Automated fixed-point data-type optimization tool for signal processing and communication systems

  • Authors:
  • Changchun Shi;Robert W. Brodersen

  • Affiliations:
  • University of California at Berkeley, CA;University of California at Berkeley, CA

  • Venue:
  • Proceedings of the 41st annual Design Automation Conference
  • Year:
  • 2004

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Abstract

A tool that automates the floating-point to fixed-point conversion (FFC) process for digital signal processing systems is described. The tool automatically optimizes fixed-point data types of arithmetic operators, including overflow modes, integer word lengths, fractional word lengths, and the number systems. The approach is based on statistical modeling, hardware resource estimation and global optimization based on an initial structural system description. The basic technique exploits the fact that the fixed point realization is a weak perturbation of the floating point realization which allows the development of a system model which can be used in the optimization process.