No abstract

Embedded systems are constrained by the available memory. Code compression techniques address this issue by reducing the code size of application programs. Dictionary-based code compression techniques are popular because they offer both good compression ratio and fast decompression scheme. Recently proposed techniques [8,9] improve standard dictionary-based compression by considering mismatches. This paper makes two important contributions: i) it provides a cost-benefit analysis framework for improving the compression ratio by creating more matching patterns, and ii) it develops an efficient code compression technique using bitmasks to improve the compression ratio without introducing any decompression penalty. To demonstrate the usefulness of our approach we have used applications from various domains and compiled for a wide variety of architectures. Our approach outperforms the existing dictionary-based techniques by an average of 15%, giving a compression ratio of 55% -65%.

Memory plays a crucial role in designing embedded systems. A larger memory can accommodate more and large applications but increases cost, area, as well as energy requirements. Code compression techniques address this problem by reducing the size of the applications. While early work on bitmask-based compression has proposed several promising ideas, many challenges remain in applying them to embedded system design. This paper makes two important contributions to address these challenges by developing application-specific bitmask selection and bitmask-aware dictionary selection techniques. We applied these techniques for code compression of TI and MediaBench applications to demonstrate the usefulness of our approach.

No abstract

Embedded systems are constrained by the available memory. Code compression techniques address this issue by reducing the code size of application programs. Dictionary-based code compression techniques are popular because they offer both good compression ratio and fast decompression scheme. Recently proposed techniques [8,9] improve standard dictionary-based compression by considering mismatches. This paper makes two important contributions: i) it provides a cost-benefit analysis framework for improving the compression ratio by creating more matching patterns, and ii) it develops an efficient code compression technique using bitmasks to improve the compression ratio without introducing any decompression penalty. To demonstrate the usefulness of our approach we have used applications from various domains and compiled for a wide variety of architectures. Our approach outperforms the existing dictionary-based techniques by an average of 15%, giving a compression ratio of 55% -65%.