The efficient design of multiplierless implementations of constant matrix multipliers is challenged by the huge solution search spaces even for small scale problems. Previous approaches tend to use hill-climbing algorithms risking sub-optimal results. The three-stage algorithm proposed in this paper partitions the global constant matrix multiplier into its constituent dot products, and all possible solutions are derived for each dot product in the first two stages. The third stage leverages the effective search capability of genetic programming to search for global solutions created by combining dot product partial solutions. A bonus feature of the algorithm is that the modelling is amenable to hardware acceleration. Another bonus feature is a search space reduction early exit mechanism, made possible by the way the algorithm is modelled. Results show an improvement on state of the art algorithms with future potential for even greater savings.
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