Efficient hierarchical clustering method for the multiple constant multiplication problem

In this paper, we propose an efficient solution for the Multiple Constant Multiplication (MCM) problem. The method exploits common subexpressions among constants based on hierarchical clustering and reduce the number of shifts, additions, and subtractions. The algorithm defines appropriate weights which indicate the operation priorities and selects the common subexpressions which results in the least number of local operations. It can also be extended to various high-level synthesis tasks such as arbitrary linear transforms. Experimental results show the effectiveness of our method.