An efficient code compression technique using application-aware bitmask and dictionary selection methods

Memory play's 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.