Abstract
This paper describes how profile-driven data compression, a very effective approach to reduce memory and bus traffic in singletask embedded systems, can be extended to the case of systems offering multi-function services.
Application-specific profiling is replaced by static data characterization, which allows to cover a larger spectrum of the system’s input space; characterization is performed by either averaging several profiling runs over different application mixes, or by resorting to statistical techniques. Results concerning memory traffic show reductions ranging from 10% to 22%, depending on the adopted data characterization technique.
This work was supported in part by HP Italiana S.p.A. under grant n. 398/2000.
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Benini, L., Macii, A., Macii, E. (2002). Offine Data Profiling Techniques to Enhance Memory Compression in Embedded Systems. In: Hochet, B., Acosta, A.J., Bellido, M.J. (eds) Integrated Circuit Design. Power and Timing Modeling, Optimization and Simulation. PATMOS 2002. Lecture Notes in Computer Science, vol 2451. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45716-X_31
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DOI: https://doi.org/10.1007/3-540-45716-X_31
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