A Proposal for Input-sensitivity Analysis of Profile-driven Optimizations on Embedded Applications

摘要

The ever-increasing gap between processor and memory speed is an issue also in embedded systems, because of the increased complexity of multimedia elaborations and the strict resource constraints of these devices. Profile-driven code optimization techniques can be effectively employed for tuning application-cache interaction and performances of cache system itself. In fact, applications running on such systems are usually known in advance and do not change over time. In a previous paper, we presented a profile-based code restructuring technique (CAT) that was able to dramatically increase cache exploitation of embedded applications. However, it is well known that profile-driven optimizations can suffer from input-sensitivity problems: an application that is optimized for a particular input can perform even worse than the original one, when subjected other inputs. In this paper we take into account jpeg and mpeg compressor/decompressor applications and analyze the input-sensitivity of CAT improved layouts over a wide range of inputs. The input sets were accurately determined through both black-box and white-box analysis of applications. We propose two metrics for measuring the input-sensitivity of application layouts, and show how our profile-driven code transformation technique is able to reduce the input-sensitivity of the considered applications up to 48% on caches ranging from 1KByte to 8KByte.