On the capacity of flash memories

Jiang, Anxiao; Bruck, Jehoshua

doi:10.1109/isita.2008.4895389

Cited by 7 publications

(4 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To study the storage capacity of flash memories, it is necessary to understand how accruately flash cells can be programmed using the iterative and monotonic programming method. This was studied in [18] based on an abstract programming-error model.…”

Section: Extended Information Theoretic Resultsmentioning

confidence: 99%

Data Representation for Flash Memories

Jiang¹,

Bruck²

2010

Data Storage

Self Cite

View full text Add to dashboard Cite

In this chapter, we introduce theories on data representation for flash memories. Flash memories are a milestone in the development of the data storage technology. The applications of flash memories have expanded widely in recent years, and flash memories have become the dominating member in the family of non-volatile memories. Compared to magnetic recording and optical recording, flash memories are more suitable for many mobile-, embeddedand mass-storage applications. The reasons include their high speed, physical robustness, and easy integration with circuits. The representation of data plays a key role in storage systems. Like magnetic recording and optical recording, flash memories have their own distinct properties, including block erasure, iterative cell programming, etc. These distinct properties introduce very interesting coding problems that address many aspects of a successful storage system, which include efficient data modification, error correction, and more. In this chapter, we first introduce the flash memory model, then study some newly developed codes, including codes for rewriting data and the rank modulation scheme. A main theme is understanding how to store information in a medium that has asymmetric properties when it transits between different states.

show abstract

Section: Extended Information Theoretic Resultsmentioning

confidence: 99%

Data Representation for Flash Memories

Jiang¹,

Bruck²

2010

Data Storage

Self Cite

View full text Add to dashboard Cite

show abstract

“…In addition to flash memories [10], the cell-programming problem for phase-change memories has also been studied in recent years [15]. Similar to flash memories, the phase-change memory cells can also be programmed multiple times to achieve higher accuracy.…”

Section: Overview Of Related Workmentioning

confidence: 99%

On the Capacity and Programming of Flash Memories

Jiang

Bruck

2012

IEEE Trans. Inform. Theory

Self Cite

View full text Add to dashboard Cite

Abstract-Flash memories are currently the most widely used type of nonvolatile memories. A flash memory consists of floating-gate cells as its storage elements, where the charge level stored in a cell is used to represent data. Compared to magnetic recording and optical recording, flash memories have the unique property that the cells are programmed using an iterative procedure that monotonically shifts each cell's charge level upward toward its target value. In this paper, we model the cell as a monotonic storage channel, and explore its capacity and optimal programming. We present two optimal programming algorithms based on a few different noise models and optimization objectives.

show abstract

“…Previous works considered programming schemes mostly for flash memory cells. In [9], an optimal programming algorithm was presented to maximize the number of bits that can be stored in a single cell, which achieves the zero-error storage capacity under a noisy model. In [10], an algorithm was shown for optimizing the expected cell programming precision, when the programming noise follows a random distribution.…”

Section: Introductionmentioning

confidence: 99%

Iterative Programming of Noisy Memory Cells

Horovitz

Yaakobi

Gad

et al. 2022

IEEE Trans. Commun.

Self Cite

View full text Add to dashboard Cite

In this paper, we study a model, which was first presented by Bunte and Lapidoth, that mimics the programming operation of memory cells. Under this paradigm we assume that cells are programmed sequentially and individually. The programming process is modeled as transmission over a channel, while it is possible to read the cell state in order to determine its programming success, and in case of programming failure, to reprogram the cell again. Reprogramming a cell can reduce the bit error rate, however this comes with the price of increasing the overall programming time and thereby affecting the writing speed of the memory. An iterative programming scheme is an algorithm which specifies the number of attempts to program each cell. Given the programming channel and constraints on the average and maximum number of attempts to program a cell, we study programming schemes which maximize the number of bits that can be reliably stored in the memory. We extend the results by Bunte and Lapidoth and study this problem when the programming channel is either the BSC, BEC, or Z channel. For the BSC and the BEC our analysis is also extended for the case where the error probabilities on consecutive writes are not necessarily the same. Lastly, we also study a related model which is motivated by the synthesis process of DNA molecules.

show abstract

On the capacity of flash memories

Cited by 7 publications

References 5 publications

Data Representation for Flash Memories

Data Representation for Flash Memories

On the Capacity and Programming of Flash Memories

Iterative Programming of Noisy Memory Cells

Contact Info

Product

Resources

About