Binotto, Alécio P. D. ; Pedras, Bernardo ; Götz, Marcelo ; Kuijper, Arjan ; Pereira, Carlos Eduardo ; Stork, André ; Fellner, Dieter W. (2010)
Effective Dynamic Scheduling on Heterogeneous Multi/Manycore Desktop Platforms.
SBAC-PADW 2010.
doi: 10.1109/SBAC-PADW.2010.6
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
GPUs (Graphics Processing Units) have become one of the main co-processors that contributed to desktops towards high performance computing. Together with multicore CPUs and other co-processors, a powerful heterogeneous execution platform is built on a desktop for data intensive calculations. In our perspective, we see the modern desktop as a heterogeneous cluster that can deal with several applications' tasks at the same time. To improve application performance and explore such heterogeneity, a distribution of workload over the asymmetric PUs (Processing Units) plays an important role for the system. However, this problem faces challenges since the cost of a task at a PU is non-deterministic and can be influenced by several parameters not known a priori, like the problem size domain. We present a context-aware architecture that maximizes application performance on such platforms. This approach combines a model for a first scheduling based on an offline performance benchmark with a runtime model that keeps track of tasks' real performance. We carried a demonstration using a CPU-GPU platform for computing iterative SLEs (Systems of Linear Equations) solvers using the number of unknowns as the main parameter for assignment decision. We achieved a gain of 38.3 in comparison to the static assignment of all tasks to the GPU (which is done by current programming models, such as OpenCL and CUDA for Nvidia).
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2010 |
| Autor(en): | Binotto, Alécio P. D. ; Pedras, Bernardo ; Götz, Marcelo ; Kuijper, Arjan ; Pereira, Carlos Eduardo ; Stork, André ; Fellner, Dieter W. |
| Art des Eintrags: | Bibliographie |
| Titel: | Effective Dynamic Scheduling on Heterogeneous Multi/Manycore Desktop Platforms |
| Sprache: | Englisch |
| Publikationsjahr: | 2010 |
| Verlag: | IEEE Computer Society Conference Publishing Services (CPS), Los Alamitos, Calif. |
| Veranstaltungstitel: | SBAC-PADW 2010 |
| DOI: | 10.1109/SBAC-PADW.2010.6 |
| Kurzbeschreibung (Abstract): | GPUs (Graphics Processing Units) have become one of the main co-processors that contributed to desktops towards high performance computing. Together with multicore CPUs and other co-processors, a powerful heterogeneous execution platform is built on a desktop for data intensive calculations. In our perspective, we see the modern desktop as a heterogeneous cluster that can deal with several applications' tasks at the same time. To improve application performance and explore such heterogeneity, a distribution of workload over the asymmetric PUs (Processing Units) plays an important role for the system. However, this problem faces challenges since the cost of a task at a PU is non-deterministic and can be influenced by several parameters not known a priori, like the problem size domain. We present a context-aware architecture that maximizes application performance on such platforms. This approach combines a model for a first scheduling based on an offline performance benchmark with a runtime model that keeps track of tasks' real performance. We carried a demonstration using a CPU-GPU platform for computing iterative SLEs (Systems of Linear Equations) solvers using the number of unknowns as the main parameter for assignment decision. We achieved a gain of 38.3 in comparison to the static assignment of all tasks to the GPU (which is done by current programming models, such as OpenCL and CUDA for Nvidia). |
| Freie Schlagworte: | Forschungsgruppe Semantic Models, Immersive Systems (SMIS), Graphics processors, Parallel processing, Computational fluid dynamics (CFD) |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Graphisch-Interaktive Systeme |
| Hinterlegungsdatum: | 12 Nov 2018 11:16 |
| Letzte Änderung: | 04 Feb 2022 12:41 |
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