An analytical approach for error PMF characterization in approximate circuits

Deepashree Sengupta, Farhana Sharmin Snigdha, Jiang Hu, Sachin S. Sapatnekar

Research output: Contribution to journalArticle

1 Scopus citations


Approximate computing has emerged as a circuit design technique that can reduce system power without significantly sacrificing the output quality in error-resilient applications. However, there exists only a few approaches for systematically and efficiently determining the error introduced by approximate hardware units. This paper focuses on the development of error analysis techniques for approximate circuits consisting of adders and multipliers, which are the key hardware components used in error-resilient applications. A novel algorithm has been presented, using the Fourier and the Mellin transforms, that efficiently determines the probability distribution of the error introduced by approximation in a circuit, abstracted as a directed acyclic graph. The algorithm is generalized for signed operations through two's complement representation, and its accuracy is demonstrated to be within 1% of Monte Carlo simulations, while being over an order of magnitude faster.

Original languageEnglish (US)
Article number8283743
Pages (from-to)70-83
Number of pages14
JournalIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Issue number1
StatePublished - Jan 2019



  • Approximate computing
  • Fourier transform
  • Mellin transform
  • error distribution

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