Search space definition and exploration for nonuniform data reuse opportunities in data-dominant applications

Abstract

Efficient exploitation of temporal locality in the memory accesses on array signals can have a very large impact on the power consumption in embedded data dominated applications. The effective use of an optimized custom memory hierarchy or a customized software controlled mapping on a predefined hierarchy is crucial for this. Only recently have effective systematic techniques to deal with this specific design step begun to appear. They are still limited in their exploration scope. In this paper we construct the design space by introducing three parameters which determine how and when copies are made between different levels in a hierarchy, and determine their impact on the total memory size, storage-related power consumption, and code complexity. Strategies are then established for an efficient exploration, such that cost-effective solutions for the memory size/power trade-off can be achieved. The effectiveness of the techniques is demonstrated for several real-life image processing algorithms.