Approximate memory-based logic synthesis of index generation functions using linear decomposition

Abstract

Approximate logic synthesis has gained much interest lately due to the benefits in terms of the cost, i.e., energy and resource requirements. In this paper, we analyze the application of this emerging paradigm in the memory-based logic synthesis of incompletely specified index generation functions. In particular, we focus on the reduction of the number of input variables to minimize memory consumption. We present a heuristic method that combines the approximate approach and linear decomposition. Results obtained for some well-known index generation functions are evaluated using the exact approach.