A low latency generic accuracy configurable adder

High performance approximate adders typically comprise of multiple smaller sub-adders, carry prediction units and error correction units. In this paper, we present a low-latency generic accuracy configurable adder to support variable approximation modes. It provides a higher number of potential configurations compared to state-of-the-art, thus enabling a high degree of design flexibility and trade-off between performance and output quality. An error correction unit is integrated to provide accurate results for cases where high accuracy is required. Furthermore, an associated scheme for error probability estimation allows convenient comparison of different approximate adder configurations without requiring the need to numerically simulate the adder. Our experimental results validate the developed error model and also the lower latency of our generic accuracy configurable adder over state-of-the-art approximate adders. For functional verification and prototyping, we have used a Xilinx Virtex-6 FPGA. Our adder model and synthesizable RTL are made open-source.

[1]  Olga Veksler,et al.  Fast variable window for stereo correspondence using integral images , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[2]  Paolo Ienne,et al.  Variable Latency Speculative Addition: A New Paradigm for Arithmetic Circuit Design , 2008, 2008 Design, Automation and Test in Europe.

[3]  A. Leon-Garcia Probability, statistics, and random processes for electrical engineering , 2008 .

[4]  Gauthier Lafruit,et al.  Cross-Based Local Stereo Matching Using Orthogonal Integral Images , 2009, IEEE Transactions on Circuits and Systems for Video Technology.

[5]  Kaushik Roy,et al.  Scalable effort hardware design: Exploiting algorithmic resilience for energy efficiency , 2010, Design Automation Conference.

[6]  Gang Wang,et al.  Enhanced low-power high-speed adder for error-tolerant application , 2009, 2010 International SoC Design Conference.

[7]  Xing Mei,et al.  On building an accurate stereo matching system on graphics hardware , 2011, 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops).

[8]  Gennady Pekhimenko,et al.  Approximate Computing : Application Analysis and Hardware Design , 2011 .

[9]  Ku He,et al.  Modeling and synthesis of quality-energy optimal approximate adders , 2012, 2012 IEEE/ACM International Conference on Computer-Aided Design (ICCAD).

[10]  Luis Ceze,et al.  Architecture support for disciplined approximate programming , 2012, ASPLOS XVII.

[11]  Andrew B. Kahng,et al.  Accuracy-configurable adder for approximate arithmetic designs , 2012, DAC Design Automation Conference 2012.

[12]  Rakesh Kumar,et al.  On reconfiguration-oriented approximate adder design and its application , 2013, 2013 IEEE/ACM International Conference on Computer-Aided Design (ICCAD).

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

[14]  Kaushik Roy,et al.  Analysis and characterization of inherent application resilience for approximate computing , 2013, 2013 50th ACM/EDAC/IEEE Design Automation Conference (DAC).

[15]  Asit K. Mishra,et al.  iACT: A Software-Hardware Framework for Understanding the Scope of Approximate Computing , 2014 .