Euro-Par 2009 – Parallel Processing Workshops

Software-as-a-Service (SaaS) is an interesting concept for providing scientific applications. Service providers in this field have to either run their own data centre or to outsource the applications to a third party provider. In both cases, they want to optimally utilize resources without violating service level agreements (SLAs) negotiated with their customers. This work analyzes the properties of scientific applications. We found that there are essential differences between scientific and business applications. We also build up an own cloud and analyze Gromacs 4, a common scientific application. This shows that for fulfilling an SLA, it is often possible to provide different configurations, using either a few high performance machines or multiple smaller machines. Furthermore, experiences of the performance behavior gained in physical environments must not necessarily apply in virtual environments. Fulfilling SLAs also depends significantly on the mapping of the virtual machines to physical hosts.

Providing Scientific Software as a Service in Consideration of Service Level Agreements

Grid computing enables access to high performance computing resources by offering unified interfaces to compute facilities of distributed compute centers. These compute centers are limited in personal capacity and in support capabilities for different communities/VOs. This work presents a solution to this management problem by facilitating the natural interface introduced by virtualization to separate hardware and application provisioning. Any eScience community may provide preconfigured applications within virtual machine images and compute centers run these without having to maintain applications. This is similar to the Infrastructure as a Service and Software as a Service known from cloud computing. Additionally, in contrast to the state of the art in grid computing, we propose a scalable process to maintain compute resources for scientific users, including the definition of a chain of trust between users and compute centers, which simplifies the addition of communities and resources. As a result, this paper lays the foundation for a next-generation eScience Cloud improving the accessibility of compute resources for research and industry.

eScience Cloud Infrastructure

Providing Scientific Software as a Service in Consideration of ServiceLevel Agreements

Supporting e-Science in the EGI e-Infrastructure requires extensive and reliable software, for advanced computing use, deployed across over approximately 300 European and worldwide data centers. The Unified Middleware Distribution (UMD) and Cloud Middleware Distribution (CMD) are the channels to deliver the software for the EGI e-Infrastructure consumption. The software is compiled, validated and distributed following the Software Provisioning Process (SWPP), where the Quality Criteria (QC) definition sets the minimum quality requirements for EGI acceptance. The growing number of software components currently existing within UMD and CMD distributions hinders the application of the traditional, manual-based validation mechanisms, thus driving the adoption of automated solutions. This paper presents umd-verification, an open-source tool that enforces the fulfillment of the QC requirements in an automated way for the continuous validation of the software products for scientific disposal. The umd-verification tool has been successfully integrated within the SWPP pipeline and is progressively supporting the full validation of the products in the UMD and CMD repositories. While the cost of supporting new products is dependant on the availability of Infrastructure as Code solutions to take over the deployment and high test coverage, the results obtained for the already integrated products are promising, as the time invested in the validation of products has been drastically reduced. Furthermore, automation adoption has brought along benefits for the reliability of the process, such as the removal of human-associated errors or the risk of regression of previously tested functionalities.

/pdf/umd-verification-automation-of-software-validation-for-the-6bjh2qwfvc.pdf

umd-verification : Automation of Software Validation for the EGI Federated e-Infrastructure

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.

Validation of Grid Middleware for the European Grid Infrastructure

CESGA is operating a totally virtualized grid infrastructure that supports several production sites for different grid projects (EGEE, EELA, int.eu.grid (I2G), Ibergrid, and other regional grid projects) as well as several development sites created on demand to test new middleware releases both for EGEE certification and pre-production activities. The final architecture that results from several years of development is described showing how to apply modern virtualization solutions like Xen hypervisor to migrate from an entire physical cluster to virtual machines. Thanks to a collaboration with FORMIGA's project the infrastructure also includes resources from computer labs. Worker Node VMs are automatically started following a pre-defined schedule that guarantees that the computers are not in use. Extensive benchmarks, including two of the most used applications at our supercomputing center, have been performed to quantify the performance loss of the virtual infrastructure. Currently cloud computing technologies are being explored as a way to improve the service deployment process in our platform.

Providing grid services based on virtualization and cloud technologies

/pdf/grid-engine-batch-system-integration-in-the-emi-era-nmdrxeu4xx.pdf

Grid Engine batch system integration in the EMI era

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Validation of Grid Middleware for the European Grid Infrastructure

Providing grid services based on virtualization and cloud technologies

Grid Engine batch system integration in the EMI era