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Advanced Parallel Processing Technologies

Overview of attention for book
Cover of 'Advanced Parallel Processing Technologies'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 RV-CNN: Flexible and Efficient Instruction Set for CNNs Based on RISC-V Processors
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    Chapter 2 Compiling Optimization for Neural Network Accelerators
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    Chapter 3 ZhuQue: A Neural Network Programming Model Based on Labeled Data Layout
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    Chapter 4 Reducing Rename Overhead in Full-Path-Indexed File System
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    Chapter 5 Partition and Scheduling Algorithms for Neural Network Accelerators
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    Chapter 6 SPART: Optimizing CNNs by Utilizing Both Sparsity of Weights and Feature Maps
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    Chapter 7 DA-BERT: Enhancing Part-of-Speech Tagging of Aspect Sentiment Analysis Using BERT
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    Chapter 8 Random Inception Module and Its Parallel Implementation
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    Chapter 9 CBA-Detector: An Accurate Detector Against Cache-Based Attacks Using HPCs and Pintools
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    Chapter 10 An Efficient Log Parsing Algorithm Based on Heuristic Rules
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    Chapter 11 Distribution Forest: An Anomaly Detection Method Based on Isolation Forest
Attention for Chapter 2: Compiling Optimization for Neural Network Accelerators
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mendeley
4 Mendeley
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Chapter title
Compiling Optimization for Neural Network Accelerators
Chapter number 2
Book title
Advanced Parallel Processing Technologies
Published by
Springer, Cham, August 2019
DOI 10.1007/978-3-030-29611-7_2
Book ISBNs
978-3-03-029610-0, 978-3-03-029611-7
Authors

Jin Song, Yimin Zhuang, Xiaobing Chen, Tian Zhi, Shaoli Liu, Song, Jin, Zhuang, Yimin, Chen, Xiaobing, Zhi, Tian, Liu, Shaoli

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 25%
Researcher 1 25%
Unknown 2 50%
Readers by discipline Count As %
Computer Science 2 50%
Unknown 2 50%

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