Multi-profile instruction based compression

Code compression has been used to minimize the memory area requirement of embedded systems. Recently, performance improvement and energy consumption reduction are observed as a by-product of compression. In this paper we propose a novel technique for efficiently exploring the trade-offs involved in code compression. Our multiprofile approach to build dictionaries combines the best features of both static and dynamic program behaviors. The experiments with Mediabench and MiBench suites and the Leon (SPARCv8) processor reveal a compression ratio as low as 71% while performance speed-up reaches 1.5.