{"doi":"10.1142/9789812810182_0001","type":"journal_article","date_updated":"2022-01-06T06:54:17Z","publication":"Annual Review of Scalable Computing","page":"1-31","language":[{"iso":"eng"}],"publication_status":"published","volume":3,"title":"Anatomy of a Resource Management System for HPC Clusters","_id":"1999","department":[{"_id":"27"}],"date_created":"2018-03-29T11:37:53Z","user_id":"15274","citation":{"short":"A. Keller, A. Reinefeld, Annual Review of Scalable Computing 3 (2001) 1–31.","apa":"Keller, A., &#38; Reinefeld, A. (2001). Anatomy of a Resource Management System for HPC Clusters. <i>Annual Review of Scalable Computing</i>, <i>3</i>, 1–31. <a href=\"https://doi.org/10.1142/9789812810182_0001\">https://doi.org/10.1142/9789812810182_0001</a>","chicago":"Keller, Axel, and Alexander Reinefeld. “Anatomy of a Resource Management System for HPC Clusters.” <i>Annual Review of Scalable Computing</i> 3 (2001): 1–31. <a href=\"https://doi.org/10.1142/9789812810182_0001\">https://doi.org/10.1142/9789812810182_0001</a>.","bibtex":"@article{Keller_Reinefeld_2001, title={Anatomy of a Resource Management System for HPC Clusters}, volume={3}, DOI={<a href=\"https://doi.org/10.1142/9789812810182_0001\">10.1142/9789812810182_0001</a>}, journal={Annual Review of Scalable Computing}, author={Keller, Axel and Reinefeld, Alexander}, year={2001}, pages={1–31} }","ama":"Keller A, Reinefeld A. Anatomy of a Resource Management System for HPC Clusters. <i>Annual Review of Scalable Computing</i>. 2001;3:1-31. doi:<a href=\"https://doi.org/10.1142/9789812810182_0001\">10.1142/9789812810182_0001</a>","mla":"Keller, Axel, and Alexander Reinefeld. “Anatomy of a Resource Management System for HPC Clusters.” <i>Annual Review of Scalable Computing</i>, vol. 3, 2001, pp. 1–31, doi:<a href=\"https://doi.org/10.1142/9789812810182_0001\">10.1142/9789812810182_0001</a>.","ieee":"A. Keller and A. Reinefeld, “Anatomy of a Resource Management System for HPC Clusters,” <i>Annual Review of Scalable Computing</i>, vol. 3, pp. 1–31, 2001."},"year":"2001","status":"public","intvolume":"         3","abstract":[{"lang":"eng","text":"Workstation clusters are often not only used for high-throughput computing in time-sharing mode but also for running complex parallel jobs in space-sharing mode. This poses several difficulties to the resource management system, which must be able to reserve computing resources for exclusive use and also to determine an optimal process mapping for a given system topology.\r\nOn the basis of our CCS software, we describe the anatomy of a modern resource management system. Like Codine, Condor, and LSF, CCS provides mechanisms for the user-friendly system access and management of clusters. But unlike them, CCS is targeted at the effective support of space-sharing parallel computers and even metacomputers. Among other features, CCS provides a versatile resource description facility, topology-based process mapping, pluggable schedulers, and hooks to metacomputer management."}],"author":[{"first_name":"Axel","full_name":"Keller, Axel","id":"15274","last_name":"Keller"},{"last_name":"Reinefeld","full_name":"Reinefeld, Alexander","first_name":"Alexander"}]}