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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 A Deep Learning Mapper (DLM) for Scheduling on Heterogeneous Systems
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    Chapter 2 Power Consumption Characterization of Synthetic Benchmarks in Multicores
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    Chapter 3 Initial Experiences from TUPAC Supercomputer
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    Chapter 4 romeoLAB: A High Performance Training Platform for HPC, GPU and DeepLearning
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    Chapter 5 Analysis and Characterization of GPU Benchmarks for Kernel Concurrency Efficiency
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    Chapter 6 Parallel Batch Self-Organizing Map on Graphics Processing Unit Using CUDA
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    Chapter 7 Performance Prediction of Acoustic Wave Numerical Kernel on Intel Xeon Phi Processor
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    Chapter 8 Evaluating the NVIDIA Tegra Processor as a Low-Power Alternative for Sparse GPU Computations
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    Chapter 9 Benchmarking Performance: Influence of Task Location on Cluster Throughput
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    Chapter 10 PRIMULA: A Framework Based on Finite Elements to Address Multi Scale and Multi Physics Problems
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    Chapter 11 FaaSter, Better, Cheaper: The Prospect of Serverless Scientific Computing and HPC
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    Chapter 12 AccaSim: An HPC Simulator for Workload Management
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    Chapter 13 SherlockFog: Finding Opportunities for MPI Applications in Fog and Edge Computing
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    Chapter 14 IoT Workload Distribution Impact Between Edge and Cloud Computing in a Smart Grid Application
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    Chapter 15 Model-R: A Framework for Scalable and Reproducible Ecological Niche Modeling
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    Chapter 16 Task Scheduling for Processing Big Graphs in Heterogeneous Commodity Clusters
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    Chapter 17 Exploring Application-Level Message-Logging in Scalable HPC Programs
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    Chapter 18 Accelerated Numerical Optimization with Explicit Consideration of Model Constraints
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    Chapter 19 Parallel Processing of Intra-cranial Electroencephalogram Readings on Distributed Memory Systems
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    Chapter 20 Support Vector Machine Acceleration for Intel Xeon Phi Manycore Processors
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    Chapter 21 Performance Improvements of a Parallel Multithreading Self-gravity Algorithm
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    Chapter 22 A Fast GPU Convolution/Superposition Method for Radiotherapy Dose Calculation
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    Chapter 23 Eeny Meeny Miny Moe: Choosing the Fault Tolerance Technique for my Cloud Workflow
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    Chapter 24 Energy Aware Multiobjective Scheduling in a Federation of Heterogeneous Datacenters
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    Chapter 25 Markov Decision Process to Dynamically Adapt Spots Instances Ratio on the Autoscaling of Scientific Workflows in the Cloud
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    Chapter 26 Experimental Analysis of Secret Sharing Schemes for Cloud Storage Based on RNS
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    Chapter 27 Bi-objective Heterogeneous Consolidation in Cloud Computing
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    Chapter 28 Scaling the Deployment of Virtual Machines in UnaCloud
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    Chapter 29 Distributed Cosmic Ray Detection Using Cloud Computing
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High Performance Computing
Published by
Springer, Cham, January 2017
DOI 10.1007/978-3-319-73353-1
978-3-31-973352-4, 978-3-31-973353-1

Esteban Mocskos, Sergio Nesmachnow

Mendeley readers

The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 29%
Student > Ph. D. Student 1 14%
Student > Master 1 14%
Unknown 3 43%
Readers by discipline Count As %
Agricultural and Biological Sciences 3 43%
Unknown 4 57%