A job dispatcher for large and heterogeneous HPC systems running modern applications

Cristian Galleguillos, Zeynep Kiziltan, Ricardo Soto

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

High-performance Computing (HPC) systems have become essential instruments in our modern society. As they get closer to exascale performance, HPC systems become larger in size and more heterogeneous in their computing resources. With recent advances in AI, HPC systems are also increasingly being used for applications that employ many short jobs with strict timing requirements. HPC job dispatchers need to therefore adopt techniques to go beyond the capabilities of those developed for small or homogeneous systems, or for traditional compute-intensive applications. In this paper, we present a job dispatcher suitable for today's large and heterogeneous systems running modern applications. Unlike its predecessors, our dispatcher solves the entire dispatching problem using Constraint Programming (CP) with a model size independent of the system size. Experimental results based on a simulation study show that our approach can bring about significant performance gains over the existing CP-based dispatchers in a large or heterogeneous system.

Idioma originalInglés
Título de la publicación alojada27th International Conference on Principles and Practice of Constraint Programming, CP 2021
EditoresLaurent D. Michel
EditorialSchloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
ISBN (versión digital)9783959772112
DOI
EstadoPublicada - 1 oct 2021
Publicado de forma externa
Evento27th International Conference on Principles and Practice of Constraint Programming, CP 2021 - Virtual, Montpellier, Francia
Duración: 25 oct 202129 oct 2021

Serie de la publicación

NombreLeibniz International Proceedings in Informatics, LIPIcs
Volumen210
ISSN (versión impresa)1868-8969

Conferencia

Conferencia27th International Conference on Principles and Practice of Constraint Programming, CP 2021
País/TerritorioFrancia
CiudadVirtual, Montpellier
Período25/10/2129/10/21

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