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Produktinformationen "Network and Parallel Computing"

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.

Untertitel
16th IFIP WG 10.3 International Conference, NPC 2019, Hohhot, China, August 23-24, 2019, Proceedings

H | B | T | Gramm
235 mm | 155 mm | 22 mm | 0.604 kg

Erscheinungsjahr
2019

FSK
0

Ausgabe
Taschenbuch

Verlag
Springer

ISBN-10
3030307085

ISBN-13
9783030307080

Weitere Mitwirkende
Gaudiot, Jean-Luc | Zheng, Weiming | Chen, Quan | Tang, Xiaoxin | Bose, Pradip

Sprache
Englisch

Seitenanzahl
400

Themen
Künstliche Intelligenz KI, Angewandte Informatik, Künstliche Intelligenz KI, Numerische Mathematik, Betriebssysteme, Computerhardware

Verantwortliche Person gemäß Art. 16 GPSR
Springer Nature Customer Service Center GmbH, Europaplatz 3, 69115, Heidelberg, DE, ProductSafety@springernature.com

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