English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Various performance characteristics of distributed file systems have beenwell studied. However, the performance efficiency of distributed file systemson small-file problems with complex machine learning algorithms scenarios isnot well addressed. In addition, demands for unified storage of big dataprocessing and high-performance computing have been crucial. Hence, developinga solution combining high-performance computing and big data with sharedstorage is very important. This paper focuses on the performance efficiency ofdistributed file systems with small-file datasets. We propose an architecturecombining both high-performance computing and big data with shared storage andperform a series of experiments to investigate the performance of thesedistributed file systems. The result of the experiments confirms theapplicability of the proposed architecture in terms of complex machine learningalgorithms.

Performance of Distributed File Systems on Cloud Computing Environment: An Evaluation for Small-File Problem