Task scheduling techniques for asymmetric multi-core systems

As performance and energy efficiency have become the main challenges for next-generation high-performance computing, asymmetric multi-core architectures can provide solutions to tackle these issues. Parallel programming models need to be able to suit the needs of such systems and keep on increasing...

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Detalles Bibliográficos
Autores: Chronaki, Kallia, Rico, Alejandro, Casas, Marc|||0000-0003-4564-2093, Moretó Planas, Miquel|||0000-0002-9848-8758, Badia Sala, Rosa Maria|||0000-0003-2941-5499, Ayguadé Parra, Eduard|||0000-0002-5146-103X, Labarta Mancho, Jesús José|||0000-0002-7489-4727, Valero Cortés, Mateo|||0000-0003-2917-2482
Tipo de recurso: artículo
Fecha de publicación:2017
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/104901
Acceso en línea:https://hdl.handle.net/2117/104901
https://dx.doi.org/10.1109/TPDS.2016.2633347
Access Level:acceso abierto
Palabra clave:Microprocessors -- Energy consumption
Dynamic scheduling
Programming
Runtime
Processor scheduling
Computer architecture
Electronic mail
Multi-core
Scheduling
Heterogeneous
Microprocessadors -- Consum d'energia
Àrees temàtiques de la UPC::Informàtica::Arquitectura de computadors
Descripción
Sumario:As performance and energy efficiency have become the main challenges for next-generation high-performance computing, asymmetric multi-core architectures can provide solutions to tackle these issues. Parallel programming models need to be able to suit the needs of such systems and keep on increasing the application’s portability and efficiency. This paper proposes two task scheduling approaches that target asymmetric systems. These dynamic scheduling policies reduce total execution time either by detecting the longest or the critical path of the dynamic task dependency graph of the application, or by finding the earliest executor of a task. They use dynamic scheduling and information discoverable during execution, fact that makes them implementable and functional without the need of off-line profiling. In our evaluation we compare these scheduling approaches with two existing state-of the art heterogeneous schedulers and we track their improvement over a FIFO baseline scheduler. We show that the heterogeneous schedulers improve the baseline by up to 1.45 in a real 8-core asymmetric system and up to 2.1 in a simulated 32-core asymmetric chip.