Hao Yu

(Author)

Reram-Based Machine LearningHardcover, 30 April 2021

Reram-Based Machine Learning
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Part of Series
Computing and Networks
Print Length
261 pages
Language
English
Publisher
Institution of Engineering & Technology
Date Published
30 Apr 2021
ISBN-10
1839530812
ISBN-13
9781839530814

Description

The transition towards exascale computing has resulted in major transformations in computing paradigms. The need to analyze and respond to such large amounts of data sets has led to the adoption of machine learning (ML) and deep learning (DL) methods in a wide range of applications.

One of the major challenges is the fetching of data from computing memory and writing it back without experiencing a memory-wall bottleneck. To address such concerns, in-memory computing (IMC) and supporting frameworks have been introduced. In-memory computing methods have ultra-low power and high-density embedded storage. Resistive Random-Access Memory (ReRAM) technology seems the most promising IMC solution due to its minimized leakage power, reduced power consumption and smaller hardware footprint, as well as its compatibility with CMOS technology, which is widely used in industry.

In this book, the authors introduce ReRAM techniques for performing distributed computing using IMC accelerators, present ReRAM-based IMC architectures that can perform computations of ML and data-intensive applications, as well as strategies to map ML designs onto hardware accelerators.

The book serves as a bridge between researchers in the computing domain (algorithm designers for ML and DL) and computing hardware designers.

Product Details

Authors:
Hao YuLeibin NiSai Manoj Pudukotai Dinakarrao
Book Format:
Hardcover
Country of Origin:
GB
Date Published:
30 April 2021
Dimensions:
23.88 x 16 x 1.78 cm
ISBN-10:
1839530812
ISBN-13:
9781839530814
Language:
English
Location:
Stevenage
Pages:
261
Weight:
539.77 gm

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