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

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 1 KByte to 8KByte