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  4. FPGA-SPICE: A Simulation-based Power Estimation Framework for FPGAs
 
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FPGA-SPICE: A Simulation-based Power Estimation Framework for FPGAs

Tang, Xifan  
•
Gaillardon, Pierre-Emmanuel
•
De Micheli, Giovanni  
2015
Proceedings of the 33rd IEEE International Conference on Computer Design (ICCD)
33rd IEEE International Conference on Computer Design (ICCD)

Mainstream Field Programmable Gate Array (FPGA) power estimation tools are based on probabilistic activity estimation and analytical power models. The power consumption of the programmable resources of FPGAs is highly sensitive to their configurations. Due to their highly flexible nature, the configurations of FPGAs routing multiplexers or Look Up Tables (LUTs) are really different from a design to another but current analytical power models cannot accurately capture the associated power differences. In this paper, we introduce a simulation-based power estimation framework for FPGAs, called FPGA-SPICE, which supports any FPGA architecture that can be described with an architectural description language. Our power estimation engine automatically generates accurate SPICE netlists according to the FPGA configurations and enables precise power analysis of FPGA architectures. SPICE testbenches can be generated at different level of complexity, denoted as full-chip-level, grid-level and component-level testbenches. Full-chip-level testbenches dump the netlists associated with the complete FPGA fabric. To reduce simulation time, FPGA-SPICE can split the full-chip-level testbenches into grid-level testbenches, each of which consisting of a complete logic block netlist, or component-level testbenches, which consider individual circuit elements, i.e., multiplexers, LUTs, flip-flops, etc., separately. We show that the grid/component-level approach can achieve 14 x speed-up with a moderate 14% accuracy loss, compared to the full-chip level. We also use FPGA-SPICE to study the power characteristics of a commercial FPGA architecture at different technology nodes. Experimental results show that the global routing architecture consumes 50% of the total power, the local routing architecture claims for 40% of the total power, and the remaining 10% comes from the LUTs and flip-flops.

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