Condition Graphs For High-quality Behavioral Synthesis

Abstract

Identifying mutual exclusiveness between operators during behavioral synthesis is important in order to reduce the required number of control steps or hardware resources. To improve the quality of the synthesis result, we propose a representation, the Condition Graph, and an algorithm for identification of mutually exclusive operators. Previous research efforts have concentrated on identifying mutual exclusiveness by examining language constructs such as IF-THEN-ELSE statements. Thus, their results heavily depend on the description styles. The proposed approach can produce results independent of description styles and identify more mutually exclusive operators than any previous approaches. The Condition Graph and the proposed algorithm can be used in any scheduling or binding algorithms. Experimental results on several benchmarks have shown the efficiency of the proposed representation and algorithm.