In this paper, we present a multiprecision (MP) reconfigurable multiplier that incorporates variable precision, parallel processing (PP), razor-based dynamic voltage scaling (DVS), and dedicated MP operands scheduling to provide optimum performance for a variety of operating conditions. All of the building blocks of the proposed reconfigurable multiplier can either work as independent smaller-precision multipliers or work in parallel to perform higher-precision multiplications. Given the user's requirements (e.g., throughput), a dynamic voltage/frequency scaling management unit configures the multiplier to operate at the proper precision and frequency. Adapting to the run-time workload of the targeted application, razor flip-flops together with a dithering voltage unit then configure the multiplier to achieve the lowest power consumption. The single-switch dithering voltage unit and razor flip-flops help to reduce the voltage safety margins and overhead typically associated to DVS to the lowest level. The large silicon area and power overhead typically associated to reconfigurability features are removed. Finally, the proposed novel MP multiplier can further benefit from an operands scheduler that rearranges the input data, hence to determine the optimum voltage and frequency operating conditions for minimum power consumption. This low-power MP multiplier is fabricated in AMIS 0.35-μm technology. Experimental results show that the proposed MP design features a 28.2% and 15.8% reduction in circuit area and power consumption compared with conventional fixed-width multiplier. When combining this MP design with error-tolerant razor-based DVS, PP, and the proposed novel operands scheduler, 77.7%-86.3% total power reduction is achieved with a total silicon area overhead as low as 11.1%. This paper successfully demonstrates that a MP architecture can allow more aggressive frequency/supply voltage scaling for improved power efficiency. © 2013 IEEE.
|Journal||IEEE Transactions on Very Large Scale Integration (VLSI) Systems|
|Publication status||Published - Apr 2014|