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Towards dynamic reconfigurable load-balancing for hybrid desktop platforms

: Binotto, Alecio; Pereira, Carlos Eduardo; Fellner, Dieter W.


Institute of Electrical and Electronics Engineers -IEEE-; IEEE Computer Society:
IEEE International Symposium on Parallel & Distributed Processing Workshops and Phd Forum, IPDPSW 2010. Vol.2 : Atlanta, Georgia, USA, 19 - 23 April 2010
Piscataway/NJ: IEEE, 2010
ISBN: 978-1-4244-6533-0
ISBN: 978-1-4244-6534-7
ISBN: 1-4244-6533-8
International Parallel and Distributed Processing Symposium (IPDPS) <24, 2010, Atlanta/Ga.>
Conference Paper
Fraunhofer IGD ()
graphics processors; parallel processing; load balancing

High-performance platforms are required by applications that use massive calculations. Actually, desktop accelerators (like the GPUs) form a powerful heterogeneous platform in conjunction with multi-core CPUs. To improve application performance on these hybrid platforms, load-balancing plays an important role to distribute workload. However, such scheduling problem faces challenges since the cost of a task at a Processing Unit (PU) is non-deterministic and depends on parameters that cannot be known a priori, like input data, online creation of tasks, scenario changing, etc. Therefore, self-adaptive computing is a potential paradigm as it can provide flexibility to explore computational resources and improve performance on different execution scenarios.
This paper presents an ongoing PhD research focused on a dynamic and reconfigurable scheduling strategy based on timing profiling for desktop accelerators. Preliminary results analyze the performance of solvers for SLEs (Systems of Linear Equations) over a hybrid CPU and multi-GPU platform applied to a CFD (Computational Fluid Dynamics) application. The decision of choosing the best solver as well as its scheduling must be performed dynamically considering online parameters in order to achieve a better application performance.