Number Systems for Deep Neural Network Architectures

Number Systems for Deep Neural Network Architectures
Author :
Publisher : Springer Nature
Total Pages : 100
Release :
ISBN-10 : 9783031381331
ISBN-13 : 3031381335
Rating : 4/5 (31 Downloads)

Book Synopsis Number Systems for Deep Neural Network Architectures by : Ghada Alsuhli

Download or read book Number Systems for Deep Neural Network Architectures written by Ghada Alsuhli and published by Springer Nature. This book was released on 2023-09-01 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides readers a comprehensive introduction to alternative number systems for more efficient representations of Deep Neural Network (DNN) data. Various number systems (conventional/unconventional) exploited for DNNs are discussed, including Floating Point (FP), Fixed Point (FXP), Logarithmic Number System (LNS), Residue Number System (RNS), Block Floating Point Number System (BFP), Dynamic Fixed-Point Number System (DFXP) and Posit Number System (PNS). The authors explore the impact of these number systems on the performance and hardware design of DNNs, highlighting the challenges associated with each number system and various solutions that are proposed for addressing them.


Number Systems for Deep Neural Network Architectures Related Books

Number Systems for Deep Neural Network Architectures
Language: en
Pages: 100
Authors: Ghada Alsuhli
Categories: Technology & Engineering
Type: BOOK - Published: 2023-09-01 - Publisher: Springer Nature

DOWNLOAD EBOOK

This book provides readers a comprehensive introduction to alternative number systems for more efficient representations of Deep Neural Network (DNN) data. Vari
Math and Architectures of Deep Learning
Language: en
Pages: 550
Authors: Krishnendu Chaudhury
Categories: Computers
Type: BOOK - Published: 2024-03-26 - Publisher: Simon and Schuster

DOWNLOAD EBOOK

Math and Architectures of Deep Learning bridges the gap between theory and practice, laying out the math of deep learning side by side with practical implementa
Efficient Processing of Deep Neural Networks
Language: en
Pages: 254
Authors: Vivienne Sze
Categories: Technology & Engineering
Type: BOOK - Published: 2022-05-31 - Publisher: Springer Nature

DOWNLOAD EBOOK

This book provides a structured treatment of the key principles and techniques for enabling efficient processing of deep neural networks (DNNs). DNNs are curren
Deep Learning Patterns and Practices
Language: en
Pages: 787
Authors: Andrew Ferlitsch
Categories: Computers
Type: BOOK - Published: 2021-10-12 - Publisher: Simon and Schuster

DOWNLOAD EBOOK

Discover best practices, reproducible architectures, and design patterns to help guide deep learning models from the lab into production. In Deep Learning Patte
Neural Network Design
Language: en
Pages:
Authors: Martin T. Hagan
Categories: Neural networks (Computer science)
Type: BOOK - Published: 2003 - Publisher:

DOWNLOAD EBOOK