Minimizing Scrubbing Effort through Automatic Netlist Partitioning and Floorplanning
Author(s): Schmidt B, Ziener D, Teich J
Title edited volumes: Proceedings of the International Parallel and Distributed Processing Symposium, IPDPS
Publisher: IEEE Computer Society
Publication year: 2014
Conference Proceedings Title: Proc. of the Reconfigurable Architectures Workshop (RAW)
Pages range: 299-304
Event: Reconfigurable Architectures Workshop (RAW)
Event location: Phoenix
Start date of the event: 19/05/2014
End date of the event: 23/05/2014
Existing techniques for SEU mitigation on FPGAs by scrubbing do not prevent permanent malfunction of a circuit design in case that the corresponding configuration bits do belong to feedback loops. In this paper, we a) provide a circuit analysis technique to distinguish so-called critical bits from essential bits to determine which parts of a bitstream will need also state-restoring actions after scrubbing and which not. Moreover, b) we will propose floorplanning techniques to reduce the effective number of frames that need to be scrubbed and c), experimental results will give evidence that our optimization methodology not only allows to detect errors earlier but also to minimize the Mean-Time-To-Repair (MTTR) of a circuit considerably. In particular, we show that by using our approach, the MTTR for datapath-intensive circuits may be reduced by up to 48.5% in comparison to a standard approach. For the MTTR calculation, we assume a system with checkpointing using the Xilinx SEM IP core to implement the scrubbing controller.
FAU Authors / FAU Editors How to cite
APA: Schmidt, B., Ziener, D., & Teich, J. (2014). Minimizing Scrubbing Effort through Automatic Netlist Partitioning and Floorplanning. In Proc. of the Reconfigurable Architectures Workshop (RAW) (pp. 299-304). IEEE Computer Society.
MLA: Schmidt, Bernhard, Daniel Ziener, and Jürgen Teich. "Minimizing Scrubbing Effort through Automatic Netlist Partitioning and Floorplanning." Proceedings of the Reconfigurable Architectures Workshop (RAW), Phoenix IEEE Computer Society, 2014. 299-304.