Reducing Power and Energy Overhead in Instruction Prefetching for Embedded Processor Systems

Abstract

Instruction prefetching is an effective way to improve performance of the pipelined processors. However, existing instruction prefetching schemes increase performance with a significant energy sacrifice, making them unsuitable for embedded and ubiquitous systems where high performance and low energy consumption are all demanded. This paper proposes reducing energy overhead in instruction prefetching by using a simple hardware/software design and an efficient prefetching operation scheme. Two approaches are investigated: Decoded Loop Instruction Cache based Prefetching DLICP that is most effective for loop intensive applications, and the enhanced DLICP with the popular existing Next Line Prefetching NLP for applications of a moderate number of loops. The experimental results show that both DLICP and the enhanced DLICP deliver improved performance at a much reduced energy overhead.