Multi-dimensional interleaving for time-and-memory design optimization

Abstract

This paper presents a novel optimization technique for the design of application specific integrated circuits dedicated to perform iterative or recursive time-critical sections of multi-dimensional problems, such as image processing applications. These sections are modeled as cyclic multi-dimensional data flow graphs (MDFGs). This new technique, called multi-dimensional interleaving consists of an expansion and compression of the iteration space while considering memory requirements. It guarantees that all functional elements of a circuitry can be executed simultaneously, and no additional memory queues proportional to the problem size are required. The algorithm runs in O(|E|) time, where E is the set of edges of the MDFG representing the circuit.