Donghyeon Han,
Hoi-Jun Yoo
Springer Nature Switzerland
e druk, 2023
9783031342363
On-Chip Training NPU - Algorithm, Architecture and SoC Design
Specificaties
Gebonden, blz.
|
Engels
Springer Nature Switzerland |
2023
ISBN13: 9783031342363
Rubricering
Levertijd ongeveer 9 werkdagen
Gratis verzonden
Samenvatting
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.
Specificaties
ISBN13:9783031342363
Taal:Engels
Bindwijze:gebonden
Uitgever:Springer Nature Switzerland
Inhoudsopgave
<p>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.<br></p>