Network and Parallel Computing
16th IFIP WG 10.3 International Conference, NPC 2019, Hohhot, China, August 23-24, 2019, Proceedings
Published on 28. September 2019
XIV, 385 pages
978-3-030-30709-7 (ISBN)
Description
This book constitutes the proceedings of the 16th IFIP WG 10.3 International Conference on Network and Parallel Computing, NPC 2019, held in Hohhot, China, in August 2019.
The 22 full and 11 short papers presented in this volume were carefully reviewed and selected from 107 submissions. They were organized in topical sections named: graph computing; NOC and networks; neural networks; big data and cloud; HPC; emerging topics; memory and file system.
The 22 full and 11 short papers presented in this volume were carefully reviewed and selected from 107 submissions. They were organized in topical sections named: graph computing; NOC and networks; neural networks; big data and cloud; HPC; emerging topics; memory and file system.
More details
Series
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Product notice
Reflowable
Illustrations
XIV, 385 p. 191 illus., 131 illus. in color.
File size
24,73 MB
ISBN-13
978-3-030-30709-7 (9783030307097)
DOI
10.1007/978-3-030-30709-7
Schweitzer Classification
Other editions
Additional editions
Xiaoxin Tang | Quan Chen | Pradip Bose
Network and Parallel Computing
16th IFIP WG 10.3 International Conference, NPC 2019, Hohhot, China, August 23-24, 2019, Proceedings
Book
09/2019
Springer
€53.49
Shipment within 7-9 days
Content
Graph Computing.- GraphScSh: Efficient I/O Scheduling and Graph Sharing for Concurrent Graph Processing.- NOC and Networks.- KLSAT: An Application Mapping Algorithm Based on Kernighan-Lin Partition and Simulated Annealing for a Specific WK-recursive NoC Architecture.- Modeling and Analysis of the Latency-based Congestion Control Algorithm DX.- Distributed Quality-aware Resource Allocation for Video Transmission in Wireless Networks.- Neural Networks.- PRTSM: hardware data arrangement mechanisms for convolutional layer computation on the systolic array.- PParabel: Parallel Partitioned Label Trees for Extreme Classification.- Parking Behavior Analysis and Prediction.- Big data+Cloud.- ASTracer: An Efficient Tracing Tool for HDFS with Adaptive Sampling.- BGElasor: Elastic-Scaling Framework for Distributed streaming Processing with Deep Neural Network.- High Performance Continuous Query System for Streaming Data.- DDP-B: A Distributed Dynamic Parallel Framework for Meta-genomics Binary Similarity.- Optimal Resource Allocation through Joint VM Selection and Placement in Private Clouds.- A Parallel Multi-Keyword Top-k Search Scheme over Encrypted Cloud Data.- N-Docker: a NVM-HDD Hybrid Docker Storage Framework to Improve Docker Performance.- HPC.- MMSR: A Multi-Model Super Resolution Framework.- HiPower: A High-performance RDMA Acceleration Solution for Distributed Transaction Processing.- Emerging topics.- LDAPRoam:A Generic Solution For Both Web-Based And Non-Web-Based Federate Access.- Characterizing Perception Module Performance and Robustness in Production-Scale Autonomous Driving System.- Memory and File System.- Spindle: A Write-Optimized NVM Cache for Journaling File System.- Two-Erasure Codes from 3-Plexes.- Deep Fusion: A Software Scheduling Method for Memory Access Optimization.- Optimizing Data Placement on Hierarchical Storage Architecture via Machine Learning.- Short Papers.- I/O Optimizations Based on Workload Characteristics for Parallel File System.- Energy Consumption of IT System in Cloud Data Center: Architecture, Factors and Prediction.- Efficient Processing of Convolutional Neural Networks on SW26010.- ADMMLIB: A Scalable Distributed Machine Learning Library based on ADMM.- Energy-Aware Resource Scheduling with Fault-Tolerance in Edge Computing.- DIN: A Bio-Inspired Distributed Intelligence Networking.- A DAG Refactor Based Automatic Execution Optimization Mechanism For Spark.- BTS: Balanced Task Scheduling Strategy based on Multi-resource Prediction and Allocation in Cloud Environment.- DAFL: Deep Adaptive Feature Learning for Network Anomaly Detection.- SIRM: Shift Insensitive Racetrack Main Memory.- PDRM:A Probability Distribution Based Resource Management Scheme for Batch Workloads in Heterogeneous Cluster.
