Power estimation approach for SRAM-based FPGAs
FPGA '00 Proceedings of the 2000 ACM/SIGDA eighth international symposium on Field programmable gate arrays
A Flexible Power Model for FPGAs
FPL '02 Proceedings of the Reconfigurable Computing Is Going Mainstream, 12th International Conference on Field-Programmable Logic and Applications
Power Estimation and Power Measurement of Xilinx Virtex FPGAs: Trade-Offs and Limitations
SBCCI '03 Proceedings of the 16th symposium on Integrated circuits and systems design
Methodology for high level estimation of FPGA power consumption
Proceedings of the 2005 Asia and South Pacific Design Automation Conference
A system for processing handwritten bank checks automatically
Image and Vision Computing
Power Consumption Estimations vs Measurements for FPGA-Based Security Cores
RECONFIG '08 Proceedings of the 2008 International Conference on Reconfigurable Computing and FPGAs
IEEE Transactions on Computers
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The design space of FPGA-based processor systems is huge, because many parameters can be modified at design- and runtime to achieve an efficient system solution in terms of performance, power and energy consumption. Such parameters are, for example, the number of processors and their configurations, the clock frequencies at design time, the use of dynamic frequency scaling at runtime, the application task distribution, and the FPGA type and size. The major contribution of this paper is the exploration of all these parameters and their impact on performance, power dissipation, and energy consumption for four different application scenarios. The goal is to introduce a first approach for a developer's guideline, supporting the choice of an optimized and specific system parameterization for a target application on FPGA-based multiprocessor systems-on-chip. The FPGAs used for these explorations were Xilinx Virtex-4 and Xilinx Virtex-5. The performance results were measured on the FPGA while the power consumption was estimated using the Xilinx XPower Analyzer tool. Finally, a novel runtime adaptive multiprocessor architecture for dynamic clock frequency scaling is introduced and used for the performance, power and energy consumption evaluations.