Advanced Science and Technology Letters Vol.35(Software 2013), pp.19-22 Bi-Modal Flash Code using Index-less.

Slides:



Advertisements
Similar presentations
Noise-Predictive Turbo Equalization for Partial Response Channels Sharon Aviran, Paul H. Siegel and Jack K. Wolf Department of Electrical and Computer.
Advertisements

Jesper H. Sørensen, Toshiaki Koike-Akino, and Philip Orlik 2012 IEEE International Symposium on Information Theory Proceedings Rateless Feedback Codes.
Computer Architecture
Tuning of Loop Cache Architectures to Programs in Embedded System Design Susan Cotterell and Frank Vahid Department of Computer Science and Engineering.
Introduction to H.264 / AVC Video Coding Standard Multimedia Systems Sharif University of Technology November 2008.
Introduction to Algorithms Rabie A. Ramadan rabieramadan.org 2 Some of the sides are exported from different sources.
Bounds on Code Length Theorem: Let l ∗ 1, l ∗ 2,..., l ∗ m be optimal codeword lengths for a source distribution p and a D-ary alphabet, and let L ∗ be.
Source-Location Privacy Protection in Wireless Sensor Network Presented by: Yufei Xu Xin Wu Da Teng.
CPSC 335 Computer Science University of Calgary Canada.
Some Results on Codes for Flash Memory Michael Mitzenmacher Includes work with Hilary Finucane, Zhenming Liu, Flavio Chierichetti.
Wei Zhu, Xiang Tian, Fan Zhou and Yaowu Chen IEEE TCE, 2010.
1 Data Persistence in Large-scale Sensor Networks with Decentralized Fountain Codes Yunfeng Lin, Ben Liang, Baochun Li INFOCOM 2007.
Sliding-Window Digital Fountain Codes for Streaming of Multimedia Contents Matta C.O. Bogino, Pasquale Cataldi, Marco Grangetto, Enrico Magli, Gabriella.
1 Eitan Yaakobi, Laura Grupp Steven Swanson, Paul H. Siegel, and Jack K. Wolf Flash Memory Summit, August 2010 University of California San Diego Efficient.
Santa Clara, CA USA August An Information Theory Approach for Flash Memory Eitan Yaakobi, Paul H. Siegel, Jack K. Wolf University of California,
1 Error Correction Coding for Flash Memories Eitan Yaakobi, Jing Ma, Adrian Caulfield, Laura Grupp Steven Swanson, Paul H. Siegel, Jack K. Wolf Flash Memory.
Instruction Set Architecture (ISA) for Low Power Hillary Grimes III Department of Electrical and Computer Engineering Auburn University.
Elementary Data Types Scalar Data Types Numerical Data Types Other
Coding for Flash Memories
1 Chapter 1 Introduction. 2 Outline 1.1 A Very Abstract Summary 1.2 History 1.3 Model of the Signaling System 1.4 Information Source 1.5 Encoding a Source.
Fundamentals of Multimedia Chapter 7 Lossless Compression Algorithms Ze-Nian Li and Mark S. Drew 건국대학교 인터넷미디어공학부 임 창 훈.
Generalized Communication System: Error Control Coding Occurs In Right Column. 6.
An Intelligent Cache System with Hardware Prefetching for High Performance Jung-Hoon Lee; Seh-woong Jeong; Shin-Dug Kim; Weems, C.C. IEEE Transactions.
A stack based tree searching method for the implementation of the List Sphere Decoder ASP-DAC 2006 paper review Presenter : Chun-Hung Lai.
On Error Preserving Encryption Algorithms for Wireless Video Transmission Ali Saman Tosun and Wu-Chi Feng The Ohio State University Department of Computer.
Khaled A. Al-Utaibi Memory Devices Khaled A. Al-Utaibi
1 Route Table Partitioning and Load Balancing for Parallel Searching with TCAMs Department of Computer Science and Information Engineering National Cheng.
On the Coded Complex Field Network Coding Scheme for Multiuser Cooperative Communications with Regenerative Relays Caixi Key Lab of Information.
Repairable Fountain Codes Megasthenis Asteris, Alexandros G. Dimakis IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 32, NO. 5, MAY /5/221.
Optimal Degree Distribution for LT Codes with Small Message Length Esa Hyytiä, Tuomas Tirronen, Jorma Virtamo IEEE INFOCOM mini-symposium
XOR-XNOR gates are investigated in this article, Design Methodologies for High-Performance Noise- Tolerant XOR–XNOR Circuits with Power, Area and Time.
Lecture 23: Finite State Machines with no Outputs Acceptors & Recognizers.
An Optimal Partial Decoding Algorithm for Rateless Codes Valerio Bioglio, Rossano Gaeta, Marco Grangetto, and Matteo Sereno Dipartimento di Informatica.
Chih-Ming Chen, Student Member, IEEE, Ying-ping Chen, Member, IEEE, Tzu-Ching Shen, and John K. Zao, Senior Member, IEEE Evolutionary Computation (CEC),
Efficient Deployment Algorithms for Prolonging Network Lifetime and Ensuring Coverage in Wireless Sensor Networks Yong-hwan Kim Korea.
User Cooperation via Rateless Coding Mahyar Shirvanimoghaddam, Yonghui Li, and Branka Vucetic The University of Sydney, Australia IEEE GLOBECOM 2012 &
Company name KUAS HPDS A Realistic Variable Voltage Scheduling Model for Real-Time Applications ICCAD Proceedings of the 2002 IEEE/ACM international conference.
Background Gaussian Elimination Fault Tolerance Single or multiple core failures: Single or multiple core additions: Simultaneous core failures and additions:
CprE 545 project proposal Long.  Introduction  Random linear code  LT-code  Application  Future work.
A Cyclic-Executive-Based QoS Guarantee over USB Chih-Yuan Huang,Li-Pin Chang, and Tei-Wei Kuo Department of Computer Science and Information Engineering.
Error Correction and Partial Information Rewriting for Flash Memories Yue Li joint work with Anxiao (Andrew) Jiang and Jehoshua Bruck.
Advances in digital image compression techniques Guojun Lu, Computer Communications, Vol. 16, No. 4, Apr, 1993, pp
Multi-Edge Framework for Unequal Error Protecting LT Codes H. V. Beltr˜ao Neto, W. Henkel, V. C. da Rocha Jr. Jacobs University Bremen, Germany IEEE ITW(Information.
UNDER THE GUIDANCE DR. K. R. RAO SUBMITTED BY SHAHEER AHMED ID : Encoding H.264 by Thread Level Parallelism.
Advanced Science and Technology Letters Vol.106 (Information Technology and Computer Science 2015), pp.17-21
OCR Software Architecture for Embedded Device Seho Kim', Jaehwa Park Computer Science, Chung-Ang University, Seoul, Korea
Robot Velocity Based Path Planning Along Bezier Curve Path Gil Jin Yang, Byoung Wook Choi * Dept. of Electrical and Information Engineering Seoul National.
A Fast Repair Code Based on Regular Graphs for Distributed Storage Systems Yan Wang, East China Jiao Tong University Xin Wang, Fudan University 1 12/11/2013.
Unique! coding for three different motivation flash codes network coding Slepian-Wolf coding test, take-home test.
Sequential Soft Decision Decoding of Reed Solomon Codes Hari Palaiyanur Cornell University Prof. John Komo Clemson University 2003 SURE Program.
Yue Li joint work with Anxiao (Andrew) Jiang and Jehoshua Bruck.
Lecture 12 Huffman Algorithm. In computer science and information theory, a Huffman code is a particular type of optimal prefix code that is commonly.
Rate Distortion Theory. Introduction The description of an arbitrary real number requires an infinite number of bits, so a finite representation of a.
Advanced Science and Technology Letters Vol.106 (Information Technology and Computer Science 2015), pp.27-32
Advanced Science and Technology Letters Vol.28 (EEC 2013), pp Fuzzy Technique for Color Quality Transformation.
Coding and Algorithms for Memories Lecture 6 1.
Algorithm Analysis with Big Oh ©Rick Mercer. Two Searching Algorithms  Objectives  Analyze the efficiency of algorithms  Analyze two classic algorithms.
COMBINATIONAL AND SEQUENTIAL CIRCUITS Guided By: Prof. P. B. Swadas Prepared By: BIRLA VISHVAKARMA MAHAVDYALAYA.
Professor Mukhtar ahmad Senior Member IEEE Aligarh Muslim University
Introduction to H.264 / AVC Video Coding Standard Multimedia Systems Sharif University of Technology November 2008.
Seunghui Cha1, Wookhyun Kim1
Il-Kyoung Kwon1, Sang-Yong Lee2
Advanced Science and Technology Letters Vol
Xiaoyang Zhang1, Yuchong Hu1, Patrick P. C. Lee2, Pan Zhou1
Multiway Trees Searching and B-Trees Advanced Tree Structures
Chapter 3 DataStorage Foundations of Computer Science ã Cengage Learning.
Use ECP, not ECC, for hard failures in resistive memories
A Small and Fast IP Forwarding Table Using Hashing
ECE 352 Digital System Fundamentals
Presentation transcript:

Advanced Science and Technology Letters Vol.35(Software 2013), pp Bi-Modal Flash Code using Index-less Indexed Flash Code and Layered Index- less Indexed Flash Code * Herbert R. Esling, Riz Rupert L. Ortiz **, and Proceso L. Fernandez * * * Ateneo de Manila University Abstract. Flash technology uses flash codes to efficiently manage the storage of data. Flash codes that have lower write deficiencies translate to better performance and leads to a longer lifespan of flash devices. One way to lower the write deficiency is to reduce the size of slices. This paper presents a flash code that extends the ILIFC and the LILIFC. By combining them into a bi-modal flash code, smaller slices can be used. The write deficiency is measured through numerical analysis as well as computer simulation. The flash code presented has an asymptotic worst case write deficiency of O ( k 2 q + n/k ) and produces an improved average write deficiency to ILIFC and LILIFC. Keywords: block erasure, block write, flash code, flash memory 1 Introduction Flash technology is now a ubiquitous technology. It is used in memory cards, flash drives and solid-state drives. As demand increases, so does the need for increased capacity and reliability. Flash technology as it stands today, however, has a limit because the cells used to store information have a limited number of erase cycles. Flash technology consists of a many blocks of cells that store charges. A charge in a cell is increased through a process called electron injection. Flash memory, however, is write-asymmetric. This means that while increasing a cell charge is easily done, decreasing it is difficult. In fact, to erase a single cell or lower its level is not allowed. Only an entire block can be erased and rewritten [1]. In order to do so, a process called block erasure is employed. A block erasure removes all the charges in a block. This all-or- nothing approach is further exac-erbated by the fact that block erasures are a strain on the cells, and continued erasures will eventually render the whole device unfit for use. * H.R. Esling is a MS Computer Science student at the Ateneo de Manila University ** R.R.L. Ortiz is a PhD Computer Science student at the Ateneo de Manila University * * * P.L. Fernandez is an Associate Professor at the Ateneo de Manila University ISSN: ASTL Copyright © 2013 SERSC

Advanced Science and Technology Letters Vol.35 (Software 2013) Flash codes are used to efficiently manage the storage of data in a flash device. One way to measure the performance of a flash code is by determining its write deficiency, which refers to the gap between the theoretical maximum and actual bit writes. It is computed using the equation δ(F) = n(q − 1) − t, where n(q − 1) is the theoretical maximum number of write operations allowed for a block of n cells with q levels each, while t is the actual number of write operations that a flash code F is able to perform before calling a block erasure [2]. The lower the write deficiency value, the better is the performance of the flash code. 2 Related Literature Two well-studied flash codes in literature are the Index-less Indexed Flash Code (ILIFC) [2] and the Layered Index-less Indexed Flash Code (LILIFC) [3]. Each of these two flash codes partitions a block of n cells into slices with k cells each, where k is the size of the bit information to be stored in the block. Both flash codes use an elegant scheme that enables both the bit index and the bit value to be easily inferred from the contents of a slice. The main difference is that LILFC uses a layer-based index coding, where a slice is filled up from left to right as opposed to ILIFC that fills up the level in one cell first before proceeding to the next cell. Kaji proposed an improvement to the expected write deficiency of the ILIFC by introducing left-oriented and right-oriented slices [4]. This reduced the slice size to k/2 cells and decreased the likelihood of having unused cell levels when a block erasure occurs. Nagahara and Kaji were able to reduce the size of a slice further to k/p where p is an arbitrary chosen positive integer, with p ≤ k/3 [5]. This was achieved by partitioning a block into p sub-blocks, and assigning k/p bits per sub- block, and an ILIFC-like code is also implemented. There are several other proposed flash codes in literature, including the Bi-nary Index Flash Code (BIFC) [6], BIFC with Resizable Cluster Method (BIFC-RCM) [7], and Multi-mode Flash Code (MMFC) [8]. In this study, we focus on the ILIFC and LILIFC in order to come up with a scheme that takes advantage of the high similarity between these 2 flash codes, and develop a flash code with a lower average write deficiency. 3 Combining the ILIFC and Layered ILIFC In this paper, we propose two flash codes, Bi-Modal Flash Code (BMFC) and Two-Split Bi-Modal Flash Code (BMFC2). Both flash codes combine the IL-IFC and the LILIFC in order to reduce the slice size and achieve better write deficiencies. 3.1 Bi-Modal Flash Code (BMFC) In the Bi-Modal Flash Code, we partition the k data bits into 2 groups and apply a different coding scheme for each group. The first 2 bits, with indices 0 to 2 − 1, 20 Copyright © 2013 SERSC

Advanced Science and Technology Letters Vol.35 (Software 2013) use an ILIFC-like scheme for encoding and decoding. The remaining bits, with indices 2 to k − 1, use an LILIFC-like scheme. An active slice is accordingly referred to as ILIFC-based or LILIFC-based depending on the mode that the slice uses. Because there are just 2 bit indices to distinguish within a mode, the size of a slice is reduced to 2. The BMFC is clarified further with an illustration of a sample write sequence in Fig. 1a. (a) Bi-Modal Flash Code (b) Two-Split Bi-Modal Flash Code Fig. 1: BMFC and BMFC2 block state sequence 3.2 Two-Split Bi-Modal Flash Code (BMFC2) The Two-Split Bi-Modal Flash Code (BMFC2), uses slices of size 4. It is an improvement of BMFC by treating a block as a two-sided storage that contains slices on the left and right ends, which grow towards the opposite ends whenever new slices are activated. The two modes are distributed among each side in order to differentiate the bit position; the two modes with the two sides allow up to four combinations. A sample write sequence for BMFC2 is shown in Fig. 1b. 4 Simulation Results To estimate the average case write deficiencies, computer simulations on each of the flash codes were performed. The simulation used uniform distribution, where all data bits have an equal chance of being updated. The simulation results of BMFC and BMFC2 are shown in Fig. 2a. As shown in the graph, BMFC2 outperformed BMFC. BMFC2 is then compared with ILIFC and LILIFC, and the simulation results are shown in Fig. 2b. For sufficiently small values of k, ILIFC and LILIFC performed better due to the overhead required by BMFC2 to differentiate its two modes. But for a significant majority of k values, the proposed flash code is superior. Copyright © 2013 SERSC 21

Advanced Science and Technology Letters Vol.35 (Software 2013) (a) BFMC and BMFC2 (b) BMFC2, ILIFC and LILIFC Fig. 2: Average Write Deficiency Ratios of BMFC, BMFC2, ILIFC and LILIFC in Uniform Frequency Distribution 5 Conclusion In this paper, the BMFC and its simple variant BMFC2 used two modes of coding, ILIFC and LILIFC, to utilize slices of smaller length. Simulation has shown that the proposed codes, while underperforming at small k -bit sizes, have better average write deficiencies than both ILIFC and LILIFC at greater values of k. Further studies can be made to check the advantages of flash codes with arbitrarily smaller slices. References 1.E. Yaakobi, A. Vardy, P. Siegel, and J. Wolf, 'Multidimensional flash codes,” in Communication, Control, and Computing, th Annual Allerton Conference on, 2008, pp. 392– H. Mahdavifar, P. Siegel, A. Vardy, J. Wolf, and E. Yaakobi, 'A nearly optimal construction of flash codes,” in Information Theory, ISIT IEEE Inter- national Symposium on, 2009, pp. 1239– R. Suzuki and T. Wadayama, 'Layered index-less indexed flash codes for improving average performance,” in Information Theory Proceedings (ISIT), 2011 IEEE International Symposium on, 2011, pp. 2138– Y. Kaji, 'The expected write deficiency of index-less flash codes and their improve-ment,” in Information Theory Workshop (ITW), 2011 IEEE, 2011, pp. 35– H. Nagahara and Y. Kaji, 'Index-less flash codes with arbitrary small slices,” in Information Theory and its Applications (ISITA), 2012 International Symposium on, 2012, pp. 103– M. Tan and Y. Kaji, 'Uniform compartment flash code and binary-indexed flash code,” IEICE Technical Report, pp. 25–30, M. Tan and Y. Kaji, 'Applying resizable-cluster method in binary-indexed flash code,” SITA, M. Tan, P. Fernandez, N. Salazar, J. Ty, and Y. Kaji, 'Multi-mode encoding with binary-index flash code,” Copyright © 2013 SERSC