{"id":9649,"date":"2013-09-16T10:11:13","date_gmt":"2013-09-16T08:11:13","guid":{"rendered":"https:\/\/web.computaex.es\/?page_id=9649"},"modified":"2025-08-27T10:15:05","modified_gmt":"2025-08-27T08:15:05","slug":"performance-and-energy-aware-scheduling-simulator-for-high-performance-computing","status":"publish","type":"page","link":"https:\/\/computaex.es\/en\/publicaciones\/performance-and-energy-aware-scheduling-simulator-for-high-performance-computing\/","title":{"rendered":"Performance and Energy Aware Scheduling Simulator for High-Performance Computing"},"content":{"rendered":"

C\u00e9sar G\u00f3mez-Mart\u00edn, Miguel A. Vega-Rodr\u00edguez, Jos\u00e9-Luis Gonz\u00e1lez-S\u00e1nchez, Javier Corral-Garc\u00eda y David Cort\u00e9s-Polo.\u00a0Performance and Energy Aware Scheduling Simulator for High-Performance Computing<\/strong>. 7th IBERGRID 2013, Conference Proceedings. Madrid, Espa\u00f1a. 19-20 de septiembre 2013. ISBN: 978-84-9048-110-3. pp 17-29.<\/p>\n

Abstract
\nJob scheduling is a very complex task that influences the performance of High-Performance Computing (HPC) infrastructures, thus,a simulator of real computing environments for an accurate evaluation of scheduling and resource selection policies helps ICT and data center managers to make decisions with a solid experimental basis. There are several simulators that try to address performance and somehow estimate energy consumption, but there are none in which the energy model is based on benchmark data that have been countersigned by independent bodies such as the Standard Performance Evaluation Corporation (SPEC), this is the reason why we have implemented a Performance and Energy Aware Scheduling (PEAS) Simulator for HPC. In order to validate the simulator and understand how different computing workloads behave depending on scheduling policies, several user-centric evaluation metrics have been evaluated and compared with previous studies.<\/p>\n

Fuente de la publicaci\u00f3n:<\/p>\n