Showing papers by "Violeta Holmes published in 2012"

Hybrid Computer Cluster with High Flexibility

Abstract: In this paper we present a cluster middleware, designed to implement a Linux-Windows Hybrid HPC Cluster, which not only holds the characteristics of both operating system, but also accepts and schedules jobs in both environments. Beowulf Clusters have become an economical and practical choice for small-and-medium-sized institutions to provide High Performance Computing (HPC)resources. The HPC resources are required for running simulations, image rendering and other calculations, and to support the software requiring a specific operating system. To support the software, small-scale computer clusters would have to be divided in two or more clusters if they are to run on a single operating system. The x86 virtualisation technology would help running multiple operating systems on one computer, but only with the latest hardware which many legacy Beowulf clusters do not have. To aid the institutions, who rely on legacy non-virtualisation-supported facilities rather than high-end HPC resources, we have developed and deployed a bi-stable hybrid system built around Linux CentOS 5.5 with the improved OSCAR middleware, and Windows Server 2008 and Windows HPC 2008 R2. This hybrid cluster is utilised as part of the University of Hudders field campus grid.

Robust Mouldable Scheduling Using Application Benchmarking for Elastic Environments.

Abstract: In this paper we present a framework for developing an intelligent job management and scheduling system that utilizes application specific benchmarks to mould jobs onto available resources. In an attempt to achieve the seemingly irreconcilable goals of maximum usage and minimum turnaround time this research aims to adapt an open-framework benchmarking scheme to supply information to a mouldable job scheduler. In a green IT obsessed world, hardware efficiency and usage of computer systems becomes essential. With an average computer rack consuming between 7 and 25 kW it is essential that resources be utilized in the most optimum way possible. Currently the batch schedulers employed to manage these multi-user multi-application environments are nothing more than match making and service level agreement (SLA) enforcing tools. These management systems rely on user prescribed parameters that can lead to over or under booking of compute resources. System administrators strive to get maximum “usage efficiency” from the systems by manual fine-tuning and restricting queues. Existing mouldable scheduling strategies utilize scalability characteristics, which are inherently 2dimensional and cannot provide predictable scheduling information. In this paper we have considered existing benchmarking schemes and tools, schedulers and scheduling strategies, and elastic computational environments. We are proposing a novel job management system that will extract performance characteristics of an application, with an associated dataset and workload, to devise optimal resource allocations and scheduling decisions. As we move towards an era where on-demand computing becomes the fifth utility, the end product from this research will cope with elastic computational environments.

Implementing a Condor pool using a Green-IT policy

Abstract: High Throughput Computing (HTC) systems are designed to utilise available resources on a network of idle machines in an institution or organization by cycle stealing. It provides an additional ‘free’ resource from the existing computing and networking infrastructure for modelling and simulation requiring a large number of small jobs, such as applications from biology, chemistry, physics, and digital signal processing. At the University of Huddersfield, there are thousands of idle laboratory machines that could be used to run serial/parallel jobs by cycle stealing. Our HTC system, implemented in Condor [1], is part of the Queensgate Campus Grid (QGG) [2] that consists of a number of dedicated departmental and university computer clusters. Condor is an excellent HTC tool that excels in cycle stealing and job scheduling on idle machines. However, only idle powered machines can be used from a networked pool. Many organizations deploy power saving mechanisms to try to reduce energy consumption in their systems, and power down idle resources, using rigid and inflexible power management policies. The University of Huddersfield Computing Services use the Energy Star EZ GPO power saving tool that runs as a Windows service and detects how long the computer has been idle. Then it allows the computer to first turn off the screen and then go into hibernation. Our research and development work is focused on implementing a HTC system using Condor to work within a “green IT” policy of a higher education institutions that conform to green IT challenges for a multi-platform, multi-discipline user/ resource base. This system will allow Condor to turn on machines that may have gone to sleep due to lack of usage when there is a large queue of pending jobs. The decision to utilise dormant resources will be made on a variety of factors such as job priority, job requirements, user priority, time of day, flocking options, queue conditions etc. Good practice scheduling policies would need to be devised that would work within this “green IT” pool.