On-Chip Training NPU - Algorithm, Architecture and SoC Design [[electronic resource] /] / by Donghyeon Han, Hoi-Jun Yoo
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| Autore: |
Han Donghyeon
|
| Titolo: |
On-Chip Training NPU - Algorithm, Architecture and SoC Design [[electronic resource] /] / by Donghyeon Han, Hoi-Jun Yoo
|
| Pubblicazione: | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
| Edizione: | 1st ed. 2023. |
| Descrizione fisica: | 1 online resource (249 pages) |
| Disciplina: | 621.3815 |
| Soggetto topico: | Electronic circuits |
| Embedded computer systems | |
| Microprocessors | |
| Computer architecture | |
| Electronic Circuits and Systems | |
| Embedded Systems | |
| Processor Architectures | |
| Altri autori: |
YooHoi-Jun
|
| Nota di contenuto: | 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. |
| Sommario/riassunto: | 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. |
| Titolo autorizzato: | On-Chip Training NPU - Algorithm, Architecture and SoC Design |
| ISBN: | 3-031-34237-2 |
| Formato: | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione: | Inglese |
| Record Nr.: | 9910736029603321 |
| Lo trovi qui: | Univ. Federico II |
| Opac: | Controlla la disponibilità qui |