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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 Parallel and Distributed Processing for Unsupervised Patient Phenotype Representation
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    Chapter 2 Evolutionary Algorithms for Convolutional Neural Network Visualisation
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    Chapter 3 Breast Cancer Classification: A Deep Learning Approach for Digital Pathology
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    Chapter 4 Where Do HPC and Cognitive Science Meet in Latin America?
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    Chapter 5 A Hybrid Reinforcement Learning and Cellular Automata Model for Crowd Simulation on the GPU
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    Chapter 6 In-situ Visualization of the Propagation of the Electric Potential in a Human Atrial Model Using GPU
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    Chapter 7 GPU Acceleration for Directional Variance Based Intra-prediction in HEVC
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    Chapter 8 Fast Marching Method in Seismic Ray Tracing on Parallel GPU Devices
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    Chapter 9 Improving Performance and Energy Efficiency of Geophysics Applications on GPU Architectures
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    Chapter 10 FleCSPHg: A GPU Accelerated Framework for Physics and Astrophysics Simulations
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    Chapter 11 Comparison of Tree Based Strategies for Parallel Simulation of Self-gravity in Agglomerates
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    Chapter 12 Parallel Implementations of Self-gravity Calculation for Small Astronomical Bodies on Xeon Phi
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    Chapter 13 Visualization of a Jet in Turbulent Crossflow
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    Chapter 14 Acceleration of Hydrology Simulations Using DHSVM for Multi-thousand Runs and Uncertainty Assessment
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    Chapter 15 Fine-Tuning an OpenMP-Based TVD–Hopmoc Method Using Intel ® Parallel Studio XE Tools on Intel ® Xeon ® Architectures
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    Chapter 16 Performance Evaluation of Stencil Computations Based on Source-to-Source Transformations
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    Chapter 17 Benchmarking LAMMPS: Sensitivity to Task Location Under CPU-Based Weak-Scaling
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    Chapter 18 Analyzing Communication Features and Community Structure of HPC Applications
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    Chapter 19 Power Efficiency Analysis of a Deep Learning Workload on an IBM “Minsky” Platform
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    Chapter 20 Orlando Tools: Development, Training, and Use of Scalable Applications in Heterogeneous Distributed Computing Environments
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    Chapter 21 Methodology for Tailored Linux Distributions Development for HPC Embedded Systems
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    Chapter 22 Cost and QoS Optimization of Cloud-Based Content Distribution Networks Using Evolutionary Algorithms
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    Chapter 23 Bi-objective Analysis of an Adaptive Secure Data Storage in a Multi-cloud
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    Chapter 24 Fault Characterization and Mitigation Strategies in Desktop Cloud Systems
Attention for Chapter 21: Methodology for Tailored Linux Distributions Development for HPC Embedded Systems
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Chapter title
Methodology for Tailored Linux Distributions Development for HPC Embedded Systems
Chapter number 21
Book title
High Performance Computing
Published by
Springer, Cham, September 2018
DOI 10.1007/978-3-030-16205-4_21
Book ISBNs
978-3-03-016204-7, 978-3-03-016205-4
Authors

Gilberto Díaz, Pablo Rojas, Carlos Barrios

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