Efficient reconfigurable regions management method for adaptive and dynamic FPGA based systems
Adaptive systems based on field programmable gate array (FPGA) architectures can greatly benefit from the high degree of flexibility offered by dynamic partial reconfiguration (DPR). By using this technique, hardware tasks can be loaded and reloaded on demand depending on the system requirements. I...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2017-11-01
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| Series: | Kuwait Journal of Science |
| Subjects: | |
| Online Access: | https://journalskuwait.org/kjs/index.php/KJS/article/view/2021 |
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| Summary: | Adaptive systems based on field programmable gate array (FPGA) architectures can greatly benefit from the high degree of flexibility offered by dynamic partial reconfiguration (DPR). By using this technique, hardware tasks can be loaded and reloaded on demand depending on the system requirements. In this paper, we propose to use the DPR for dynamic and adaptive implementation of a video cut detection application based on the MPEG-7 color structure descriptor (CSD). In the proposed implementation, different scenarios have been tested. Depending on the application and the system requirements, the CSD module can be loaded at any time with variable module size (corresponding to different version of the CSD) and allocated in different possible reconfigurable regions. Such implementation entails
many problems related to communication, relocation and reconfigurable region anagement. We will demonstrate how we have made this implementation successful through the use of an appropriate design method. This method was proposed to support the management of variable-size hardware tasks on DPR FPGAs based adaptive systems. It permits to efficiently handle the reconfigurable area and to relocate the reconfigurable modules in different possible regions. The implementation results for the considered application show an important optimization in terms of configuration time (until 66 %) and memory storage (until 87 %) and an efficient hardware resources utilization rate (until 90%).
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| ISSN: | 2307-4108 2307-4116 |