03446nam 22005895 450 991073602960332120230727223805.03-031-34237-210.1007/978-3-031-34237-0(MiAaPQ)EBC30668268(Au-PeEL)EBL30668268(DE-He213)978-3-031-34237-0(PPN)272257222(CKB)27867643500041(EXLCZ)992786764350004120230727d2023 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierOn-Chip Training NPU - Algorithm, Architecture and SoC Design /by Donghyeon Han, Hoi-Jun Yoo1st ed. 2023.Cham :Springer Nature Switzerland :Imprint: Springer,2023.1 online resource (249 pages)Print version: Han, Donghyeon On-Chip Training NPU - Algorithm, Architecture and SoC Design Cham : Springer,c2023 9783031342363 Chapter 1 Introduction -- Chapter 2 A Theoretical Study on Artificial Intelligence Training -- Chapter 3 New Algorithm 1: Binary Direct Feedback Alignment for Fully-Connected layer -- Chapter 4 New Algorithm 2: Extension of Direct Feedback Alignment to Convolutional Recurrent Neural Network -- Chapter 5 DF-LNPU: A Pipelined Direct Feedback Alignment based Deep Neural Network Learning Processor for Fast Online Learning -- Chapter 6 HNPU-V1: An Adaptive DNN Training Processor Utilizing Stochastic Dynamic Fixed-point and Active Bit-precision Searching -- Chapter 7 HNPU-V2: An Energy-efficient DNN Training Processor for Robust Object Detection with Real-World Environmental Adaptation -- Chapter 8 An Overview of Energy-efficient DNN Training Processors -- Chapter 9 Conclusion.Unlike most available sources that focus on deep neural network (DNN) inference, this book provides readers with a single-source reference on the needs, requirements, and challenges involved with on-device, DNN training semiconductor and SoC design. The authors include coverage of the trends and history surrounding the development of on-device DNN training, as well as on-device training semiconductors and SoC design examples to facilitate understanding. Focuses on the requirements and challenges of on-device deep neural network (DNN) training, rather than DNN inference; Provides guidelines for on-device, DNN training semiconductor or System-on-Chip (SoC) design; Includes on-device training semiconductors and SoC design examples to facilitate understanding.Electronic circuitsEmbedded computer systemsMicroprocessorsComputer architectureElectronic Circuits and SystemsEmbedded SystemsProcessor ArchitecturesElectronic circuits.Embedded computer systems.Microprocessors.Computer architecture.Electronic Circuits and Systems.Embedded Systems.Processor Architectures.621.3815Han Donghyeon1380380Yoo Hoi-Jun1380381MiAaPQMiAaPQMiAaPQBOOK9910736029603321On-Chip Training NPU - Algorithm, Architecture and SoC Design3421645UNINA