Huffman coding with unequal letter costs
STOC '02 Proceedings of the thiry-fourth annual ACM symposium on Theory of computing
Low-energy off-chip SDRAM memory systems for embedded applications
ACM Transactions on Embedded Computing Systems (TECS)
Probability and Random Processes For EE's (3rd Edition)
Probability and Random Processes For EE's (3rd Edition)
A dynamic programming algorithm for constructing optimal prefix-free codes with unequal letter costs
IEEE Transactions on Information Theory
ACM Transactions on Design Automation of Electronic Systems (TODAES)
An energy-efficient I/O request mechanism for multi-bank flash-memory storage systems
ACM Transactions on Design Automation of Electronic Systems (TODAES)
Power Modeling of Solid State Disk for Dynamic Power Management Policy Design in Embedded Systems
SEUS '09 Proceedings of the 7th IFIP WG 10.2 International Workshop on Software Technologies for Embedded and Ubiquitous Systems
A reliable MTD design for MLC flash-memory storage systems
EMSOFT '10 Proceedings of the tenth ACM international conference on Embedded software
Meta-Cure: a reliability enhancement strategy for metadata in NAND flash memory storage systems
Proceedings of the 49th Annual Design Automation Conference
Underpowering NAND flash: profits and perils
Proceedings of the 50th Annual Design Automation Conference
ACM Transactions on Embedded Computing Systems (TECS)
Migration-based hybrid cache design for file systems over flash storage devices
ACM SIGAPP Applied Computing Review
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We discover significant value-dependent programming energy variations in multi-level cell (MLC) flash memories, and introduce an energy-aware data compression method that minimizes the flash programming energy rather than the size of the compressed data. We express energy-aware data compression as an entropy coding with unequal bit-pattern costs. Deploying a probabilistic approach, we derive the energy-optimal bit-pattern probabilities and the expected values of the bit-pattern costs for the large amounts of compressed data which are typical in multimedia applications. Then we develop an energy-optimal prefix coding that uses integer linear programming, and construct a prefix code table. From a consideration of Pareto-optimal energy consumption, we make tradeoffs between data size and programming energy, such as a 35% energy saving for a 50% area overhead.