Emerging technology and architecture for big-data analytics

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 eme...

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Další autoři: Chattopadhyay, Anupam, 1977- (Editor) 
Chang, Chip-Hong (Editor) 
Yu, Hao, 1976- (Editor) 
Korporace: SpringerLink (online služba) (Distributor) 
Médium: E-kniha
Jazyk:angličtina
Vydáno: Cham : Springer, 2017
Žánr/forma:sborníky
elektronické knihy
ISBN:978-3-319-54840-1
978-3-319-54839-5
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On-line přístup:Plný text
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245 0 0 |a Emerging technology and architecture for big-data analytics /  |c Anupam Chattopadhyay, Chip Hong Chang, Hao Yu, edited 
264 1 |a Cham :  |b Springer,  |c [2017] 
264 4 |c ©2017 
300 |a 1 online zdroj (XI, 330 stran) :  |b 162 ilustrací, 98 barevných ilustrací 
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505 0 |a Part I State-of-the-Art Architectures and Automation for Data-analytics -- Chapter 1. Scaling the Java Virtual Machine on a Many-core System -- Chapter 2. Scaling the Java Virtual Machine on a Many-core System -- Chapter 3. Least-squares based Machine Learning Accelerator for Big-data Analytics in Smart Buildings -- Chapter 4. Compute-in-memory Architecture for Data-Intensive Kernels -- Chapter 5. New Solutions for Cross-Layer System-Level and High-Level Synthesis -- Part II New Solutions for Cross-Layer System-Level and High-Level Synthesis -- Chapter 6. Side Channel Attacks and Efficient Countermeasures on Residue Number System Multipliers -- Chapter 7. Ultra-Low-Power Biomedical Circuit Design and Optimization: Catching The Don’t Cares -- Chapter 8. Acceleration of MapReduce Framework on a Multicore Processor -- Chapter 9. Adaptive dynamic range compression for improving envelope-based speech perception: Implications for cochlear implants -- Part III Emerging Technology, Circuits and Systems for Data-analytics -- Chapter 10. Emerging Technology, Circuits and Systems for Data-analytics -- Chapter 11. Energy Efficient Spiking Neural Network Design with RRAM Devices -- Chapter 12. Efficient Neuromorphic Systems and Emerging Technologies: Prospects and Perspectives -- Chapter 13. In-memory Data Compression Using ReRAMs -- Chapter 14. In-memory Data Compression Using ReRAMs -- Chapter 15. Data Analytics in Quantum Paradigm: An Introduction 
520 |a 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. 
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700 1 |a Yu, Hao,  |d 1976-  |7 ntk20191035840  |4 edt  |0 https://orcid.org/0000-0001-8747-3203 
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