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| Content Provider | Springer Nature Link |
|---|---|
| Author | Boulos, Vincent Huet, Sylvain Fristot, Vincent Salvo, Luc Houzet, Dominique |
| Copyright Year | 2012 |
| Abstract | Nowadays, it is possible to build a multi-GPU supercomputer, well suited for implementation of digital signal processing algorithms, for a few thousand dollars. However, to achieve the highest performance with this kind of architecture, the programmer has to focus on inter-processor communications, tasks synchronization. In this paper, we propose a high level programming model based on a data flow graph (DFG) allowing an efficient implementation of digital signal processing applications on a multi-GPU computer cluster. This DFG-based design flow abstracts the underlying architecture. We focus particularly on the efficient implementation of communications by automating computation–communication overlap, which can lead to significant speedups as shown in the presented benchmark. The approach is validated on three experiments: a multi-host multi-gpu benchmark, a 3D granulometry application developed for research on materials and an application for computing visual saliency maps. |
| Starting Page | 217 |
| Ending Page | 232 |
| Page Count | 16 |
| File Format | |
| ISSN | 18618200 |
| Journal | Journal of Real-Time Image Processing |
| Volume Number | 9 |
| Issue Number | 1 |
| e-ISSN | 18618219 |
| Language | English |
| Publisher | Springer Berlin Heidelberg |
| Publisher Date | 2012-10-10 |
| Publisher Place | Berlin, Heidelberg |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | GPU cluster Data flow graph (DFG) Computation communication overlap Image Processing and Computer Vision Multimedia Information Systems Computer Graphics Pattern Recognition Signal, Image and Speech Processing |
| Content Type | Text |
| Resource Type | Article |
| Subject | Information Systems |
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