Vlsi Design Of Non Volatile Memories

Download or read book VLSI-Design of Non-Volatile Memories written by Giovanni Campardo and published by Springer Science & Business Media. This book was released on 2005-01-18 with total page 616 pages. Available in PDF, EPUB and Kindle. Book excerpt: VLSI-Design for Non-Volatile Memories is intended for electrical engineers and graduate students who want to enter into the integrated circuit design world. Non-volatile memories are treated as an example to explain general design concepts. Practical illustrative examples of non-volatile memories, including flash types, are showcased to give insightful examples of the discussed design approaches. A collection of photos is included to make the reader familiar with silicon aspects. Throughout all parts of this book, the authors have taken a practical and applications-driven point of view, providing a comprehensive and easily understood approach to all the concepts discussed. Giovanni Campardo and Rino Micheloni have a solid track record of leading design activities at the STMicroelectronics Flash Division. David Novosel is President and founder of Intelligent Micro Design, Inc., Pittsburg, PA.

Download or read book Error Correction Codes for Non-Volatile Memories written by Rino Micheloni and published by Springer Science & Business Media. This book was released on 2008-06-03 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nowadays it is hard to find an electronic device which does not use codes: for example, we listen to music via heavily encoded audio CD's and we watch movies via encoded DVD's. There is at least one area where the use of encoding/decoding is not so developed, yet: Flash non-volatile memories. Flash memory high-density, low power, cost effectiveness, and scalable design make it an ideal choice to fuel the explosion of multimedia products, like USB keys, MP3 players, digital cameras and solid-state disk. In ECC for Non-Volatile Memories the authors expose the basics of coding theory needed to understand the application to memories, as well as the relevant design topics, with reference to both NOR and NAND Flash architectures. A collection of software routines is also included for better understanding. The authors form a research group (now at Qimonda) which is the typical example of a fruitful collaboration between mathematicians and engineers.

Download or read book Logic Non-volatile Memory: The Nvm Solutions For Ememory written by Charles Ching-hsiang Hsu and published by World Scientific. This book was released on 2014-03-18 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: Would you like to add the capabilities of the Non-Volatile Memory (NVM) as a storage element in your silicon integrated logic circuits, and as a trimming sector in your high voltage driver and other silicon integrated analog circuits? Would you like to learn how to embed the NVM into your silicon integrated circuit products to improve their performance?This book is written to help you.It provides comprehensive instructions on fabricating the NVM using the same processes you are using to fabricate your logic integrated circuits. We at our eMemory company call this technology the embedded Logic NVM. Because embedded Logic NVM has simple fabrication processes, it has replaced the conventional NVM in many traditional and new applications, including LCD driver, LED driver, MEMS controller, touch panel controller, power management unit, ambient and motion sensor controller, micro controller unit (MCU), security ID setting tag, RFID, NFC, PC camera controller, keyboard controller, and mouse controller. The recent explosive growth of the Logic NVM indicates that it will soon dominate all NVM applications. The embedded Logic NVM was invented and has been implemented in users' applications by the 200+ employees of our eMemory company, who are also the authors and author-assistants of this book.This book covers the following Logic NVM products: One Time Programmable (OTP) memory, Multiple Times Programmable (MTP) memory, Flash memory, and Electrically Erasable Programmable Read Only Memory (EEPROM). The fundamentals of the NVM are described in this book, which include: the physics and operations of the memory transistors, the basic building block of the memory cells and the access circuits.All of these products have been used continuously by the industry worldwide. In-depth readers can attain expert proficiency in the implementation of the embedded Logic NVM technology in their products.

Download or read book Silicon Non-Volatile Memories written by Barbara de Salvo and published by John Wiley & Sons. This book was released on 2013-05-10 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: Semiconductor flash memory is an indispensable component of modern electronic systems which has gained a strategic position in recent decades due to the progressive shift from computing to consumer (and particularly mobile) products as revenue drivers for Integrated Circuits (IC) companies. This book provides a comprehensive overview of the different technological approaches currently being studied to fulfill future memory requirements. Two main research paths are identified and discussed. Different "evolutionary paths" based on the use of new materials (such as silicon nanocrystals for storage nodes and high-k insulators for active dielectrics) and of new transistor structures (such as multi-gate devices) are investigated in order to extend classical floating gate technology to the 32 nm node. "Disruptive paths" based on new storage mechanisms or new technologies (such as phase-change devices, polymer or molecular cross-bar memories) are also covered in order to address 22 nm and smaller IC generations. Finally, the main factors at the origin of these phenomena are identified and analyzed, providing pointers on future research activities and developments in this area.

Download or read book Machine Learning and Non-volatile Memories written by Rino Micheloni and published by Springer Nature. This book was released on 2022-05-25 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the basics of both NAND flash storage and machine learning, detailing the storage problems the latter can help to solve. At a first sight, machine learning and non-volatile memories seem very far away from each other. Machine learning implies mathematics, algorithms and a lot of computation; non-volatile memories are solid-state devices used to store information, having the amazing capability of retaining the information even without power supply. This book will help the reader understand how these two worlds can work together, bringing a lot of value to each other. In particular, the book covers two main fields of application: analog neural networks (NNs) and solid-state drives (SSDs). After reviewing the basics of machine learning in Chapter 1, Chapter 2 shows how neural networks can mimic the human brain; to accomplish this result, neural networks have to perform a specific computation called vector-by-matrix (VbM) multiplication, which is particularly power hungry. In the digital domain, VbM is implemented by means of logic gates which dictate both the area occupation and the power consumption; the combination of the two poses serious challenges to the hardware scalability, thus limiting the size of the neural network itself, especially in terms of the number of processable inputs and outputs. Non-volatile memories (phase change memories in Chapter 3, resistive memories in Chapter 4, and 3D flash memories in Chapter 5 and Chapter 6) enable the analog implementation of the VbM (also called “neuromorphic architecture”), which can easily beat the equivalent digital implementation in terms of both speed and energy consumption. SSDs and flash memories are strictly coupled together; as 3D flash scales, there is a significant amount of work that has to be done in order to optimize the overall performances of SSDs. Machine learning has emerged as a viable solution in many stages of this process. After introducing the main flash reliability issues, Chapter 7 shows both supervised and un-supervised machine learning techniques that can be applied to NAND. In addition, Chapter 7 deals with algorithms and techniques for a pro-active reliability management of SSDs. Last but not least, the last section of Chapter 7 discusses the next challenge for machine learning in the context of the so-called computational storage. No doubt that machine learning and non-volatile memories can help each other, but we are just at the beginning of the journey; this book helps researchers understand the basics of each field by providing real application examples, hopefully, providing a good starting point for the next level of development.

Download or read book Vlsi-Design Of Non-Volatile Memories written by Campardo and published by . This book was released on 2007-10-01 with total page 581 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Emerging Non-Volatile Memories written by Seungbum Hong and published by Springer. This book was released on 2014-11-18 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an introduction to the fundamentals of emerging non-volatile memories and provides an overview of future trends in the field. Readers will find coverage of seven important memory technologies, including Ferroelectric Random Access Memory (FeRAM), Ferromagnetic RAM (FMRAM), Multiferroic RAM (MFRAM), Phase-Change Memories (PCM), Oxide-based Resistive RAM (RRAM), Probe Storage, and Polymer Memories. Chapters are structured to reflect diffusions and clashes between different topics. Emerging Non-Volatile Memories is an ideal book for graduate students, faculty, and professionals working in the area of non-volatile memory. This book also: Covers key memory technologies, including Ferroelectric Random Access Memory (FeRAM), Ferromagnetic RAM (FMRAM), and Multiferroic RAM (MFRAM), among others. Provides an overview of non-volatile memory fundamentals. Broadens readers’ understanding of future trends in non-volatile memories.