Architecture-level Designs Using Emerging Non-volatile Memories

Architecture-level Designs Using Emerging Non-volatile Memories
Author: Jue Wang
Publisher:
Total Pages:
Release: 2014
Genre:
ISBN:

SRAM and DRAM have been used to build our memory systems for decades, but their scalability is facing more and more challenges in terms of leakage power and density. Meanwhile, new emerging non-volatile memory technologies (NVMs) are being explored, such as Phase-Change RAM (PCM or PCRAM), Spin-Torque Transfer RAM (STTRAM or MRAM), and Resistive RAM (ReRAM). They have common advantages of high density, low standby power and non-volatility. It could bring benefits by using NVMs to replace SRAM and DRAM in our memory systems. However, NVM technologies still have some disadvantages. First, the NVM write operation is much more expensive in terms of longer latency and higher energy. It causes negative impacts on the system performance and energy efficiency. Second, NVMs usually have limited write endurance, which brings challenges on system reliability. Last but not least, the size of NVM sense amplifier is larger, and how to maintain the area utilization is an issue. All of these NVM characteristics are caused by their basic mechanisms, and they are very difficult to be improved by changing cell designs. Therefore, new architecture techniques are necessary for mitigating these issues and building efficient and reliable systems with NVMs.In this dissertation, NVMs are evaluated as alternatives of traditional memory technologies for different memory levels. We explore NVMs as main memory systems, on-chip caches and GPGPU register files. We analyze their impact on system level and propose several techniques on architecture level to mitigate their disadvantages. We believe these techniques make NVMs more attractive in the future computer systems.

Facilitating Emerging Non-volatile Memories in Next-generation Memory System Design

Facilitating Emerging Non-volatile Memories in Next-generation Memory System Design
Author: Ping Chi
Publisher:
Total Pages: 143
Release: 2016
Genre:
ISBN: 9781369147049

This dissertation focuses on three types of emerging NVMs, spin-transfer torque RAM (STT-RAM), phase change memory (PCM), and metal-oxide resistive RAM (ReRAM). STT-RAM has been identified as the best replacement of SRAM to build large-scale and low-power on-chip caches and also an energy-efficient alternative to DRAM as main memory. PCM and ReRAM have been considered to be promising technologies for building future large-scale and low-power main memory systems. This dissertation investigates two aspects to facilitate them in next-generation memory system design, architecture-level and application-level perspectives. First, multi-level cell (MLC) STT-RAM based cache design is optimized by using data encoding and data compression. Second, MLC STT-RAM is utilized as persistent main memory for fast and energy-efficient local checkpointing. Third, the commonly used database indexing algorithm, B+tree, is redesigned to be NVM-friendly. Forth, a novel processing-in-memory architecture built on ReRAM based main memory is proposed to accelerate neural network applications.

Design Exploration of Emerging Nano-scale Non-volatile Memory

Design Exploration of Emerging Nano-scale Non-volatile Memory
Author: Hao Yu
Publisher: Springer Science & Business
Total Pages: 200
Release: 2014-04-18
Genre: Technology & Engineering
ISBN: 1493905511

This book presents the latest techniques for characterization, modeling and design for nano-scale non-volatile memory (NVM) devices. Coverage focuses on fundamental NVM device fabrication and characterization, internal state identification of memristic dynamics with physics modeling, NVM circuit design and hybrid NVM memory system design-space optimization. The authors discuss design methodologies for nano-scale NVM devices from a circuits/systems perspective, including the general foundations for the fundamental memristic dynamics in NVM devices. Coverage includes physical modeling, as well as the development of a platform to explore novel hybrid CMOS and NVM circuit and system design. • Offers readers a systematic and comprehensive treatment of emerging nano-scale non-volatile memory (NVM) devices; • Focuses on the internal state of NVM memristic dynamics, novel NVM readout and memory cell circuit design and hybrid NVM memory system optimization; • Provides both theoretical analysis and practical examples to illustrate design methodologies; • Illustrates design and analysis for recent developments in spin-toque-transfer, domain-wall racetrack and memristors.

Emerging Memory Technologies

Emerging Memory Technologies
Author: Yuan Xie
Publisher: Springer Science & Business Media
Total Pages: 321
Release: 2013-10-21
Genre: Technology & Engineering
ISBN: 144199551X

This book explores the design implications of emerging, non-volatile memory (NVM) technologies on future computer memory hierarchy architecture designs. Since NVM technologies combine the speed of SRAM, the density of DRAM, and the non-volatility of Flash memory, they are very attractive as the basis for future universal memories. This book provides a holistic perspective on the topic, covering modeling, design, architecture and applications. The practical information included in this book will enable designers to exploit emerging memory technologies to improve significantly the performance/power/reliability of future, mainstream integrated circuits.

Micro-Architecture and Systems Support for Emerging Non-Volatile Memories

Micro-Architecture and Systems Support for Emerging Non-Volatile Memories
Author: Meenakshi Sundaram Bhaskaran
Publisher:
Total Pages: 127
Release: 2016
Genre:
ISBN:

Emerging non-volatile memory technologies such as phase-change memory, resistive random access memory, spin-torque transfer memory and 3D XPoint memory promise to significantly increase the I/O sub-system performance. But, current disk-centric systems fall short in taking advantage of the bandwidth and latency characteristics of such memories. This dissertation presents three systems that address: hardware, system software and micro-architecture support for faster-than-flash non-volatile memories. First, we explore system design for using emerging non-volatile memories (NVM) as a persistent cache that bridges the price and density gap between NVMs and denser storage. Bankshot is a prototype PCIe-based intelligent cache with access latencies an order of magnitude lower than conventional SSDs. Unlike previous designs of SSD caches, Bankshot relies on the OS for heavyweight operations such as servicing misses and write-backs while allows cache hits to bypass the operating system (OS) and its associated software overhead entirely. Second, we extend the ability to define application specific interface to emerging NVM SSDs such that a broad range of applications can benefit from low-latency, high-bandwidth access to the SSD's data. Our prototype system, called Willow, supports concurrent execution of an application and trusted code within the SSD without compromising on file system protections. We present three SSD apps - Caching, Append and zero-out that showcase Willows capabilities. Caching extends Willows semantics to use the SSD storage as a persistent cache while file-append and zero-out extends the semantics for file system operations. Finally, we address the challenge of accessing byte-addressable, emerging NVMs with higher than DRAM latency when attached to the processor memory bus; specifically for loads. We propose Non-Blocking Load (NBLD), an instruction set extension to mitigate pipeline stalls from long-latency memory accesses. NBLD is a non-blocking instruction that brings data into the upper levels of the cache hierarchy, however, unlike prefetch instructions, NBLD triggers the execution of application-specific code once data is resident in the cache, effectively hiding the latency of the memory.

Embedded Computer Systems: Architectures, Modeling, and Simulation

Embedded Computer Systems: Architectures, Modeling, and Simulation
Author: Dionisios N. Pnevmatikatos
Publisher: Springer
Total Pages: 486
Release: 2019-08-09
Genre: Computers
ISBN: 3030275620

This book constitutes the refereed proceedings of the 19th International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation, SAMOS 2019, held in Pythagorion, Samos, Greece, in July 2019. The 21 regular papers presented were carefully reviewed and selected from 55 submissions. The papers are organized in topical sections on system design space exploration; deep learning optimization; system security; multi/many-core scheduling; system energy and heat management; many-core communication; and electronic system-level design and verification. In addition there are 13 papers from three special sessions which were organized on topics of current interest: insights from negative results; machine learning implementations; and European projects.

Durable Phase-Change Memory Architectures

Durable Phase-Change Memory Architectures
Author:
Publisher: Academic Press
Total Pages: 148
Release: 2020-02-21
Genre: Computers
ISBN: 0128187557

Advances in Computers, Volume 118, the latest volume in this innovative series published since 1960, presents detailed coverage of new advancements in computer hardware, software, theory, design and applications. Chapters in this updated release include Introduction to non-volatile memory technologies, The emerging phase-change memory, Phase-change memory architectures, Inter-line level schemes for handling hard errors in PCMs, Handling hard errors in PCMs by using intra-line level schemes, and Addressing issues with MLC Phase-change Memory. Gives a comprehensive overlook of new memory technologies, including PCM Provides reliability features with an in-depth discussion of physical mechanisms that are currently limiting PCM capabilities Covers the work of well-known authors and researchers in the field Includes volumes that are devoted to single themes or subfields of computer science

Applied Reconfigurable Computing. Architectures, Tools, and Applications

Applied Reconfigurable Computing. Architectures, Tools, and Applications
Author: Nikolaos Voros
Publisher: Springer
Total Pages: 761
Release: 2018-04-25
Genre: Computers
ISBN: 3319788906

This book constitutes the proceedings of the 14th International Conference on Applied Reconfigurable Computing, ARC 2018, held in Santorini, Greece, in May 2018. The 29 full papers and 22 short presented in this volume were carefully reviewed and selected from 78 submissions. In addition, the volume contains 9 contributions from research projects. The papers were organized in topical sections named: machine learning and neural networks; FPGA-based design and CGRA optimizations; applications and surveys; fault-tolerance, security and communication architectures; reconfigurable and adaptive architectures; design methods and fast prototyping; FPGA-based design and applications; and special session: research projects.

Smart Sensors and Systems

Smart Sensors and Systems
Author: Chong-Min Kyung
Publisher: Springer
Total Pages: 517
Release: 2016-10-16
Genre: Technology & Engineering
ISBN: 3319332015

This book describes the technology used for effective sensing of our physical world and intelligent processing techniques for sensed information, which are essential to the success of Internet of Things (IoT). The authors provide a multidisciplinary view of sensor technology from materials, process, circuits, and big data domains and showcase smart sensor systems in real applications including smart home, transportation, medical, environmental, agricultural, etc. Unlike earlier books on sensors, this book provides a “global” view on smart sensors covering abstraction levels from device, circuit, systems, and algorithms.

Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing

Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing
Author: Sudeep Pasricha
Publisher: Springer Nature
Total Pages: 481
Release: 2023-10-09
Genre: Technology & Engineering
ISBN: 3031399323

This book presents recent advances towards the goal of enabling efficient implementation of machine learning models on resource-constrained systems, covering different application domains. The focus is on presenting interesting and new use cases of applying machine learning to innovative application domains, exploring the efficient hardware design of efficient machine learning accelerators, memory optimization techniques, illustrating model compression and neural architecture search techniques for energy-efficient and fast execution on resource-constrained hardware platforms, and understanding hardware-software codesign techniques for achieving even greater energy, reliability, and performance benefits. Discusses efficient implementation of machine learning in embedded, CPS, IoT, and edge computing; Offers comprehensive coverage of hardware design, software design, and hardware/software co-design and co-optimization; Describes real applications to demonstrate how embedded, CPS, IoT, and edge applications benefit from machine learning.