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Euro-Par 2019: Parallel Processing Workshops

Overview of attention for book
Cover of 'Euro-Par 2019: Parallel Processing Workshops'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Parallelization of Massive Multiway Stream Joins on Manycore CPUs
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    Chapter 2 Adaptive Crown Scheduling for Streaming Tasks on Many-Core Systems with Discrete DVFS
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    Chapter 3 Minimizing Self-adaptation Overhead in Parallel Stream Processing for Multi-cores
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    Chapter 4 A Fully Decentralized Autoscaling Algorithm for Stream Processing Applications
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    Chapter 5 Transparent Autonomicity for OpenMP Applications
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    Chapter 6 Optimizing Memory Bandwidth Efficiency with User-Preferred Kernel Merge
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    Chapter 7 Opportunities for Partitioning Non-volatile Memory DIMMs Between Co-scheduled Jobs on HPC Nodes
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    Chapter 8 Security and Privacy Management in a Fog-to-Cloud Environment
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    Chapter 9 On the Similarities and Differences Between the Cloud, Fog and the Edge
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    Chapter 10 TDM Edge Gateway: A Flexible Microservice-Based Edge Gateway Architecture for Heterogeneous Sensors
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    Chapter 11 mF2C: The Evolution of Cloud Computing Towards an Open and Coordinated Ecosystem of Fogs and Clouds
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    Chapter 12 Academic Achievement Recognition and Verification Using Blockchain
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    Chapter 13 Crypto-Trading. Rechargeable Token-Based Smart Energy Market Enabled by Blockchain and IoT Technology
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    Chapter 14 Ethereum Transaction Performance Evaluation Using Test-Nets
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    Chapter 15 Blockchain-Based Trusted Cross-organizational Deliveries of Sensor-Equipped Parcels
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    Chapter 16 Towards a Trusted Support Platform for the Job Placement Task
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    Chapter 17 Blockchain Materialization as a General Purpose Technology: A Research Framework
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    Chapter 18 On Refining Design Patterns for Smart Contracts
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    Chapter 19 DataRaceOnAccelerator – A Micro-benchmark Suite for Evaluating Correctness Tools Targeting Accelerators
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    Chapter 20 Application Topology Definition and Tasks Mapping for Efficient Use of Heterogeneous Resources
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    Chapter 21 Toward Heterogeneous MPI+MPI Programming: Comparison of OpenMP and MPI Shared Memory Models
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    Chapter 22 Multicore Performance Prediction – Comparing Three Recent Approaches in a Case Study
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    Chapter 23 Exploiting Historical Data: Pruning Autotuning Spaces and Estimating the Number of Tuning Steps
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    Chapter 24 Advancing Automatic Code Generation for Agent-Based Simulations on Heterogeneous Hardware
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    Chapter 25 Optimization of Data-Parallel Applications on Heterogeneous HPC Platforms for Dynamic Energy Through Workload Distribution
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    Chapter 26 Search-Based Scheduling for Parallel Tasks on Heterogeneous Platforms
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    Chapter 27 Adaptation of Workflow Application Scheduling Algorithm to Serverless Infrastructure
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    Chapter 28 CCAMP: OpenMP and OpenACC Interoperable Framework
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    Chapter 29 HPC Requirements of High-Fidelity Flow Simulations for Aerodynamic Applications
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    Chapter 30 Data-Adapted Parallel Merge Sort
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    Chapter 31 In Situ Visualization of Performance-Related Data in Parallel CFD Applications
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    Chapter 32 ARTICONF: Towards a Smart Social Media Ecosystem in a Blockchain Federated Environment
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    Chapter 33 Bitcoin Price Variation: An Analysis of the Correlations
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    Chapter 34 A Semantic Model with Self-adaptive and Autonomous Relevant Technology for Social Media Applications
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    Chapter 35 A Novel Data-Centric Programming Model for Large-Scale Parallel Systems
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    Chapter 36 Co-located and Orchestrated Network Fabric (CONF): An Automated Cloud Virtual Infrastructure for Social Network Applications
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    Chapter 37 Auto-scaling for a Streaming Architecture with Fuzzy Deep Reinforcement Learning
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    Chapter 38 High Performance Queries Using Compressed Bitmap Indexes
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    Chapter 39 Learning Quality Improved Word Embedding with Assessment of Hyperparameters
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    Chapter 40 Hugo: A Cluster Scheduler that Efficiently Learns to Select Complementary Data-Parallel Jobs
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    Chapter 41 FLY: A Domain-Specific Language for Scientific Computing on FaaS
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    Chapter 42 Parallel Learning of Weighted Association Rules in Human Phenotype Ontology
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    Chapter 43 Improving the Runtime Performance of Non-linear Mixed-Effects Model Estimation
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    Chapter 44 Hybrid Machine Learning and Polymer Physics Approach to Investigate 3D Chromatin Structure
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    Chapter 45 Adaptive Domain Decomposition for Effective Data Assimilation
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    Chapter 46 Sparse Grid Regression for Performance Prediction Using High-Dimensional Run Time Data
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    Chapter 47 MPCDF HPC Performance Monitoring System: Enabling Insight via Job-Specific Analysis
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    Chapter 48 Towards a Predictive Energy Model for HPC Runtime Systems Using Supervised Learning
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    Chapter 49 Resource Aware Scheduling for EDA Regression Jobs
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    Chapter 50 Space-Efficient Reed-Solomon Encoding to Detect and Correct Pointer Corruption
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    Chapter 51 Improving Reliability for Provisioning of Virtual Machines in Desktop Clouds
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    Chapter 52 Physics-Based Checksums for Silent-Error Detection in PDE Solvers
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    Chapter 53 Checkpointing Kernel Executions of MPI+CUDA Applications
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    Chapter 54 MPI+OpenMP Parallelization for Elastic Wave Simulation with an Iterative Solver
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    Chapter 55 Active-Code Replacement in the OODIDA Data Analytics Platform
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    Chapter 56 CNN-SIM: A Detailed Arquitectural Simulator of CNN Accelerators
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    Chapter 57 Duality-Based Locality-Aware Stream Partitioning in Distributed Stream Processing Engines
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    Chapter 58 Message Latency-Based Load Shedding Mechanism in Apache Kafka
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    Chapter 59 Enhancing Block-Wise Transfer with Network Coding in CoAP
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    Chapter 60 A Classification of Resource Heterogeneity in Multiprocessing Systems
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    Chapter 61 Abstract Decision Engine for Task Scheduling in Linux Based Operating Systems
  63. Altmetric Badge
    Chapter 62 Transparent Data Access for Scientific Workflows Across Clouds
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    Chapter 63 Time-Based Consensus
Overall attention for this book and its chapters
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (66th percentile)
  • Average Attention Score compared to outputs of the same age and source

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Title
Euro-Par 2019: Parallel Processing Workshops
Published by
Lecture notes in computer science, January 2020
DOI 10.1007/978-3-030-48340-1
ISBNs
978-3-03-048339-5, 978-3-03-048340-1
Editors

Schwardmann, Ulrich, Boehme, Christian, B. Heras, Dora, Cardellini, Valeria, Jeannot, Emmanuel, Salis, Antonio, Schifanella, Claudio, Manumachu, Ravi Reddy, Schwamborn, Dieter, Ricci, Laura, Sangyoon, Oh, Gruber, Thomas, Antonelli, Laura, Scott, Stephen L.

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The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 March 2024.
All research outputs
#7,436,279
of 25,605,018 outputs
Outputs from Lecture notes in computer science
#2,180
of 8,165 outputs
Outputs of similar age
#154,899
of 478,505 outputs
Outputs of similar age from Lecture notes in computer science
#14
of 25 outputs
Altmetric has tracked 25,605,018 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 8,165 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one has gotten more attention than average, scoring higher than 72% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 478,505 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.
We're also able to compare this research output to 25 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.