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CIF: Small: Coding for Non-Volatile Memories

$500,000FY2011CSENSF

University Of California-San Diego, La Jolla CA

Investigators

Abstract

Non-volatile data storage devices, particularly those based upon NAND flash memory and emerging phase-change memory (PCM) technologies, are revolutionizing the way we access and manipulate information. They have many attractive features compared to magnetic hard disk drives, including their compactness, shock resistance, and faster data access. Flash memory is now preferred in portable consumer electronics, and high performance solid-state drives (SSDs) are being introduced in mobile computing, enterprise storage, data warehousing, and data-intensive computing applications. Accordingly, there is a surge in interest in the refinement, development, and expanded commercial use of these non-volatile memory technologies. On the other hand, these technologies present major challenges in the areas of device reliability, endurance, and energy efficiency. These challenges can be overcome, in part, through innovative coding and data handling techniques, which is the subject of this research project. Specifically, the problems addressed include: (1) the design of efficient, error-resilient rewriting codes for single-level cell (SLC) flash memories using write-once memory (WOM) coding techniques; (2) the design of non-binary rewriting codes for multi-level cell (MLC) flash memories, as well as codes that tolerate asymmetric cell-level transitions and writing errors; (3) the development of coding techniques that mitigate the effects of heat accumulation in PCMs; and (4) the design of error-correcting codes for PCMs with stuck cells. The research involves the information-theoretic analysis of flash memory and PCM channel models, the development of novel coding schemes, and system performance evaluation. A unique aspect of the project is the use of the facilities of the Non-Volatile Systems Laboratory at UC San Diego, providing an experimental platform for device characterization and empirical performance comparisons of new coding techniques and architectures.

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