A batch scheduler with high level components

By Nicolas Capit, Georges Da Costa, Yiannis Georgiou, Guillaume Huard, Cyrille Martin, G. Mounié, P. Neyron, Olivier Richard. CCGrid 2005. IEEE International Symposium on Cluster Computing and the Grid, 2005., 2005

369 citations recorded by the source corpus.

In this article we present the design choices and the evaluation of a batch scheduler for large clusters, named OAR. This batch scheduler is based upon an original design that emphasizes on low software complexity by using high level tools. The global architecture is built upon the scripting language Perl and the relational database engine Mysql. The goal of the project OAR is to prove that it is possible today to build a complex system for resource management using such tools without sacrificing efficiency and scalability. Currently, our system offers most of the important features implemented by other batch schedulers such as priority scheduling (by queues), reservations, backfilling and some global computing support. Despite the use of high level tools, our experiments show that our system has performances close to other systems. Furthermore, OAR is currently exploited for the management of 700 nodes (a metropolitan grid) and has shown good efficiency and robustness.

Subfields: Computer Networks and Communications, Hardware and Architecture, Information Systems

View Paper: https://www.semanticscholar.org/paper/4ac84942337ab94894321601c81ed37b1c90d4b1

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

In Hardware and Architecture

In Information Systems

Citations in the corpus

Apache Hadoop YARN: yet another resource negotiator (2013, methodology): “To address some of its multi-tenancy issues, Yahoo! developed and deployed Hadoop on Demand (HoD), which used Torque[7] and Maui[20] to allocate Hadoop clusters on a shared pool of hardware.”
Management of an academic HPC cluster: The UL experience (2014, methodology): “OAR manages resources of clusters as a traditional batch scheduler (as PBS [11], Torque [12], LSF [13] or SGE [14]).”
Grid'5000: a large scale and highly reconfigurable grid experimental testbed (2005, methodology): “As described in the next section, Grid’5000 software set provides a reservation tool (OAR [13]), a deployment tool (Kadeploy [?]) and a several tools (FAIL [14], eWAN eWAN experimental condition injectors.”
FIT IoT-LAB: A large scale open experimental IoT testbed (2015, methodology): “This application interacts with OAR Batch scheduler software [5], an open-source resource manager for large clusters, which allows optimal experiment scheduling and resource allocation.”
The Grid Workloads Archive (2008, methodology): “We have obtained traces recorded by all batch schedulers handling Grid’5000 clusters (OAR [24]), from the beginning of the Grid’5000 project up to November 2006.”