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Author : Anonim
Publisher : Unknown
Page : 2266 pages
File Size : 51,5 Mb
Release : 1895
Category : Hardware
ISBN : UOM:39015080299053
Author : Laura Isabel Galindez Olascoaga,Wannes Meert,Marian Verhelst
Publisher : Springer Nature
Page : 163 pages
File Size : 42,6 Mb
Release : 2021-05-19
Category : Technology & Engineering
ISBN : 9783030740429
This book proposes probabilistic machine learning models that represent the hardware properties of the device hosting them. These models can be used to evaluate the impact that a specific device configuration may have on resource consumption and performance of the machine learning task, with the overarching goal of balancing the two optimally. The book first motivates extreme-edge computing in the context of the Internet of Things (IoT) paradigm. Then, it briefly reviews the steps involved in the execution of a machine learning task and identifies the implications associated with implementing this type of workload in resource-constrained devices. The core of this book focuses on augmenting and exploiting the properties of Bayesian Networks and Probabilistic Circuits in order to endow them with hardware-awareness. The proposed models can encode the properties of various device sub-systems that are typically not considered by other resource-aware strategies, bringing about resource-saving opportunities that traditional approaches fail to uncover. The performance of the proposed models and strategies is empirically evaluated for several use cases. All of the considered examples show the potential of attaining significant resource-saving opportunities with minimal accuracy losses at application time. Overall, this book constitutes a novel approach to hardware-algorithm co-optimization that further bridges the fields of Machine Learning and Electrical Engineering.
Author : Sandeep Saini,Kusum Lata,G.R. Sinha
Publisher : CRC Press
Page : 292 pages
File Size : 47,8 Mb
Release : 2021-12-31
Category : Technology & Engineering
ISBN : 9781000523843
Machine learning is a potential solution to resolve bottleneck issues in VLSI via optimizing tasks in the design process. This book aims to provide the latest machine-learning–based methods, algorithms, architectures, and frameworks designed for VLSI design. The focus is on digital, analog, and mixed-signal design techniques, device modeling, physical design, hardware implementation, testability, reconfigurable design, synthesis and verification, and related areas. Chapters include case studies as well as novel research ideas in the given field. Overall, the book provides practical implementations of VLSI design, IC design, and hardware realization using machine learning techniques. Features: Provides the details of state-of-the-art machine learning methods used in VLSI design Discusses hardware implementation and device modeling pertaining to machine learning algorithms Explores machine learning for various VLSI architectures and reconfigurable computing Illustrates the latest techniques for device size and feature optimization Highlights the latest case studies and reviews of the methods used for hardware implementation This book is aimed at researchers, professionals, and graduate students in VLSI, machine learning, electrical and electronic engineering, computer engineering, and hardware systems.
Author : Anonim
Publisher : Unknown
Page : 948 pages
File Size : 55,9 Mb
Release : 1963
Category : Hardware
ISBN : NYPL:33433109829998
Author : Anonim
Publisher : Unknown
Page : 750 pages
File Size : 46,5 Mb
Release : 1980
Category : Industrial statistics
ISBN : WISC:89107187684
Business establishments, employment, and taxable pay rolls, by industry groups, under Old-Age and Survivors Program.
Author : Anonim
Publisher : Unknown
Page : 12 pages
File Size : 44,6 Mb
Release : 1905
Category : Commercial catalogs
ISBN : UOM:39015071457652
Author : Anonim
Publisher : Unknown
Page : 654 pages
File Size : 49,9 Mb
Release : 1920
Category : Electronic
ISBN : NYPL:33433063053577
Author : Anonim
Publisher : Academic Press
Page : 416 pages
File Size : 54,9 Mb
Release : 2021-03-28
Category : Computers
ISBN : 9780128231241
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
Author : Anonim
Publisher : Unknown
Page : 436 pages
File Size : 46,9 Mb
Release : 1994
Category : Industrial statistics
ISBN : UCBK:C045134554
Author : Anonim
Publisher : Unknown
Page : 500 pages
File Size : 45,7 Mb
Release : 1966
Category : Wholesale trade
ISBN : IND:30000097896322
Author : United States. Department of the Air Force
Publisher : Unknown
Page : 596 pages
File Size : 47,6 Mb
Release : 1953
Category : Freight and freightage
ISBN : MINN:30000010504052
Author : Anonim
Publisher : Unknown
Page : 32 pages
File Size : 48,6 Mb
Release : 1921
Category : Consular reports
ISBN : MINN:30000010338337
Author : United States Senate
Publisher : Unknown
Page : 1002 pages
File Size : 44,8 Mb
Release : 1872
Category : Electronic
ISBN : BSB:BSB11037581
Author : Anonim
Publisher : Unknown
Page : 816 pages
File Size : 52,7 Mb
Release : 1883
Category : Automobiles
ISBN : UOM:39015084601700
Author : American Iron and Steel Association
Publisher : Unknown
Page : 670 pages
File Size : 43,5 Mb
Release : 1897
Category : Iron industry and trade
ISBN : HARVARD:32044020482691