Dynamic code mapping for limited local memory systems

Abstract

This paper presents heuristics for dynamic management of application code on limited local memories present in high-performance multi-core processors. Previous techniques formulate the problem using call graphs, which do not capture the temporal ordering of functions. In addition, they only use a conservative estimate of the interference cost between functions to obtain a mapping. As a result previous techniques are unable to achieve efficient code mapping. Techniques proposed in this paper overcome both these limitations and achieve superior code mapping. Experimental results from executing benchmarks from MiBench onto the Cell processor in the Sony Playstation 3 demonstrate up to 29% and average 12% performance improvement, at tolerable compile-time overhead.