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04804nam a22005295i 4500 |
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978-3-319-54840-1 |
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DE-He213 |
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20210618213751.0 |
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cr nn 008mamaa |
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170420s2017 gw | s |||| 0|eng d |
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|a 9783319548401
|9 978-3-319-54840-1
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|a 10.1007/978-3-319-54840-1
|2 doi
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|a 621.3815
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|a Emerging Technology and Architecture for Big-data Analytics
|h [electronic resource] /
|c edited by Anupam Chattopadhyay, Chip Hong Chang, Hao Yu.
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|a 1st ed. 2017.
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|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2017.
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| 300 |
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|a XI, 330 p. 162 illus., 98 illus. in color.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
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|a text file
|b PDF
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|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.
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|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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|a Electronic circuits.
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| 650 |
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|a Microprocessors.
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| 650 |
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|a Big data.
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| 650 |
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4 |
|a Circuits and Systems.
|0 https://scigraph.springernature.com/ontologies/product-market-codes/T24068
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| 650 |
2 |
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|a Processor Architectures.
|0 https://scigraph.springernature.com/ontologies/product-market-codes/I13014
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| 650 |
2 |
4 |
|a Electronic Circuits and Devices.
|0 https://scigraph.springernature.com/ontologies/product-market-codes/P31010
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| 650 |
2 |
4 |
|a Big Data/Analytics.
|0 https://scigraph.springernature.com/ontologies/product-market-codes/522070
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| 700 |
1 |
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|a Chattopadhyay, Anupam.
|e editor.
|0 (orcid)0000-0002-8818-6983
|1 https://orcid.org/0000-0002-8818-6983
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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| 700 |
1 |
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|a Chang, Chip Hong.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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| 700 |
1 |
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|a Yu, Hao.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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| 710 |
2 |
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|a SpringerLink (Online service)
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| 773 |
0 |
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|t Springer Nature eBook
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| 776 |
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8 |
|i Printed edition:
|z 9783319548395
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| 776 |
0 |
8 |
|i Printed edition:
|z 9783319548418
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| 776 |
0 |
8 |
|i Printed edition:
|z 9783319854977
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| 856 |
4 |
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|u https://doi.org/10.1007/978-3-319-54840-1
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| 912 |
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|a ZDB-2-ENG
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| 912 |
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|a ZDB-2-SXE
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| 950 |
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|a Engineering (SpringerNature-11647)
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| 950 |
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|a Engineering (R0) (SpringerNature-43712)
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