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Emerging Technology and Architecture for Big-data Analytics (Hardcover, 1st ed. 2017) Loot Price: R5,037
Discovery Miles 50 370
Emerging Technology and Architecture for Big-data Analytics (Hardcover, 1st ed. 2017): Anupam Chattopadhyay, Chip-Hong Chang,...

Emerging Technology and Architecture for Big-data Analytics (Hardcover, 1st ed. 2017)

Anupam Chattopadhyay, Chip-Hong Chang, Hao Yu

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Loot Price R5,037 Discovery Miles 50 370 | Repayment Terms: R472 pm x 12*

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This book describes the current state of the art in big-data analytics, from a technology and hardware architecture perspective. The presentation is designed to be accessible to a broad audience, with general knowledge of hardware design and some interest in big-data analytics. Coverage includes emerging technology and devices for data-analytics, circuit design for data-analytics, and architecture and algorithms to support data-analytics. Readers will benefit from the realistic context used by the authors, which demonstrates what works, what doesn’t work, and what are the fundamental problems, solutions, upcoming challenges and opportunities. Provides a single-source reference to hardware architectures for big-data analytics; Covers various levels of big-data analytics hardware design abstraction and flow, from device, to circuits and systems; Demonstrates how non-volatile memory (NVM) based hardware platforms can be a viable solution to existing challenges in hardware architecture for big-data analytics.

General

Imprint: Springer International Publishing AG
Country of origin: Switzerland
Release date: April 2017
First published: 2017
Editors: Anupam Chattopadhyay • Chip-Hong Chang • Hao Yu
Dimensions: 235 x 155 x 21mm (L x W x T)
Format: Hardcover
Pages: 330
Edition: 1st ed. 2017
ISBN-13: 978-3-319-54839-5
Categories: Books > Business & Economics > General
Books > Computing & IT > General
Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Circuits & components
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LSN: 3-319-54839-5
Barcode: 9783319548395

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