A dynamic partial reconfiguration design flow for permanent faults mitigation in FPGAs

2018 ◽  
Vol 83 ◽  
pp. 50-63 ◽  
Author(s):  
Victor Manuel Gonçalves Martins ◽  
Paulo Ricardo Cechelero Villa ◽  
Rodrigo Travessini ◽  
Marcelo Daniel Berejuck ◽  
Eduardo Augusto Bezerra
Keyword(s):  
Design Flow ◽  
Partial Reconfiguration ◽  
Dynamic Partial Reconfiguration ◽  
Permanent Faults

High-level design flow and environment for FPGA-based dynamic partial reconfiguration

2017 ◽  
Vol 104 (8) ◽  
pp. 1254-1284
Author(s):  
Abdessalem Ben Abdelali ◽  
Marwa Hannachi ◽  
Mohamed Nidhal Krifa ◽  
Hassan Rabah ◽  
Abdellatif Mtibaa
Keyword(s):  
Design Flow ◽  
Partial Reconfiguration ◽  
Dynamic Partial Reconfiguration ◽  
Level Design ◽  
High Level

A Hardware/Software Co-Design Flow for Dynamic Partial Reconfiguration

2012 ◽  
Vol 433-440 ◽  
pp. 5172-5177
Author(s):  
Xiao Jing Feng ◽  
Xi Li ◽  
Wang Chao ◽  
Xue Hai Zhou ◽  
Jun Neng Zhang
Keyword(s):  
Embedded Systems ◽  
Hardware Design ◽  
Design Flow ◽  
Experimental Results ◽  
Prototype System ◽  
Partial Reconfiguration ◽  
Dynamic Partial Reconfiguration ◽  
Software And Hardware ◽  
Reconfiguration Overhead ◽  
Hardware Designs

The strict requirements on both performance and flexibility lead us to apply Dynamic Partial Reconfiguration (DPR) technology in embedded systems. However, existing DPR design flows are still immature, since previous works mainly focus on hardware designs while ignore software designs for DPR. To remedy this weakness, this paper proposes a hardware/software (HW/SW) co-design flow for DPR. The co-design flow aims at accelerating the process of DPR designs, and it merges software and hardware design flows to make them operate in parallel. Besides, in order to validate the effectiveness of our co-design flow, we implement a partial self-reconfigurable prototype system on Xilinx Virtex-5 platform and perform a set of experiments. Experimental results present that the reconfiguration overhead for partial reconfiguration is only 4.66% against global reconfiguration in our prototype. It’s also presented that our prototype can achieve a 23.6 × speedup over software algorithm solutions.

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