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An effective dynamic scheduling runtime and tuning system for heterogeneous multi and many-core desktop platforms

 
: Binotto, Alecio; Pereira, Carlos Eduardo; Kuijper, Arjan; Stork, André; Fellner, Dieter W.

:

Thulasiraman, P. ; IEEE Computer Society:
IEEE 13th International Conference on High Performance Computing and Communications, HPCC 2011. Proceedings : 2-4 September 2011, Banff
Los Alamitos, Calif.: IEEE Computer Society Press, 2011
ISBN: 978-1-4577-1564-8 (Print)
ISBN: 978-0-7695-4538-7
S.78-85
International Conference on High Performance Computing and Communications (HPCC) <13, 2011, Banff>
Englisch
Konferenzbeitrag
Fraunhofer IGD ()
high performance computing; heterogeneous system; Graphics Processing Unit (GPU); Forschungsgruppe Semantic Models, Immersive Systems (SMIS)

Abstract
A personal computer can be considered as a one-node heterogeneous cluster that simultaneously processes several application tasks. It can be composed by, for example, asymmetric CPU and GPUs. This way, a high-performance heterogeneous platform is built on a desktop for data intensive engineering calculations. In our perspective, a workload distribution over the Processing Units (PUs) plays a key role in such systems. This issue presents challenges since the cost of a task at a PU is non-deterministic and can be affected by parameters not known a priori.
This paper presents a context-aware runtime and tuning system based on a compromise between reducing the execution time of engineering applications - due to appropriate dynamic scheduling - and the cost of computing such scheduling applied on a platform composed of CPU and GPUs. Results obtained in experimental case studies are encouraging and a performance gain of 21.77% was achieved in comparison to the static assignment of all tasks to the GPU.

: http://publica.fraunhofer.de/dokumente/N-192476.html