Low Energy Solutions for Multi- and Triple-Level Cell Non-Volatile Memories

Due to the high refresh power and scalability issues of DRAM, non-volatile memories (NVM) such as phase change memory (PCM) and resistive RAM (RRAM) are being actively investigated as viable replacements of DRAM. However, although these NVMs are more scalable than DRAM, they have shortcomings such as higher write energy and lower endurance. Further, the increased capacity of multi- and triple-level cells (MLC/TLC) in these NVM technologies comes at the cost of even higher write energies and lower endurance attributed to the MLC/TLC program-and-verify (P&V) techniques. This dissertation makes the following contributions to address the high write energy associated with MLC/TLC NVMs. First, we describe MFNW, a Flip-N-Write encoding that effectively reduces the write energy and improves the endurance of MLC NVMs. MFNW encodes an MLC/TLC word into a number of codewords and selects the one resulting in lowest write energy. Second, we present another encoding solution that is based on perfect knowledge frequent value encoding (FVE). This encoding technique leverages machine learning to cluster a set of general-purpose applications according to their frequency profiles and generates a dedicated offline FVE for every cluster to maximize energy reduction across a broad spectrum of applications. Whereas the proposed encodings are used as an add-on layer on top of the MLC/TLC P&V solutions, the third contribution is a low latency, low energy P&V (L3EP) approach for MLC/TLC PCM. The primary motivation of L^3EP is to fix the problem from its origin by crafting a higher speed programming algorithm. A reduction in write latency implies a reduction in write energy as well as an improvement in cell endurance. Directions for future research include the integration and evaluation of a software-based hybrid encoding mechanism for MLC/TLC NVMs; this is a page-level encoding that employs a DRAM cache for coding/decoding purposes. The main challenges include how the cache block replacement algorithm can easily access the page-level auxiliary cells to encode the cache block correctly. In summary, this work presents multiple solutions to address major challenges of MLC/TLC NVMs, including write latency, write energy, and cell endurance

Low Power Memory/Memristor Devices and Systems

This reprint focusses on achieving low-power computation using memristive devices. The topic was designed as a convenient reference point: it contains a mix of techniques starting from the fundamental manufacturing of memristive devices all the way to applications such as physically unclonable functions, and also covers perspectives on, e.g., in-memory computing, which is inextricably linked with emerging memory devices such as memristors. Finally, the reprint contains a few articles representing how other communities (from typical CMOS design to photonics) are fighting on their own fronts in the quest towards low-power computation, as a comparison with the memristor literature. We hope that readers will enjoy discovering the articles within

A Survey of Face Recognition

Recent years witnessed the breakthrough of face recognition with deep convolutional neural networks. Dozens of papers in the field of FR are published every year. Some of them were applied in the industrial community and played an important role in human life such as device unlock, mobile payment, and so on. This paper provides an introduction to face recognition, including its history, pipeline, algorithms based on conventional manually designed features or deep learning, mainstream training, evaluation datasets, and related applications. We have analyzed and compared state-of-the-art works as many as possible, and also carefully designed a set of experiments to find the effect of backbone size and data distribution. This survey is a material of the tutorial named The Practical Face Recognition Technology in the Industrial World in the FG2023

Design and Management of Manufacturing Systems

Although the design and management of manufacturing systems have been explored in the literature for many years now, they still remain topical problems in the current scientific research. The changing market trends, globalization, the constant pressure to reduce production costs, and technical and technological progress make it necessary to search for new manufacturing methods and ways of organizing them, and to modify manufacturing system design paradigms. This book presents current research in different areas connected with the design and management of manufacturing systems and covers such subject areas as: methods supporting the design of manufacturing systems, methods of improving maintenance processes in companies, the design and improvement of manufacturing processes, the control of production processes in modern manufacturing systems production methods and techniques used in modern manufacturing systems and environmental aspects of production and their impact on the design and management of manufacturing systems. The wide range of research findings reported in this book confirms that the design of manufacturing systems is a complex problem and that the achievement of goals set for modern manufacturing systems requires interdisciplinary knowledge and the simultaneous design of the product, process and system, as well as the knowledge of modern manufacturing and organizational methods and techniques