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An Effective Dynamic Scheduling Runtime and Tuning System for Heterogeneous Multi and Many-Core Desktop Platforms

Binotto, Alécio P. D. and Pereira, Carlos Eduardo and Kuijper, Arjan and Stork, André and Fellner, Dieter W. (2011):
An Effective Dynamic Scheduling Runtime and Tuning System for Heterogeneous Multi and Many-Core Desktop Platforms.
pp. 78-85, IEEE Computer Society Conference Publishing Services (CPS), Los Alamitos, Calif., Proceedings 2011 IEEE International Conference on High Performance Computing and Communications, DOI: 10.1109/HPCC.2011.20,
[Conference or Workshop Item]

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.

Item Type: Conference or Workshop Item
Erschienen: 2011
Creators: Binotto, Alécio P. D. and Pereira, Carlos Eduardo and Kuijper, Arjan and Stork, André and Fellner, Dieter W.
Title: An Effective Dynamic Scheduling Runtime and Tuning System for Heterogeneous Multi and Many-Core Desktop Platforms
Language: English
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.

Publisher: IEEE Computer Society Conference Publishing Services (CPS), Los Alamitos, Calif.
Uncontrolled Keywords: Forschungsgruppe Semantic Models, Immersive Systems (SMIS), Business Field: Virtual engineering, Research Area: Confluence of graphics and vision, High performance computing, Heterogeneous systems, Graphics Processing Unit (GPU), Solvers for systems of linear equations
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Interactive Graphics Systems
Event Title: Proceedings 2011 IEEE International Conference on High Performance Computing and Communications
Date Deposited: 12 Nov 2018 11:16
DOI: 10.1109/HPCC.2011.20
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