Transforming set data types to power optimal data structures

In this paper, we present a novel approach to model the search space for the custom implementation of set data types, a data type that is commonly found in important application domains such as network component realizations and database applications. The main objective is to arrive at power efficient realizations of these data types in custom data structures, but the model can also be used with nonpower cost functions. Based on the model, we propose an efficient optimization method for finding the implementation with minimum power consumption without performing an exhaustive scan of the search space. The range of power costs for different solutions can easily span four orders of magnitude, so a near optimal solution is crucial. This paper also strongly contributes to our overall goal of a higher level of specification and shorter design cycles for table-based memory organizations for applications where these data types are frequently used. The proposed model and methodology are suited for both hardware and software realizations.