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Sm@rtConfig: A Context-Aware Runtime and Tuning System Using an Aspect-Oriented Approach for Data Intensive Engineering Applications

Binotto, Alécio P. D. ; Wehrmeister, Marco A. ; Kuijper, Arjan ; Pereira, Carlos Eduardo (2013)
Sm@rtConfig: A Context-Aware Runtime and Tuning System Using an Aspect-Oriented Approach for Data Intensive Engineering Applications.
In: Control Engineering Practice, 21 (2)
doi: 10.1016/j.conengprac.2012.10.001
Article, Bibliographie

Abstract

Distributing the workload upon all available Processing Units (PUs) of a high-performance heterogeneous platform (e.g., PCs composed by CPU-GPUs) is a challenging task, since the execution cost of a task on distinct PUs is non-deterministic and affected by parameters not known a priori. This paper presents Sm@rtConfig, a context-aware runtime and tuning system based on a compromise between reducing the execution time of engineering applications and the cost of tasks' scheduling on CPU-GPUs' platforms. Using Model-Driven Engineering and Aspect Oriented Software Development, a high-level specification and implementation for Sm@rtConfig has been created, aiming at improving modularization and reuse in different applications. As case study, the simulation subsystem of a CFD application has been developed using the proposed approach. These system's tasks were designed considering only their functional concerns, whereas scheduling and other non-functional concerns are handled by Sm@rtConfig aspects, improving tasks modularity. Although Sm@rtConfig supports multiple PUs, in this case study, these tasks have been scheduled to execute on an platform composed by one CPU and one GPU. Experimental results show an overall performance gain of 21.77 in comparison to the static assignment of all tasks only to the GPU.

Item Type: Article
Erschienen: 2013
Creators: Binotto, Alécio P. D. ; Wehrmeister, Marco A. ; Kuijper, Arjan ; Pereira, Carlos Eduardo
Type of entry: Bibliographie
Title: Sm@rtConfig: A Context-Aware Runtime and Tuning System Using an Aspect-Oriented Approach for Data Intensive Engineering Applications
Language: English
Date: 2013
Journal or Publication Title: Control Engineering Practice
Volume of the journal: 21
Issue Number: 2
DOI: 10.1016/j.conengprac.2012.10.001
Abstract:

Distributing the workload upon all available Processing Units (PUs) of a high-performance heterogeneous platform (e.g., PCs composed by CPU-GPUs) is a challenging task, since the execution cost of a task on distinct PUs is non-deterministic and affected by parameters not known a priori. This paper presents Sm@rtConfig, a context-aware runtime and tuning system based on a compromise between reducing the execution time of engineering applications and the cost of tasks' scheduling on CPU-GPUs' platforms. Using Model-Driven Engineering and Aspect Oriented Software Development, a high-level specification and implementation for Sm@rtConfig has been created, aiming at improving modularization and reuse in different applications. As case study, the simulation subsystem of a CFD application has been developed using the proposed approach. These system's tasks were designed considering only their functional concerns, whereas scheduling and other non-functional concerns are handled by Sm@rtConfig aspects, improving tasks modularity. Although Sm@rtConfig supports multiple PUs, in this case study, these tasks have been scheduled to execute on an platform composed by one CPU and one GPU. Experimental results show an overall performance gain of 21.77 in comparison to the static assignment of all tasks only to the GPU.

Uncontrolled Keywords: Business Field: Virtual engineering, Research Area: Semantics in the modeling process, Scheduling, Load balancing, Graphics Processing Unit (GPU)
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Interactive Graphics Systems
Date Deposited: 12 Nov 2018 11:16
Last Modified: 12 Nov 2018 11:16
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