Journal Article10.2200/S01109ED1V01Y202106CAC057
In-/Near-Memory Computing
11
TL;DR: This book provides a structured introduction of the key concepts and techniques that enable in-/near-memory computing.
read more
Abstract: This book provides a structured introduction of the key concepts and techniques that enable in-/near-memory computing.
For decades, processing-in-memory or near-memory computing has been attracting growing interest due to its potential to break the memory wall. Near-memory computing moves compute logic near the memory, and thereby reduces data movement. Recent work has also shown that certain memories can morph themselves into compute units by exploiting the physical properties of the memory cells, enabling in-situ computing in the memory array. While in- and near-memory computing can circumvent overheads related to data movement, it comes at the cost of restricted flexibility of data representation and computation, design challenges of compute capable memories, and difficulty in system and software integration. Therefore, wide deployment of in-/near-memory computing cannot be accomplished without techniques that enable efficient mapping of data-intensive applications to such devices, without sacrificing accuracy or increasing hardware costs excessively. This book describes various memory substrates amenable to in- and near-memory computing, architectural approaches for designing efficient and reliable computing devices, and opportunities for in-/near-memory acceleration of different classes of applications.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
Infinity Stream: Portable and Programmer-Friendly In-/Near-Memory Fusion
Zhengrong Wang,Christopher Liu,Aman Arora,Lizy K. John,Tony Nowatzki +4 more
- 25 Mar 2023
TL;DR: The tensor dataflow graph (tDFG) as mentioned in this paper is a unified representation of in-memory and near-memory computation, which exposes tensor-data structure information so that the hardware and runtime can automatically orchestrate data management for bitserial execution, including runtime data layout transformations.
13
A Review on the emerging technology of TinyML
Vasileios Tsoukas,Anargyros Gkogkidis,Eleni Boumpa,Athanasios Kakarountas +3 more
TL;DR: TinyML is an emerging technology for developing autonomous and secure devices with local AI capabilities. It aims to democratize AI and contribute to the digital revolution of intelligent devices. The work reviews optimization techniques, development boards, software, applications, and future directions.
10
Memristor-Based Read/Write Circuit with Stable Continuous Read Operation
TL;DR: This paper studies some circuits studied by predecessors on read/write circuit, compares the experimental results, analyzes the reason for the resistance state deviation of memristor, and puts forward a new parallel structure of Memristor based on opposite polarity.
Cognitive sensor systems for NDE 4.0: Technology, AI embedding, validation and qualification
B. Valeske,Ralf Tschuncky,Frank Leinenbach,Ahmad Osman,Ziang Wei,F. Römer,Dirk Koster,Kevin Becker,Thomas Schwender +8 more
TL;DR: Applied Artificial Intelligence (AI) is a key element for the development of cognitive NDE 4.0 sensor systems and trusted AI also plays an important role in CSS, as it is able to provide reliable and trustworthy data evaluation decisions for the end user.
4
Energy-efficient neural network design using memristive MAC unit
TL;DR: This paper proposes and presents a mixed-signal multiply-accumulate unit design with in-memory computing to improve both latency and energy and investigates the usefulness of this MAC design in machine learning applications.
2
References
In situ click chemistry generation of cyclooxygenase-2 inhibitors
TL;DR: In situ click chemistry is used to develop COX-2 specific inhibitors with high in vivo anti-inflammatory activity, significantly higher than that of widely used selective cyclooxygenase-2 inhibitors.
Canu: scalable and accurate long-read assembly via adaptive k-mer weighting and repeat separation.
Sergey Koren,Brian P. Walenz,Konstantin Berlin,Jason R. Miller,Nicholas H. Bergman,Adam M. Phillippy +5 more
TL;DR: Canu, a successor of Celera Assembler that is specifically designed for noisy single-molecule sequences, is presented, demonstrating that Canu can reliably assemble complete microbial genomes and near-complete eukaryotic chromosomes using either Pacific Biosciences or Oxford Nanopore technologies.
•Book
CMOS VLSI Design : A Circuits and Systems Perspective
Neil Weste,David Money Harris +1 more
- 21 May 2004
TL;DR: The authors draw upon extensive industry and classroom experience to introduce todays most advanced and effective chip design practices, and present extensively updated coverage of every key element of VLSI design, and illuminate the latest design challenges with 65 nm process examples.
2.9K
Training and operation of an integrated neuromorphic network based on metal-oxide memristors
Mirko Prezioso,Farnood Merrikh-Bayat,Brian D. Hoskins,Gina C. Adam,Konstantin K. Likharev,Dmitri B. Strukov +5 more
TL;DR: The experimental implementation of transistor-free metal-oxide memristor crossbars, with device variability sufficiently low to allow operation of integrated neural networks, in a simple network: a single-layer perceptron (an algorithm for linear classification).
Hitting the memory wall: implications of the obvious
William A. Wulf,Sally A. McKee +1 more
TL;DR: This work proposes an exact analysis, removing all remaining uncertainty, based on model checking, using abstract-interpretation results to prune down the model for scalability, and notably improves precision upon classical abstract interpretation at reasonable cost.