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High Performance Computing

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Cover of 'High Performance Computing'

Table of Contents

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    Book Overview
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    Chapter 1 Dynamically Distributing Tasks from an Unattended Parallel Compiler with Cloudbook
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    Chapter 2 Fostering Remote Visualization: Experiences in Two Different HPC Sites
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    Chapter 3 High Performance Computing Simulations of Granular Media in Silos
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    Chapter 4 Performance Analysis of Main Public Cloud Big Data Services Processing Brazilian Government Data
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    Chapter 5 Accelerating Machine Learning Algorithms with TensorFlow Using Thread Mapping Policies
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    Chapter 6 Methodology for Design and Implementation an Efficient HPC Cluster
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    Chapter 7 Estimating the Execution Time of the Coupled Stage in Multiscale Numerical Simulations
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    Chapter 8 Using HPC as a Competitive Advantage in an International Robotics Challenge
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    Chapter 9 A Survey on Privacy-Preserving Machine Learning with Fully Homomorphic Encryption
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    Chapter 10 Distributed Greedy Approach for Autonomous Surveillance Using Unmanned Aerial Vehicles
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    Chapter 11 Electricity Demand Forecasting Using Computational Intelligence and High Performance Computing
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    Chapter 12 Parallel/Distributed Generative Adversarial Neural Networks for Data Augmentation of COVID-19 Training Images
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    Chapter 13 Analysis of Regularization in Deep Learning Models on Testbed Architectures
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    Chapter 14 Computer Application for the Detection of Skin Diseases in Photographic Images Using Convolutional Neural Networks
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    Chapter 15 Neocortex and Bridges-2: A High Performance AI+HPC Ecosystem for Science, Discovery, and Societal Good
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Title
High Performance Computing
Published by
Springer International Publishing, January 2021
DOI 10.1007/978-3-030-68035-0
ISBNs
978-3-03-068034-3, 978-3-03-068035-0
Editors

Nesmachnow, Sergio, Castro, Harold, Tchernykh, Andrei

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