ILP-based bitwidth-aware subexpression sharing for area minimization in multiple constant multiplication

Bu Ching Lin, Juinn-Dar Huang, Jing Yang Jou

Research output: Contribution to journalArticlepeer-review

Abstract

The notion of multiple constant multiplication (MCM) is extensively adopted in digital signal processing (DSP) applications such as finite impulse filter (FIR) designs. A set of adders is utilized to replace regular multipliers for the multiplications between input data and constant filter coefficients. Though many algorithms have been proposed to reduce the total number of adders in an MCM block for area minimization, they do not consider the actual bitwidth of each adder, which may not estimate the hardware cost well enough. Therefore, in this article we propose a bitwidth-aware MCM optimization algorithm that focuses on minimizing the total number of adder bits rather than the adder count. It first builds a subexpression graph based on the given coefficients, derives a set of constraints for adder bitwidth minimization, and then optimally solves the problem through integer linear programming (ILP). Experimental results show that the proposed algorithm can effectively reduce the required adder bit count and outperforms the existing state-of-the-art techniques.

Original languageEnglish
Pages (from-to)931-939
Number of pages9
JournalIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
VolumeE97-A
Issue number4
DOIs
StatePublished - 1 Jan 2014

Keywords

  • Bitwidth
  • Finite impulse response (FIR) filter
  • Integer linear programming (ILP)
  • Multiple constant multiplication (MCM)

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