Emerging Technology and Architecture for Big-data Analytics

✍ Scribed by Anupam Chattopadhyay, Chip Hong Chang, Hao Yu (eds.)

• Publisher: Springer International Publishing
• Year: 2017
• Tongue: English
• Leaves: 332
• Edition: 1
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

Front Matter....Pages i-xi
Front Matter....Pages 1-1
Scaling the Java Virtual Machine on a Many-Core System....Pages 3-24
Accelerating Data Analytics Kernels with Heterogeneous Computing....Pages 25-49
Least-squares-solver Based Machine Learning Accelerator for Real-time Data Analytics in Smart Buildings....Pages 51-76
Compute-in-Memory Architecture for Data-Intensive Kernels....Pages 77-101
New Solutions for Cross-Layer System-Level and High-Level Synthesis....Pages 103-134
Front Matter....Pages 135-135
Side Channel Attacks and Their Low Overhead Countermeasures on Residue Number System Multipliers....Pages 137-158
Ultra-Low-Power Biomedical Circuit Design and Optimization: Catching the Don’t Cares....Pages 159-173
Acceleration of MapReduce Framework on a Multicore Processor....Pages 175-190
Adaptive Dynamic Range Compression for Improving Envelope-Based Speech Perception: Implications for Cochlear Implants....Pages 191-214
Front Matter....Pages 215-215
Neuromorphic Hardware Acceleration Enabled by Emerging Technologies....Pages 217-244
Energy Efficient Spiking Neural Network Design with RRAM Devices....Pages 245-259
Efficient Neuromorphic Systems and Emerging Technologies: Prospects and Perspectives....Pages 261-274
In-Memory Data Compression Using ReRAMs....Pages 275-291
Big Data Management in Neural Implants: The Neuromorphic Approach....Pages 293-311
Data Analytics in Quantum Paradigm: An Introduction....Pages 313-330

✦ Subjects

Circuits and Systems;Processor Architectures;Electronic Circuits and Devices;Big Data/Analytics