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Advanced Computer Architecture

Overview of attention for book
Cover of 'Advanced Computer Architecture'

Table of Contents

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    Book Overview
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    Chapter 1 A Scalable FPGA Accelerator for Convolutional Neural Networks
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    Chapter 2 Memory Bandwidth and Energy Efficiency Optimization of Deep Convolutional Neural Network Accelerators
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    Chapter 3 Research on Parallel Acceleration for Deep Learning Inference Based on Many-Core ARM Platform
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    Chapter 4 Research on Acceleration Method of Speech Recognition Training
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    Chapter 5 A Post-link Prefetching Based on Event Sampling
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    Chapter 6 The Design of Reconfigurable Instruction Set Processor Based on ARM Architecture
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    Chapter 7 Stateful Forward-Edge CFI Enforcement with Intel MPX
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    Chapter 8 Analytical Two-Level Near Threshold Cache Exploration for Low Power Biomedical Applications
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    Chapter 9 DearDRAM: Discard Weak Rows for Reducing DRAM’s Refresh Overhead
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    Chapter 10 EffectFace: A Fast and Efficient Deep Neural Network Model for Face Recognition
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    Chapter 11 A Power Efficient Hardware Implementation of the IF Neuron Model
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    Chapter 12 paraSNF: An Parallel Approach for Large-Scale Similarity Network Fusion
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    Chapter 13 An Experimental Perspective for Computation-Efficient Neural Networks Training
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    Chapter 14 Distributed Data Load Balancing for Scalable Key-Value Cache Systems
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    Chapter 15 Performance Analysis and Optimization of Cyro-EM Structure Determination in RELION-2
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    Chapter 16 The Checkpoint-Timing for Backward Fault-Tolerant Schemes
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    Chapter 17 Quota-constrained Job Submission Behavior at Commercial Supercomputer
Attention for Chapter 1: A Scalable FPGA Accelerator for Convolutional Neural Networks
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Chapter title
A Scalable FPGA Accelerator for Convolutional Neural Networks
Chapter number 1
Book title
Advanced Computer Architecture
Published by
Springer, Singapore, August 2018
DOI 10.1007/978-981-13-2423-9_1
Book ISBNs
978-9-81-132422-2, 978-9-81-132423-9
Authors

Ke Xu, Xiaoyun Wang, Shihang Fu, Dong Wang, Xu, Ke, Wang, Xiaoyun, Fu, Shihang, Wang, Dong

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 35 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 23%
Student > Bachelor 4 11%
Researcher 3 9%
Student > Master 3 9%
Professor 2 6%
Other 2 6%
Unknown 13 37%
Readers by discipline Count As %
Engineering 15 43%
Computer Science 8 23%
Unknown 12 34%

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