Coscheduling techniques and monitoring tools for non-dedicated cluster computing

Our efforts are directed towards the understanding of the coscheduling mechanism in a NOW system when a parallel job is executed jointly with local workloads, balancing parallel perfor-mance against the local interactive response. Explicit and implicit coscheduling techniques in a PVM-Linux NOW (or cluster) have been implemented. Furthermore, dynamic coscheduling remains an open question when parallel jobs are executed in a non-dedicated Cluster. A basis model for dynamic coscheduling in Cluster systems is presented in this paper. Also, one dynamic coscheduling algorithm for this model is proposed. The applicability of this algorithm has been proved and its performance ana-lyzed by simulation. Finally, a new tool (named Monito) for monitoring the different queues of messages in such an environments is presented. The main aim of implementing this facility is to provide a mean of capturing the bottlenecks and overheads of the communication system in a PVM-Linux cluster.Facultad de Informátic

Técnicas de coscheduling y herramientas de monitorización para clusters no dedicados

En este trabajo presentamos el diseño e implementación de un cluster de PCs en un entorno PVM/Linux que ofrece un sistema dual computador paralelo - computador tradicional. Nuestro proyecto está centrado en el desarrollo del software necesario para la construcción de máquinas paralelas de bajo costo, que nos permitan, a partir de componentes comerciales, abordar problemáticas de cómputo paralelo sin afectar demasiado la ejecución de las aplicaciones que se están ejecutando de forma rutinaria en el sistema. Hemos implementado tanto técnicas de coscheduling explícito, implícito como dinámico, y analizado y comparado, tanto la eficiencia como el costo que suponen la implementación de los métodos comentados anteriormente mediante benchmarks standards. Los resultados obtenidos, medidos con herramientas que han sido desarrolladas a tal efecto, muestran la viabilidad de nuestras propuestas.I Workshop de Procesamiento Distribuido y Paralelo (WPDP)Red de Universidades con Carreras en Informática (RedUNCI

Técnicas de coscheduling y herramientas de monitorización para clusters no dedicados

En este trabajo presentamos el diseño e implementación de un cluster de PCs en un entorno PVM/Linux que ofrece un sistema dual computador paralelo - computador tradicional. Nuestro proyecto está centrado en el desarrollo del software necesario para la construcción de máquinas paralelas de bajo costo, que nos permitan, a partir de componentes comerciales, abordar problemáticas de cómputo paralelo sin afectar demasiado la ejecución de las aplicaciones que se están ejecutando de forma rutinaria en el sistema. Hemos implementado tanto técnicas de coscheduling explícito, implícito como dinámico, y analizado y comparado, tanto la eficiencia como el costo que suponen la implementación de los métodos comentados anteriormente mediante benchmarks standards. Los resultados obtenidos, medidos con herramientas que han sido desarrolladas a tal efecto, muestran la viabilidad de nuestras propuestas.I Workshop de Procesamiento Distribuido y Paralelo (WPDP)Red de Universidades con Carreras en Informática (RedUNCI

Técnicas de coscheduling y herramientas de monitorización para clusters no dedicados

En este trabajo presentamos el diseño e implementación de un cluster de PCs en un entorno PVM/Linux que ofrece un sistema dual computador paralelo - computador tradicional. Nuestro proyecto está centrado en el desarrollo del software necesario para la construcción de máquinas paralelas de bajo costo, que nos permitan, a partir de componentes comerciales, abordar problemáticas de cómputo paralelo sin afectar demasiado la ejecución de las aplicaciones que se están ejecutando de forma rutinaria en el sistema. Hemos implementado tanto técnicas de coscheduling explícito, implícito como dinámico, y analizado y comparado, tanto la eficiencia como el costo que suponen la implementación de los métodos comentados anteriormente mediante benchmarks standards. Los resultados obtenidos, medidos con herramientas que han sido desarrolladas a tal efecto, muestran la viabilidad de nuestras propuestas.I Workshop de Procesamiento Distribuido y Paralelo (WPDP)Red de Universidades con Carreras en Informática (RedUNCI

LOMARC: Look ahead matchmaking for multi-resource coscheduling.

Hyper-Threading (HT) provides a new possibility for job coscheduling without context switch and without the cost for coordinating processes of one parallel job. However, HT achieves high processor throughput at the expense of reducing the performance of the individual process. Since the hardware resources are actually shared between two coscheduled jobs, the resource contention will harm the performance of each job. Most scheduling approaches only focus on the CPU without considering the impact on other resources. In this thesis we present LOMARC, a space-time sharing approach that takes multiple resources, including CPU, I/O, memory and network, into consideration for job coscheduling on HT processors. To improve resource utilization and reduce job response times, LOMARC matches two jobs with complementary resource requirements to coschedule. Our approach partially reorders the waiting job queue by lookahead to increase the possibility of finding a good match. LOMARC also generalizes for standard CPUs, using an adjusted matching scheme and only focusing on hiding I/O latency. In addition, LOMARC incorporates standard scheduling approaches such as priority ordering, aging and backfilling. In our simulation experiment, we use a realistic workload model to provide the convincing results. Our experimental results demonstrate that LOMARC delivers better performance than the standard space sharing approach and the other two job coscheduling approaches for HT processors. The performance gain is mainly due to an increased possibility of coscheduling two complementary jobs by looking ahead on the waiting queue. Source: Masters Abstracts International, Volume: 43-01, page: 0239. Adviser: Angela Sodan. Thesis (M.Sc.)--University of Windsor (Canada), 2004

Adaptive space-time sharing with SCOJO.

Coscheduling is a technique used to improve the performance of parallel computer applications under time sharing, i.e., to provide better response times than standard time sharing or space sharing. Dynamic coscheduling and gang scheduling are two main forms of coscheduling. In SCOJO (Share-based Job Coscheduling), we have introduced our own original framework to employ loosely coordinated dynamic coscheduling and a dynamic directory service in support of scheduling cross-site jobs in grid scheduling. SCOJO guarantees effective CPU shares by taking coscheduling effects into consideration and supports both time and CPU share reservation for cross-site job. However, coscheduling leads to high memory pressure and still involves problems like fragmentation and context-switch overhead, especially when applying higher multiprogramming levels. As main part of this thesis, we employ gang scheduling as more directly suitable approach for combined space-time sharing and extend SCOJO for clusters to incorporate adaptive space sharing into gang scheduling. We focus on taking advantage of moldable and malleable characteristics of realistic job mixes to dynamically adapt to varying system workloads and flexibly reduce fragmentation. In addition, our adaptive scheduling approach applies standard job-scheduling techniques like a priority and aging system, backfilling or easy backfilling. We demonstrate by the results of a discrete-event simulation that this dynamic adaptive space-time sharing approach can deliver better response times and bounded relative response times even with a lower multiprogramming level than traditional gang scheduling.Dept. of Computer Science. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2004 .H825. Source: Masters Abstracts International, Volume: 43-01, page: 0237. Adviser: A. Sodan. Thesis (M.Sc.)--University of Windsor (Canada), 2004