Sm@rtConfig: A context-aware runtime and tuning system using an aspect-oriented approach for data intensive engineering applications
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 p...
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| Published in | Control engineering practice Vol. 21; no. 2; pp. 204 - 217 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
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Elsevier Ltd
01.02.2013
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| 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. |
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| AbstractList | 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. |
| Author | Kuijper, Arjan Pereira, Carlos Eduardo Wehrmeister, Marco Aurélio Binotto, Alécio Pedro Delazari |
| Author_xml | – sequence: 1 givenname: Alécio Pedro Delazari surname: Binotto fullname: Binotto, Alécio Pedro Delazari email: abinotto@inf.ufrgs.br organization: UFRGS—Electrical Engineering Department, Av. Osvaldo Aranha 103, 90035-190 Porto Alegre, Brazil – sequence: 2 givenname: Marco Aurélio surname: Wehrmeister fullname: Wehrmeister, Marco Aurélio organization: Santa Catarina State University, Rua Paulo Malschitzki, 89219-710 Joinville, Brazil – sequence: 3 givenname: Arjan surname: Kuijper fullname: Kuijper, Arjan organization: Technische Universität Darmstadt & Fraunhofer IGD, Fraunhoferstr. 5, 64283 Darmstadt, Germany – sequence: 4 givenname: Carlos Eduardo surname: Pereira fullname: Pereira, Carlos Eduardo organization: UFRGS—Electrical Engineering Department, Av. Osvaldo Aranha 103, 90035-190 Porto Alegre, Brazil |
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| CitedBy_id | crossref_primary_10_1007_s00607_018_0614_9 crossref_primary_10_1016_j_mechatronics_2013_12_008 crossref_primary_10_1016_j_parco_2019_102584 crossref_primary_10_1007_s00170_017_0154_z |
| Cites_doi | 10.1007/978-3-642-04284-3_4 10.3182/20080706-5-KR-1001.01167 10.1109/IPDPSW.2010.5470804 10.1287/opre.21.2.498 10.1109/HPCC.2011.20 10.1109/ISPA.2008.69 10.1007/978-3-642-03869-3_80 10.1016/j.csi.2009.11.009 10.1109/71.993206 10.1109/SBAC-PADW.2010.6 10.1109/ISORC.2008.67 10.1109/MOMPES.2008.9 10.1016/j.scico.2008.05.005 10.1109/HPCC.2010.40 |
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