods have been proposed which use different approaches to provide this information. This paper presents a family of analysis methods oriented to the user. The methods in this family should assist the user in estimating the benefits when increasing the system size. The key issue in the proposal is the appropriate combination of a scaling model, which reflects the way the users utilize an increasing number of resources, and a figure of merit that the user wants to improve with the larger system. Another important element in the proposal is the approach to characterize the scalability, which enables quick visual analyses and comparisons. Finally, three concrete examples of methods belonging to the proposed family are introduced in this paper.Peer ReviewedPostprint (published version

Two ways to Grid: the contribution of Open Grid Services Architecture (OGSA) mechanisms to service-centric and resource-centric lifecycles

Service Oriented Architectures (SOAs) support service lifecycle tasks, including Development, Deployment, Discovery and Use. We observe that there are two disparate ways to use Grid SOAs such as the Open Grid Services Architecture (OGSA) as exemplified in the Globus Toolkit (GT3/4). One is a traditional enterprise SOA use where end-user services are developed, deployed and resourced behind firewalls, for use by external consumers: a service-centric (or ‘first-order’) approach. The other supports end-user development, deployment, and resourcing of applications across organizations via the use of execution and resource management services: A Resource-centric (or ‘second-order’) approach. We analyze and compare the two approaches using a combination of empirical experiments and an architectural evaluation methodology (scenario, mechanism, and quality attributes) to reveal common and distinct strengths and weaknesses. The impact of potential improvements (which are likely to be manifested by GT4) is estimated, and opportunities for alternative architectures and technologies explored. We conclude by investigating if the two approaches can be converged or combined, and if they are compatible on shared resources

An Efficient Thread Mapping Strategy for Multiprogramming on Manycore Processors

The emergence of multicore and manycore processors is set to change the parallel computing world. Applications are shifting towards increased parallelism in order to utilise these architectures efficiently. This leads to a situation where every application creates its desirable number of threads, based on its parallel nature and the system resources allowance. Task scheduling in such a multithreaded multiprogramming environment is a significant challenge. In task scheduling, not only the order of the execution, but also the mapping of threads to the execution resources is of a great importance. In this paper we state and discuss some fundamental rules based on results obtained from selected applications of the BOTS benchmarks on the 64-core TILEPro64 processor. We demonstrate how previously efficient mapping policies such as those of the SMP Linux scheduler become inefficient when the number of threads and cores grows. We propose a novel, low-overhead technique, a heuristic based on the amount of time spent by each CPU doing some useful work, to fairly distribute the workloads amongst the cores in a multiprogramming environment. Our novel approach could be implemented as a pragma similar to those in the new task-based OpenMP versions, or can be incorporated as a distributed thread mapping mechanism in future manycore programming frameworks. We show that our thread mapping scheme can outperform the native GNU/Linux thread scheduler in both single-programming and multiprogramming environments.Comment: ParCo Conference, Munich, Germany, 201

Reconfigurability Function Deployment in Software Development

In the forthcoming highly dynamic and complex business environment high-speed and cost-effective development of software applications for targeting a precise, unique and momentary set of requirements (no more-no less) associated to a customized business case will bring sig-nificant benefits both for producers and users. This requires a life cycle change-oriented ap-proach in software development. In this respect, designing software with intrinsic evolutionary resources for reconfiguration represents the sound approach. A methodology for concurrent deployment of reconfigurability characteristics in software applications is introduced in this paper. Its potential is exemplified in a case study dealing with web-based software tools to support systematic product innovation projects.Reconfigurability, Software Development, Innovation, TRIZ, RAD

How blockchain impacts cloud-based system performance: a case study for a groupware communication application

This paper examines the performance trade-off when implementing a blockchain architecture for a cloud-based groupware communication application. We measure the additional cloud-based resources and performance costs of the overhead required to implement a groupware collaboration system over a blockchain architecture. To evaluate our groupware application, we develop measuring instruments for testing scalability and performance of computer systems deployed as cloud computing applications. While some details of our groupware collaboration application have been published in earlier work, in this paper we reflect on a generalized measuring method for blockchain-enabled applications which may in turn lead to a general methodology for testing cloud-based system performance and scalability using blockchain. Response time and transaction throughput metrics are collected for the blockchain implementation against the non-blockchain implementation and some conclusions are drawn about the additional resources that a blockchain architecture for a groupware collaboration application impose