On Coding Efficiency for Flash Memories

Recently, flash memories have become a competitive solution for mass storage. The flash memories have rather different properties compared with the rotary hard drives. That is, the writing of flash memories is constrained, and flash memories can endure only limited numbers of erases. Therefore, the design goals for the flash memory systems are quite different from these for other memory systems. In this paper, we consider the problem of coding efficiency. We define the "coding-efficiency" as the amount of information that one flash memory cell can be used to record per cost. Because each flash memory cell can endure a roughly fixed number of erases, the cost of data recording can be well-defined. We define "payload" as the amount of information that one flash memory cell can represent at a particular moment. By using information-theoretic arguments, we prove a coding theorem for achievable coding rates. We prove an upper and lower bound for coding efficiency. We show in this paper that there exists a fundamental trade-off between "payload" and "coding efficiency". The results in this paper may provide useful insights on the design of future flash memory systems.Comment: accepted for publication in the Proceeding of the 35th IEEE Sarnoff Symposium, Newark, New Jersey, May 21-22, 201

Rank-Modulation Rewrite Coding for Flash Memories

The current flash memory technology focuses on the cost minimization of its static storage capacity. However, the resulting approach supports a relatively small number of program-erase cycles. This technology is effective for consumer devices (e.g., smartphones and cameras) where the number of program-erase cycles is small. However, it is not economical for enterprise storage systems that require a large number of lifetime writes. The proposed approach in this paper for alleviating this problem consists of the efficient integration of two key ideas: 1) improving reliability and endurance by representing the information using relative values via the rank modulation scheme and 2) increasing the overall (lifetime) capacity of the flash device via rewriting codes, namely, performing multiple writes per cell before erasure. This paper presents a new coding scheme that combines rank-modulation with rewriting. The key benefits of the new scheme include: 1) the ability to store close to 2 bit per cell on each write with minimal impact on the lifetime of the memory and 2) efficient encoding and decoding algorithms that make use of capacity-achieving write-once-memory codes that were proposed recently

Towards Endurable, Reliable and Secure Flash Memories-a Coding Theory Application

Storage systems are experiencing a historical paradigm shift from hard disk to nonvolatile memories due to its advantages such as higher density, smaller size and non-volatility. On the other hand, Solid Storage Disk (SSD) also poses critical challenges to application and system designers. The first challenge is called endurance. Endurance means flash memory can only experience a limited number of program/erase cycles, and after that the cell quality degradation can no longer be accommodated by the memory system fault tolerance capacity. The second challenge is called reliability, which means flash cells are sensitive to various noise and disturbs, i.e., data may change unintentionally after experiencing noise/disturbs. The third challenge is called security, which means it is impossible or costly to delete files from flash memory securely without leaking information to possible eavesdroppers. In this dissertation, we first study noise modeling and capacity analysis for NAND flash memories (which is the most popular flash memory in market), which gains us some insight on how flash memories are working and their unique noise. Second, based on the characteristics of content-replication codewords in flash memories, we propose a joint decoder to enhance the flash memory reliability. Third, we explore data representation schemes in flash memories and optimal rewriting code constructions in order to solve the endurance problem. Fourth, in order to make our rewriting code more practical, we study noisy write-efficient memories and Write-Once Memory (WOM) codes against inter-cell interference in NAND memories. Finally, motivated by the secure deletion problem in flash memories, we study coding schemes to solve both the endurance and the security issues in flash memories. This work presents a series of information theory and coding theory research studies on the aforesaid three critical issues, and shows that how coding theory can be utilized to address these challenges

Storage Techniques in Flash Memories and Phase-change Memories

Non-volatile memories are an emerging storage technology with wide applica- tions in many important areas. This study focuses on new storage techniques for flash memories and phase-change memories. Flash memories are currently the most widely used type of non-volatile memory, and phase-change memories (PCMs) are the most promising candidate for the next-generation non-volatile memories. Like magnetic recording and optical recording, flash memories and PCMs have their own distinct properties, which introduce very interesting data storage problems. They include error correction, cell programming and other coding problems that affect the reliability and efficiency of data storage. Solutions to these problems can signifi- cantly improve the longevity and performance of the storage systems based on flash memories and PCMs. In this work, we study several new techniques for data storage in flash memories and PCMs. First, we study new types of error-correcting codes for flash memories – called error scrubbing codes –that correct errors by only increasing cell levels. Error scrubbing codes can correct errors without the costly block erasure operations, and we show how they can outperform conventional error-correcting codes. Next, we study the programming strategies for flash memory cells, and present an adaptive algorithm that optimizes the expected precision of cell programming. We then study data storage in PCMs, where thermal interference is a major challenge for data reliability. We present two new coding techniques that reduce thermal interference, and study their storage capacities and code constructions

Trajectory Codes for Flash Memory

Flash memory is well-known for its inherent asymmetry: the flash-cell charge levels are easy to increase but are hard to decrease. In a general rewriting model, the stored data changes its value with certain patterns. The patterns of data updates are determined by the data structure and the application, and are independent of the constraints imposed by the storage medium. Thus, an appropriate coding scheme is needed so that the data changes can be updated and stored efficiently under the storage-medium's constraints. In this paper, we define the general rewriting problem using a graph model. It extends many known rewriting models such as floating codes, WOM codes, buffer codes, etc. We present a new rewriting scheme for flash memories, called the trajectory code, for rewriting the stored data as many times as possible without block erasures. We prove that the trajectory code is asymptotically optimal in a wide range of scenarios. We also present randomized rewriting codes optimized for expected performance (given arbitrary rewriting sequences). Our rewriting codes are shown to be asymptotically optimal.Comment: Submitted to IEEE Trans. on Inform. Theor