Editorial for the special issue on high performance distributed computing

With the advent of the Big Data era, the demand for storing, processing, and analyzing this vast and growing amount of data has emerged in the market. Since a single node cannot cope with its complexity requirements, high-performance systems typically operate in a distributed environment. [...]the d...

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Veröffentlicht in:CCF transactions on high performance computing (Online) Jg. 3; H. 2; S. 127 - 128
Hauptverfasser: Guo, Minyi, Chen, Guihai, Liao, Xiaofei, Zheng, Long
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Singapore Springer Singapore 01.06.2021
Springer Nature B.V
Schlagworte:
3. High Performance Distributed Computing
Artificial neural networks
Big Data
Computer Hardware
Computer networks
Computer Science
Computer Systems Organization and Communication Networks
Distributed processing
Editorial
Fault tolerance
Neural networks
Resource allocation
Resource management
Training
ISSN:2524-4922, 2524-4930
Online-Zugang:Volltext
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Zusammenfassung:With the advent of the Big Data era, the demand for storing, processing, and analyzing this vast and growing amount of data has emerged in the market. Since a single node cannot cope with its complexity requirements, high-performance systems typically operate in a distributed environment. [...]the diverse development of hardware platforms, the spurt of data growth, and the rapid changes in applications are increasingly challenging resource management, energy efficiency, performance tuning, scalability, and fault tolerance. The paper written by Qiang Qi et al. proposes a network bandwidth resource allocation strategy for distributed deep neural network (DNN) training tasks to mitigate the network resource contention and alleviate the performance variation of training jobs.
Bibliographie:SourceType-Scholarly Journals-1
content type line 14
ObjectType-Editorial-2
ObjectType-Commentary-1
ISSN:2524-4922
2524-4930
DOI:10.1007/s42514-021-00068-7