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Published Articles >> Table of Contents >> Abstract
IEEE Computer Society Annual Symposium on VLSI (ISVLSI'03)
p. 222
Automated Dynamic Memory Data Type Implementation Exploration and Optimization
Marc Leeman, ESAT K.U. Leuven
Chantal Ykman, ESAT K.U. Leuven
David Atienza, ESAT K.U. Leuven
Vincenzo De Florio, ESAT K.U. Leuven
Geert Deconinck, ESAT K.U. Leuven
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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ISVLSI.2003.1183476
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| Abstract |
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The behavior of many algorithms is heavily determined by the input data. Furthermore, this often means that multiple and completely different execution paths can be followed, also internal data usage and handling is frequently quite different. Therefore, static compile time memory allocation is not efficient, especially on embedded systems where memory is a scarce resource, and dynamic memory management is the only feasible alternative. Including applications with dynamic memory in embedded systems introduces new challenges as compared to traditional signal processing applications. In this session, an automated framework is presented to optimize embedded applications with extensive use of dynamic memory management. The proposed methodology automates the exploration and identification of optimal data type implementations based on power estimates, memory accesses and normalized memory usage.
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Citation:
Marc Leeman, Chantal Ykman, David Atienza, Vincenzo De Florio, Geert Deconinck,
"Automated Dynamic Memory Data Type Implementation Exploration and Optimization,"
isvlsi,
p. 222,
IEEE Computer Society Annual Symposium on VLSI (ISVLSI'03),
2003
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