Evolutionary Standard Cell Synthesis of Unconventional Designs

Abstract

Conventional synthesis algorithms transform the behavioral RTL design to a standard cell mapped gate level netlist, with support to customize optimization effort of few operators. HDL description standards and current synthesis methods lack support to generate netlist of custom functions for quick validation and characterization of the design. Additionally, synthesis does not cater directly to various mathematical functions, design efforts towards approximating the desired function is needed. Hence a synthesis method for realizing circuits applicable to not only arithmetic but also to non-linear functions will be highly valuable and appreciated among the VLSI design community. This work employs Cartesian Genetic Programming (CGP) algorithm, an evolutionary design methodology suitable to synthesize digital circuits. CGP benefits in accelerating the design process and offers the ease to realize complex functions with little to no design effort. Activation functions are difficult to realize as combinational circuits using traditional design methods, this work validates the synthesis results for 6 non-linear activation functions using both classical and standard cell synthesis oriented CGP. The ability to incorporate such unconventional designs to the traditional synthesis flow will be instrumental for implementing accelerators in hardware space, and eventually for efficient design of heterogeneous SoC systems.