In-Memory Computing Architectures for Big Data and Machine Learning Applications

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F22%3A10252016" target="_blank" >RIV/61989100:27240/22:10252016 - isvavai.cz</a>

Result on the web

<a href="https://link.springer.com/chapter/10.1007/978-981-19-8069-5_2" target="_blank" >https://link.springer.com/chapter/10.1007/978-981-19-8069-5_2</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-981-19-8069-5_2" target="_blank" >10.1007/978-981-19-8069-5_2</a>

Result language

angličtina

Original language name

In-Memory Computing Architectures for Big Data and Machine Learning Applications

Original language description

Traditional computing hardware is working to meet the extensive computational load presented by the rapidly growing Machine Learning (ML) and Artificial Intelligence algorithms such as Deep Neural Networks and Big Data. In order to get hardware solutions to meet the low-latency and high-throughput computational needs of these algorithms, Non-Von Neumann computing architectures such as In-memory Computing (IMC) have been extensively researched and experimented with over the last five years. This study analyses and reviews works designed to accelerate Machine Learning task. We investigate different architectural aspects and directions and provide our comparative evaluations. We further discuss IMC research&apos;s challenges and limitations and present possible directions.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2022

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

FUTURE DATA AND SECURITY ENGINEERING. BIG DATA, SECURITY AND PRIVACY, SMART CITY AND INDUSTRY 4.0 APPLICATIONS, FDSE 2022

ISBN

978-981-19806-9-5

ISSN

1865-0929

e-ISSN

1865-0937

Number of pages

15

Pages from-to

19-33

Publisher name

SPRINGER INTERNATIONAL PUBLISHING AG

Place of publication

CHAM

Event location

Ho Chi Minh

Event date

Nov 23, 2022

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000921145600002