Low-Power and High-Speed Approximate Multiplier Design with a Tree Compressor

Many applications, such as image signal processing, has an inherent tolerance for insignificant inaccuracies. Multipliers are key arithmetic functions for many error-tolerant applications. Approximate multipliers are considered an efficient technique to trade off energy relative to performance and accuracy. We propose two approximate multiplier designs that demonstrate lower power consumption and shorter critical path delay than the conventional multiplier by employing an approximate tree compressor. The proposed compressor halves the height of the partial product tree and generates a vector to recover accuracy. Compared to the conventional Wallace tree multiplier, one of the proposed 8-bit approximate multipliers reduces power consumption and critical path delay by 59.9% and 36.3%, respectively. Furthermore, with 0.28% normalized mean error distance, the silicon area required to implement the multiplier is reduced by 50.1%. The proposed approximate multiplier designs outperform previous multipliers relative to power consumption, critical path delay, and design area.

[1]  Marian Verhelst,et al.  DVAS: Dynamic Voltage Accuracy Scaling for increased energy-efficiency in approximate computing , 2015, 2015 IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED).

[2]  Fabrizio Lombardi,et al.  Approximate compressors for error-resilient multiplier design , 2015, 2015 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFTS).

[3]  Fabrizio Lombardi,et al.  New Metrics for the Reliability of Approximate and Probabilistic Adders , 2013, IEEE Transactions on Computers.

[4]  Kaushik Roy,et al.  Quality programmable vector processors for approximate computing , 2013, 2013 46th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO).

[5]  Mark S. K. Lau,et al.  Energy-aware probabilistic multiplier: design and analysis , 2009, CASES '09.

[6]  Fabrizio Lombardi,et al.  Design and Analysis of Approximate Compressors for Multiplication , 2015, IEEE Transactions on Computers.

[7]  Fabrizio Lombardi,et al.  A low-power, high-performance approximate multiplier with configurable partial error recovery , 2014, 2014 Design, Automation & Test in Europe Conference & Exhibition (DATE).

[8]  Sherief Reda,et al.  DRUM: A Dynamic Range Unbiased Multiplier for approximate applications , 2015, 2015 IEEE/ACM International Conference on Computer-Aided Design (ICCAD).

[9]  Earl E. Swartzlander,et al.  Analysis of column compression multipliers , 2001, Proceedings 15th IEEE Symposium on Computer Arithmetic. ARITH-15 2001.

[10]  Caro Lucas,et al.  Bio-Inspired Imprecise Computational Blocks for Efficient VLSI Implementation of Soft-Computing Applications , 2010, IEEE Transactions on Circuits and Systems I: Regular Papers.

[11]  Kaushik Roy,et al.  Low-Power Digital Signal Processing Using Approximate Adders , 2013, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.