Profile-driven compression scheme for embedded systems

Abstract

The extensive usage of embedded systems involves running complex applications that require tightly limited resources such as memory and storage. One efficient way to satisfy the resource requirements is to reduce the code size through code compression. Our work describes a software-based code compression scheme that reduces the storage space of a program, which in turn induces a reduction of access time to off-chip memory in SoC embedded architectures. To select those sections of code that are most advantageous for compression, our scheme utilizes profiling information to evaluate and trade off storage space reduction for future run-time overhead. During run-time, the compressed parts are decompressed as necessary into a run-time buffer for execution. Experimental results on the SPEC CPU2000 and MediaBench suites show reduction in code size averaging 18.5%, along with reasonable memory consumption overhead averaging 3.8%, and a reasonable run-time overhead averaging 7.8%.