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

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

Job scheduling considering best-effort and soft real-time applications on non-dedicated clusters

As Network Of Workstations (NOWs) emerge as a viable platform for a wide range of workloads, new scheduling approaches are needed to allocate the collection of resources from competing applications. New workload types introduce high uncertainty into the predictability of the system, hindering the applicability of the job scheduling strategies. A new kind of parallel applications has appeared in business or scientific domains, namely Soft Real-Time (SRT). They, together with new SRT desktop applications, turn prediction into a more difficult goal by adding inherent complexity to estimation procedures. In previous work, we introduced an estimation engine into our job scheduling system, termed CISNE. In this work, the estimation engine is extended, by adding two new kernels, both SRT aware. Experimental results confirm the better performance of simulated respect to the analytical kernels and show a maximum average prediction error deviation of 20%.Mientras las Redes de Estaciones de Trabajo (NOWs) emergen como una plataforma viable para un amplio espectro de aplicaciones, son necesarios nuevos enfoques para planificar los recursos disponibles entre las aplicaciones que compiten por ellos. Los nuevos tipos de cargas introducen una alta incertidumbre en la predictibilidad del sistema, afectando la aplicabilidad de las estrategias de planificación de tareas. Un nuevo tipo de aplicaciones paralelas, denominado tiempo real débil (SRT), ha aparecido tanto en los ámbitos comerciales como científicos. Las nuevas aplicaciones paralelas SRT, conjuntamente con los nuevos tipos de aplicaciones SRT de escritorio, convierten la predicción en una meta aún más difícil, al agregar complejidad a los procedimientos de estimación. En trabajos anteriores dotamos al sistema CISNE de un motor de estimación. En este trabajo añadimos al sistema de predicción fuera de línea dos nuevos núcleos de estimación con capacidad SRT. Los resultados experimentales muestran un mejor rendimiento del núcleo simulado con respecto a su homólogo analítico, mostrando un promedio de desviación máximo del 20%.VIII Workshop de Procesamiento Distribuido y ParaleloRed de Universidades con Carreras en Informática (RedUNCI

Demand-based coscheduling of parallel jobs on multiprogrammed multiprocessors

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1997.Includes bibliographical references (p. 92-94).by Patrick Gregory Sobalvarro.Ph.D

An efficient virtual network interface in the FUGU scalable workstation dc by Kenneth Martin Mackenzie.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1998.Includes bibliographical references (p. 123-129).Ph.D

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

G-LOMARC-TS: Lookahead group matchmaking for time/space sharing on multi-core parallel machines

Parallel machines with multi-core nodes are becoming increasingly popular. The performances of applications running on these machines are improved gradually due to the resource competition in each node. Researches have found that coscheduling different applications with complementary resource characteristics on the same set of nodes (semi time sharing) may improve the performance. We propose a scheduling algorithm G-LOMARC-TS which incorporates both space and semi time sharing scheduling methods and matches groups of jobs if possible for coscheduling. Since matchmaking may select jobs further down the waiting queue and the jobs in front of the queue may be delayed subsequently, fairness for each individual job will be watched and the delay will be kept within a limited bound. Several heuristics are used to solve the NP-complete problem of forming groups. Our experiment results show both utilization gain and average relative response time improvements of G-LOMARC-TS over other several scheduling policies

Planificación de aplicaciones best-effort y soft real-time en NOWs

La aparición de nuevos tipos de aplicaciones, como vídeo bajo demanda, realidad virtual y videoconferencias entre otras, caracterizadas por la necesidad de cumplir sus deadlines. Este tipo de aplicaciones, han sido denominadas en la literatura aplicaciones soft-real time (SRT) periódicas. Este trabajo se centra en el problema de la planificación temporal de este nuevo tipo de aplicaciones en clusters no dedicados.L'aparició de nous tipus d'aplicacions, com vídeo sota demanda, realitat virtual i videoconferències entre unes altres, caracteritzades per la necessitat de complir les seves deadlines. Aquest tipus d'aplicacions, han estat denominades en la literatura aplicacions soft-real time (SRT) periòdiques. Aquest treball es centra en el problema de la planificació temporal d'aquest nou tipus d'aplicacions en clusters no dedicats