Processing-in-Memory for AI

Processing-in-Memory for AI PDF Author: Joo-Young Kim
Publisher: Springer Nature
ISBN: 3030987817
Category : Technology & Engineering
Languages : en
Pages : 168

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Book Description
This book provides a comprehensive introduction to processing-in-memory (PIM) technology, from its architectures to circuits implementations on multiple memory types and describes how it can be a viable computer architecture in the era of AI and big data. The authors summarize the challenges of AI hardware systems, processing-in-memory (PIM) constraints and approaches to derive system-level requirements for a practical and feasible PIM solution. The presentation focuses on feasible PIM solutions that can be implemented and used in real systems, including architectures, circuits, and implementation cases for each major memory type (SRAM, DRAM, and ReRAM).

Processing-in-Memory for AI

Processing-in-Memory for AI PDF Author: Joo-Young Kim
Publisher: Springer Nature
ISBN: 3030987817
Category : Technology & Engineering
Languages : en
Pages : 168

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Book Description
This book provides a comprehensive introduction to processing-in-memory (PIM) technology, from its architectures to circuits implementations on multiple memory types and describes how it can be a viable computer architecture in the era of AI and big data. The authors summarize the challenges of AI hardware systems, processing-in-memory (PIM) constraints and approaches to derive system-level requirements for a practical and feasible PIM solution. The presentation focuses on feasible PIM solutions that can be implemented and used in real systems, including architectures, circuits, and implementation cases for each major memory type (SRAM, DRAM, and ReRAM).

From Artificial Intelligence to Brain Intelligence

From Artificial Intelligence to Brain Intelligence PDF Author: Rajiv Joshi
Publisher: CRC Press
ISBN: 1000795829
Category : Science
Languages : en
Pages : 209

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Book Description
Research in Artificial Intelligence (AI) is not new, it has been around since 1950’s. AI resurfaced at that time while Moore’s law was on an aggressive path of scaling, with the transformation of NMOS and later bipolar technology to CMOS for high performance, low power as well as low cost applications.Several breakthroughs in the electronics industry helped to push Moore’s law in chip miniaturization along with increased computing power (parallel and distributed processing) and memory bandwidth. Once this paradigm shift occurred it naturally opened doors for AI as it required big data manipulations, and thus AI could thrive again. AI has already shown success in industries such as finance, marketing, health care, transportation, gaming, education and the defence and space, to name but a few.The human brain amazingly has a memory in the order of millions of digital bits, however it cannot compete with machines for data crunching and speed. Thus tomorrow’s world will be a World of Wonders of Artificial Intelligence (WOW- AI), to compensate the computational limitations of human beings. In short, AI research and applications will continue to grow with the development of software, algorithms and hardware accelerators.To continue the development of AI, an advanced AI Compute Symposium was launched with the sponsorship of IBM, IEEE CAS and EDS, from which this book came. Overall, the book covers two broad topics: general AI advances, and applications to neuromorphic computing.

Efficient Processing of Deep Neural Networks

Efficient Processing of Deep Neural Networks PDF Author: Vivienne Sze
Publisher: Springer Nature
ISBN: 3031017668
Category : Technology & Engineering
Languages : en
Pages : 254

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Book Description
This book provides a structured treatment of the key principles and techniques for enabling efficient processing of deep neural networks (DNNs). DNNs are currently widely used for many artificial intelligence (AI) applications, including computer vision, speech recognition, and robotics. While DNNs deliver state-of-the-art accuracy on many AI tasks, it comes at the cost of high computational complexity. Therefore, techniques that enable efficient processing of deep neural networks to improve key metrics—such as energy-efficiency, throughput, and latency—without sacrificing accuracy or increasing hardware costs are critical to enabling the wide deployment of DNNs in AI systems. The book includes background on DNN processing; a description and taxonomy of hardware architectural approaches for designing DNN accelerators; key metrics for evaluating and comparing different designs; features of DNN processing that are amenable to hardware/algorithm co-design to improve energy efficiency and throughput; and opportunities for applying new technologies. Readers will find a structured introduction to the field as well as formalization and organization of key concepts from contemporary work that provide insights that may spark new ideas.

Deep In-memory Architectures for Machine Learning

Deep In-memory Architectures for Machine Learning PDF Author: Mingu Kang
Publisher: Springer Nature
ISBN: 3030359719
Category : Technology & Engineering
Languages : en
Pages : 181

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Book Description
This book describes the recent innovation of deep in-memory architectures for realizing AI systems that operate at the edge of energy-latency-accuracy trade-offs. From first principles to lab prototypes, this book provides a comprehensive view of this emerging topic for both the practicing engineer in industry and the researcher in academia. The book is a journey into the exciting world of AI systems in hardware.

In-/Near-Memory Computing

In-/Near-Memory Computing PDF Author: Daichi Fujiki
Publisher: Morgan & Claypool Publishers
ISBN: 1636391877
Category : Computers
Languages : en
Pages : 142

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Book Description
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.

Memory Storage Patterns in Parallel Processing

Memory Storage Patterns in Parallel Processing PDF Author: Mary E. Mace
Publisher: Springer
ISBN:
Category : Computers
Languages : en
Pages : 168

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Book Description
This project had its beginnings in the Fall of 1980. At that time Robert Wagner suggested that I investigate compiler optimi zation of data organization, suitable for use in a parallel or vector machine environment. We developed a scheme in which the compiler, having knowledge of the machine's access patterns, does a global analysis of a program's operations, and automatically determines optimum organization for the data. For example, for certain architectures and certain operations, large improvements in performance can be attained by storing a matrix in row major order. However a subsequent operation may require the matrix in column major order. A determination must be made whether or not it is the best solution globally to store the matrix in row order, column order, or even have two copies of it, each organized differently. We have developed two algorithms for making this determination. The technique shows promise in a vector machine environ ment, particularly if memory interleaving is used. Supercomputers such as the Cray, the CDC Cyber 205, the IBM 3090, as well as superminis such as the Convex are possible environments for implementation.

Artificial Intelligence Hardware Design

Artificial Intelligence Hardware Design PDF Author: Albert Chun-Chen Liu
Publisher: John Wiley & Sons
ISBN: 1119810450
Category : Computers
Languages : en
Pages : 244

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Book Description
ARTIFICIAL INTELLIGENCE HARDWARE DESIGN Learn foundational and advanced topics in Neural Processing Unit design with real-world examples from leading voices in the field In Artificial Intelligence Hardware Design: Challenges and Solutions, distinguished researchers and authors Drs. Albert Chun Chen Liu and Oscar Ming Kin Law deliver a rigorous and practical treatment of the design applications of specific circuits and systems for accelerating neural network processing. Beginning with a discussion and explanation of neural networks and their developmental history, the book goes on to describe parallel architectures, streaming graphs for massive parallel computation, and convolution optimization. The authors offer readers an illustration of in-memory computation through Georgia Tech’s Neurocube and Stanford’s Tetris accelerator using the Hybrid Memory Cube, as well as near-memory architecture through the embedded eDRAM of the Institute of Computing Technology, the Chinese Academy of Science, and other institutions. Readers will also find a discussion of 3D neural processing techniques to support multiple layer neural networks, as well as information like: A thorough introduction to neural networks and neural network development history, as well as Convolutional Neural Network (CNN) models Explorations of various parallel architectures, including the Intel CPU, Nvidia GPU, Google TPU, and Microsoft NPU, emphasizing hardware and software integration for performance improvement Discussions of streaming graph for massive parallel computation with the Blaize GSP and Graphcore IPU An examination of how to optimize convolution with UCLA Deep Convolutional Neural Network accelerator filter decomposition Perfect for hardware and software engineers and firmware developers, Artificial Intelligence Hardware Design is an indispensable resource for anyone working with Neural Processing Units in either a hardware or software capacity.

Algorithm Design and Applications

Algorithm Design and Applications PDF Author: Michael T. Goodrich
Publisher: Wiley Global Education
ISBN: 1119028485
Category : Computers
Languages : en
Pages : 803

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Book Description
ALGORITHM DESIGN and APPLICATIONS “This is a wonderful book, covering both classical and contemporary topics in algorithms. I look forward to trying it out in my algorithms class. I especially like the diversity in topics and difficulty of the problems.” ROBERT TARJAN, PRINCETON UNIVERSITY “The clarity of explanation is excellent. I like the inclusion of the three types of exercises very much.” MING-YANG KAO, NORTHWESTERN UNIVERSITY “Goodrich and Tamassia have designed a book that is both remarkably comprehensive in its coverage and innovative in its approach. Their emphasis on motivation and applications, throughout the text as well as in the many exercises, provides a book well-designed for the boom in students from all areas of study who want to learn about computing. The book contains more than one could hope to cover in a semester course, giving instructors a great deal of flexibility and students a reference that they will turn to well after their class is over.” MICHAEL MITZENMACHER, HARVARD UNIVERSITY “I highly recommend this accessible roadmap to the world of algorithm design. The authors provide motivating examples of problems faced in the real world and guide the reader to develop workable solutions, with a number of challenging exercises to promote deeper understanding.” JEFFREY S. VITTER, UNIVERSITY OF KANSAS DidYouKnow? This book is available as a Wiley E-Text. The Wiley E-Text is a complete digital version of the text that makes time spent studying more efficient. Course materials can be accessed on a desktop, laptop, or mobile device—so that learning can take place anytime, anywhere. A more affordable alternative to traditional print, the Wiley E-Text creates a flexible user experience: Access on-the-go Search across content Highlight and take notes Save money! The Wiley E-Text can be purchased in the following ways: Via your campus bookstore: Wiley E-Text: Powered by VitalSource® ISBN 9781119028796 *Instructors: This ISBN is needed when placing an order. Directly from: www.wiley.com/college/goodrich

Artificial Intelligence in Healthcare

Artificial Intelligence in Healthcare PDF Author: Adam Bohr
Publisher: Academic Press
ISBN: 0128184396
Category : Computers
Languages : en
Pages : 385

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Book Description
Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. Highlights different data techniques in healthcare data analysis, including machine learning and data mining Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks Includes applications and case studies across all areas of AI in healthcare data

Woods and the Sea

Woods and the Sea PDF Author: Michael Dumiak
Publisher: Black Dog Press
ISBN: 9781910433591
Category : Art
Languages : en
Pages : 192

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Book Description
Woods and The Sea: Estonian Design and the Virtual Frontier' explores how Estonian designers have found ways to stoke creative spirit and forge distinctive goods, by their sense of place and historical interests. As a small nation on the Baltic coast, Estonia has acted as a port between Eastern Europe and Russia. In a small and often turbulent environment, its designers engage every aspect of Estonian culture, from stern Soviet orthodoxy to whirlwind globalisation, to a wired and forward-thinking social nature, to the constants of seaside life, and to mushroom hunting in the deep woods. 'Woods and The Sea' presents the stories and personalities of Estonian design and its distinctive style by taking the reader to its sources. 'Woods and the Sea' is structured in three parts; a long-form narrative portrait of Estonian designers, and the development of a distinct style, followed by essays exploring the history of Estonian design, and finally the current situation and future prospects of Estonian design.