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Accelerators For Convolutional Neural Networks
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Book Synopsis Accelerators for Convolutional Neural Networks by : Arslan Munir
Download or read book Accelerators for Convolutional Neural Networks written by Arslan Munir and published by John Wiley & Sons. This book was released on 2023-10-31 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: Accelerators for Convolutional Neural Networks Comprehensive and thorough resource exploring different types of convolutional neural networks and complementary accelerators Accelerators for Convolutional Neural Networks provides basic deep learning knowledge and instructive content to build up convolutional neural network (CNN) accelerators for the Internet of things (IoT) and edge computing practitioners, elucidating compressive coding for CNNs, presenting a two-step lossless input feature maps compression method, discussing arithmetic coding -based lossless weights compression method and the design of an associated decoding method, describing contemporary sparse CNNs that consider sparsity in both weights and activation maps, and discussing hardware/software co-design and co-scheduling techniques that can lead to better optimization and utilization of the available hardware resources for CNN acceleration. The first part of the book provides an overview of CNNs along with the composition and parameters of different contemporary CNN models. Later chapters focus on compressive coding for CNNs and the design of dense CNN accelerators. The book also provides directions for future research and development for CNN accelerators. Other sample topics covered in Accelerators for Convolutional Neural Networks include: How to apply arithmetic coding and decoding with range scaling for lossless weight compression for 5-bit CNN weights to deploy CNNs in extremely resource-constrained systems State-of-the-art research surrounding dense CNN accelerators, which are mostly based on systolic arrays or parallel multiply-accumulate (MAC) arrays iMAC dense CNN accelerator, which combines image-to-column (im2col) and general matrix multiplication (GEMM) hardware acceleration Multi-threaded, low-cost, log-based processing element (PE) core, instances of which are stacked in a spatial grid to engender NeuroMAX dense accelerator Sparse-PE, a multi-threaded and flexible CNN PE core that exploits sparsity in both weights and activation maps, instances of which can be stacked in a spatial grid for engendering sparse CNN accelerators For researchers in AI, computer vision, computer architecture, and embedded systems, along with graduate and senior undergraduate students in related programs of study, Accelerators for Convolutional Neural Networks is an essential resource to understanding the many facets of the subject and relevant applications.
Book Synopsis Efficient Processing of Deep Neural Networks by : Vivienne Sze
Download or read book Efficient Processing of Deep Neural Networks written by Vivienne Sze and published by Springer Nature. This book was released on 2022-05-31 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Proceedings of the 40th Chinese Control Conference by : Cheng Peng
Download or read book Proceedings of the 40th Chinese Control Conference written by Cheng Peng and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Green Electronics by : Cristian Ravariu
Download or read book Green Electronics written by Cristian Ravariu and published by BoD – Books on Demand. This book was released on 2018-06-20 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Green Electronics book is intended to stimulate people's thinking toward the new concepts of an environment-friendly electronics - the main challenge in the future. The book offers multiple solutions to push the classical electronic industry toward green concepts, aided by nanotechnologies, with revolutionary features that provide low power consumption in electronics, use biomaterials for integrated structures, and include environmental monitoring tools. Based on organic semiconductors/insulators without toxic precursors, green electronic technologies launched promising devices like OLED, OTFT, or nano-core-shell transistors. The Green Electronics book successfully presents the recent directions collected worldwide and leaves free space for continuing year by year with new subtopics.
Book Synopsis Data Orchestration in Deep Learning Accelerators by : Tushar Krishna
Download or read book Data Orchestration in Deep Learning Accelerators written by Tushar Krishna and published by Springer Nature. This book was released on 2022-05-31 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Synthesis Lecture focuses on techniques for efficient data orchestration within DNN accelerators. The End of Moore's Law, coupled with the increasing growth in deep learning and other AI applications has led to the emergence of custom Deep Neural Network (DNN) accelerators for energy-efficient inference on edge devices. Modern DNNs have millions of hyper parameters and involve billions of computations; this necessitates extensive data movement from memory to on-chip processing engines. It is well known that the cost of data movement today surpasses the cost of the actual computation; therefore, DNN accelerators require careful orchestration of data across on-chip compute, network, and memory elements to minimize the number of accesses to external DRAM. The book covers DNN dataflows, data reuse, buffer hierarchies, networks-on-chip, and automated design-space exploration. It concludes with data orchestration challenges with compressed and sparse DNNs and future trends. The target audience is students, engineers, and researchers interested in designing high-performance and low-energy accelerators for DNN inference.
Book Synopsis Accelerators for Convolutional Neural Networks by : Arslan Munir
Download or read book Accelerators for Convolutional Neural Networks written by Arslan Munir and published by John Wiley & Sons. This book was released on 2023-10-16 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: Accelerators for Convolutional Neural Networks Comprehensive and thorough resource exploring different types of convolutional neural networks and complementary accelerators Accelerators for Convolutional Neural Networks provides basic deep learning knowledge and instructive content to build up convolutional neural network (CNN) accelerators for the Internet of things (IoT) and edge computing practitioners, elucidating compressive coding for CNNs, presenting a two-step lossless input feature maps compression method, discussing arithmetic coding -based lossless weights compression method and the design of an associated decoding method, describing contemporary sparse CNNs that consider sparsity in both weights and activation maps, and discussing hardware/software co-design and co-scheduling techniques that can lead to better optimization and utilization of the available hardware resources for CNN acceleration. The first part of the book provides an overview of CNNs along with the composition and parameters of different contemporary CNN models. Later chapters focus on compressive coding for CNNs and the design of dense CNN accelerators. The book also provides directions for future research and development for CNN accelerators. Other sample topics covered in Accelerators for Convolutional Neural Networks include: How to apply arithmetic coding and decoding with range scaling for lossless weight compression for 5-bit CNN weights to deploy CNNs in extremely resource-constrained systems State-of-the-art research surrounding dense CNN accelerators, which are mostly based on systolic arrays or parallel multiply-accumulate (MAC) arrays iMAC dense CNN accelerator, which combines image-to-column (im2col) and general matrix multiplication (GEMM) hardware acceleration Multi-threaded, low-cost, log-based processing element (PE) core, instances of which are stacked in a spatial grid to engender NeuroMAX dense accelerator Sparse-PE, a multi-threaded and flexible CNN PE core that exploits sparsity in both weights and activation maps, instances of which can be stacked in a spatial grid for engendering sparse CNN accelerators For researchers in AI, computer vision, computer architecture, and embedded systems, along with graduate and senior undergraduate students in related programs of study, Accelerators for Convolutional Neural Networks is an essential resource to understanding the many facets of the subject and relevant applications.
Book Synopsis Advanced Computer Architecture by : Chao Li
Download or read book Advanced Computer Architecture written by Chao Li and published by Springer. This book was released on 2018-09-12 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 12th Annual Conference on Advanced Computer Architecture, ACA 2018, held in Yingkou, China, in August 2018. The 17 revised full papers presented were carefully reviewed and selected from 80 submissions. The papers of this volume are organized in topical sections on: accelerators; new design explorations; towards efficient ML/AI; parallel computing system.
Book Synopsis VLSI Design and Test by : S. Rajaram
Download or read book VLSI Design and Test written by S. Rajaram and published by Springer. This book was released on 2019-01-24 with total page 722 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 22st International Symposium on VLSI Design and Test, VDAT 2018, held in Madurai, India, in June 2018. The 39 full papers and 11 short papers presented together with 8 poster papers were carefully reviewed and selected from 231 submissions. The papers are organized in topical sections named: digital design; analog and mixed signal design; hardware security; micro bio-fluidics; VLSI testing; analog circuits and devices; network-on-chip; memory; quantum computing and NoC; sensors and interfaces.
Book Synopsis 2019 IEEE Computer Society Annual Symposium on VLSI (ISVLSI) by : IEEE Staff
Download or read book 2019 IEEE Computer Society Annual Symposium on VLSI (ISVLSI) written by IEEE Staff and published by . This book was released on 2019-07-15 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This Symposium explores emerging trends and novel ideas and concepts in the area of VLSI The Symposium covers a range of topics from VLSI circuits, systems and design methods to system level design and system on chip issues, to bringing VLSI experience to new areas and technologies Future design methodologies as well as new CAD tools to support them will also be the key topics ISVLSI 2019 highlights a special theme of Neuromoprhic Computing Over almost two decades the Symposium has been a unique forum promoting multidisciplinary research and new visionary approaches in the area of VLSI
Book Synopsis Hardware Accelerator Systems for Artificial Intelligence and Machine Learning by : Shiho Kim
Download or read book Hardware Accelerator Systems for Artificial Intelligence and Machine Learning written by Shiho Kim and published by Elsevier. This book was released on 2021-04-07 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Volume 122 delves into arti?cial Intelligence and the growth it has seen with the advent of Deep Neural Networks (DNNs) and Machine Learning. Updates in this release include chapters on Hardware accelerator systems for artificial intelligence and machine learning, Introduction to Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Deep Learning with GPUs, Edge Computing Optimization of Deep Learning Models for Specialized Tensor Processing Architectures, Architecture of NPU for DNN, Hardware Architecture for Convolutional Neural Network for Image Processing, FPGA based Neural Network Accelerators, and much more. Updates on new information on the architecture of GPU, NPU and DNN Discusses In-memory computing, Machine intelligence and Quantum computing Includes sections on Hardware Accelerator Systems to improve processing efficiency and performance
Book Synopsis Embedded Computer Systems: Architectures, Modeling, and Simulation by : Alex Orailoglu
Download or read book Embedded Computer Systems: Architectures, Modeling, and Simulation written by Alex Orailoglu and published by Springer. This book was released on 2020-10-15 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 20th International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation, SAMOS 2020, held in Samos, Greece, in July 2020.* The 16 regular papers presented were carefully reviewed and selected from 35 submissions. In addition, 9 papers from two special sessions were included, which were organized on topics of current interest: innovative architectures for security and European projects on embedded and high performance computing for health applications. * The conference was held virtually due to the COVID-19 pandemic.
Book Synopsis Hardware Accelerator Systems for Artificial Intelligence and Machine Learning by :
Download or read book Hardware Accelerator Systems for Artificial Intelligence and Machine Learning written by and published by Academic Press. This book was released on 2021-03-28 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Volume 122 delves into arti?cial Intelligence and the growth it has seen with the advent of Deep Neural Networks (DNNs) and Machine Learning. Updates in this release include chapters on Hardware accelerator systems for artificial intelligence and machine learning, Introduction to Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Deep Learning with GPUs, Edge Computing Optimization of Deep Learning Models for Specialized Tensor Processing Architectures, Architecture of NPU for DNN, Hardware Architecture for Convolutional Neural Network for Image Processing, FPGA based Neural Network Accelerators, and much more. Updates on new information on the architecture of GPU, NPU and DNN Discusses In-memory computing, Machine intelligence and Quantum computing Includes sections on Hardware Accelerator Systems to improve processing efficiency and performance
Book Synopsis Artificial Neural Networks and Machine Learning -- ICANN 2014 by : Stefan Wermter
Download or read book Artificial Neural Networks and Machine Learning -- ICANN 2014 written by Stefan Wermter and published by Springer. This book was released on 2014-08-18 with total page 852 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book constitutes the proceedings of the 24th International Conference on Artificial Neural Networks, ICANN 2014, held in Hamburg, Germany, in September 2014. The 107 papers included in the proceedings were carefully reviewed and selected from 173 submissions. The focus of the papers is on following topics: recurrent networks; competitive learning and self-organisation; clustering and classification; trees and graphs; human-machine interaction; deep networks; theory; reinforcement learning and action; vision; supervised learning; dynamical models and time series; neuroscience; and applications.
Book Synopsis Proceedings of the 2017 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays by : Jonathan Greene
Download or read book Proceedings of the 2017 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays written by Jonathan Greene and published by . This book was released on 2017-02-22 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: FPGA '17: The 2017 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays Feb 22, 2017-Feb 24, 2017 Monterey, USA. You can view more information about this proceeding and all of ACM�s other published conference proceedings from the ACM Digital Library: http://www.acm.org/dl.
Book Synopsis Artificial Intelligence and Hardware Accelerators by : Ashutosh Mishra
Download or read book Artificial Intelligence and Hardware Accelerators written by Ashutosh Mishra and published by Springer Nature. This book was released on 2023-03-15 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores new methods, architectures, tools, and algorithms for Artificial Intelligence Hardware Accelerators. The authors have structured the material to simplify readers’ journey toward understanding the aspects of designing hardware accelerators, complex AI algorithms, and their computational requirements, along with the multifaceted applications. Coverage focuses broadly on the hardware aspects of training, inference, mobile devices, and autonomous vehicles (AVs) based AI accelerators
Book Synopsis From CNN to DNN Hardware Accelerators by : Leonardo Rezende Juracy
Download or read book From CNN to DNN Hardware Accelerators written by Leonardo Rezende Juracy and published by . This book was released on 2023-03-06 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The past decade has witnessed the consolidation of Artificial Intelligence technology, thanks to the popularization of Machine Learning (ML) models. The technological boom of ML models started in 2012 when the world was stunned by the record-breaking classification performance achieved by combining an ML model with a high computational performance graphic processing unit (GPU). Since then, ML models received ever-increasing attention, being applied in different areas such as computational vision, virtual reality, voice assistants, chatbots, and self-driving vehicles. The most popular ML models are brain-inspired models such as Neural Networks (NNs), including Convolutional Neural Networks (CNNs) and, more recently, Deep Neural Networks (DNNs). They are characterized by resembling the human brain, performing data processing by mimicking synapses using thousands of interconnected neurons in a network. In this growing environment, GPUs have become the de facto reference platform for the training and inference phases of CNNs and DNNs, due to their high processing parallelism and memory bandwidth. However, GPUs are power-hungry architectures. To enable the deployment of CNN and DNN applications on energy-constrained devices (e.g., IoT devices), industry and academic research have moved towards hardware accelerators. Following the evolution of neural networks from CNNs to DNNs, this monograph sheds light on the impact of this architectural shift and discusses hardware accelerator trends in terms of design, exploration, simulation, and frameworks developed in both academia and industry.
Book Synopsis 2021 31st International Conference on Field Programmable Logic and Applications (FPL) by : IEEE Staff
Download or read book 2021 31st International Conference on Field Programmable Logic and Applications (FPL) written by IEEE Staff and published by . This book was released on 2021-08-30 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: First and largest conference about field programmable gate arrays and reconfigurable architectures FPL 2021 is the 31st edition of this conference
