Fr. 190.90

Reram-Based Machine Learning

English · Hardback

Shipping usually within 2 to 3 weeks (title will be printed to order)

Description

Read more










Serving as a bridge between researchers in the computing domain and computing hardware designers, this book presents ReRAM techniques for distributed computing using IMC accelerators, ReRAM-based IMC architectures for machine learning (ML) and data-intensive applications, and strategies to map ML designs onto hardware accelerators.


About the author










Hao Yu is a professor in the School of Microelectronics at Southern University of Science and Technology (SUSTech), China. His main research interests cover energy-efficient IC chip design and mmwave IC design. He is a senior member of IEEE and a member of ACM. He has written several books and holds 20 granted patents. He is a distinguished lecturer of IEEE Circuits and Systems and associate editor of Elsevier Integration, the VLSI Journal, Elsevier Microelectronics Journal, Nature Scientific Reports, ACM Transactions on Embedded Computing Systems and IEEE Transactions on Biomedical Circuits and Systems. He is also a technical program committee member of several IC conferences, including IEEE CICC, BioCAS, A-SSCC, ACM DAC, DATE and ICCAD. He obtained his Ph.D. degree from the EE department at UCLA, USA.


Summary

Serving as a bridge between researchers in the computing domain and computing hardware designers, this book presents ReRAM techniques for distributed computing using IMC accelerators, ReRAM-based IMC architectures for machine learning (ML) and data-intensive applications, and strategies to map ML designs onto hardware accelerators.

Product details

Authors Sai Manoj Pudukotai Dinakarrao, Leibin Ni, Leibin (Principle Engineer Ni, Sai Manoj Pudukotai Dinakarrao, Sai Manoj (Assistant Professor Pudukotai Dinakarrao, Hao Yu, Hao (Professor Yu
Publisher Institution of Engineering & Technology
 
Languages English
Product format Hardback
Released 30.04.2021
 
EAN 9781839530814
ISBN 978-1-83953-081-4
No. of pages 261
Dimensions 160 mm x 239 mm x 18 mm
Weight 540 g
Series Computing and Networks
Subject Natural sciences, medicine, IT, technology > IT, data processing > IT

Customer reviews

No reviews have been written for this item yet. Write the first review and be helpful to other users when they decide on a purchase.

Write a review

Thumbs up or thumbs down? Write your own review.

For messages to CeDe.ch please use the contact form.

The input fields marked * are obligatory

By submitting this form you agree to our data privacy statement.