Paper Info
Title
Characterization Research On I/O Improvements Targeting Disc And Hpc Applications.
Abstract
Improvements in I/O architectures are becoming increasingly required nowadays. This is an essential point to complex and data intensive scalable applications. Data-Intensive Scalable Computing (DISC) and High-Performance Computing (HPC) applications frequently need to transfer data between storage resources. In the scientific and industrial fields, the storage component is a key element, because usually those applications employ a huge amount of data. Therefore, the performance of these applications commonly depends on some factors related to time spent in execution of the I/O operations. However, researchers, through their works, are proposing different approaches targeting improvements on the storage layer, thus, reducing the gap between processing and storage. Some solutions combine different hardware technologies to achieve high performance, while others develop solutions on the software layer. This paper aims to present a characterization model for classifying research works on I/O performance improvements for large scale computing facilities. Analysis over 36 different scenarios using a synthetic I/O benchmark demonstrates how the latency parameter behaves when performing different I/O operations using distinct storage technologies and approaches.
Year
DOI
Venue
2020
10.1109/IECON43393.2020.9255087
IECON 2020: THE 46TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY
Keywords
DocType
ISSN
DISC, HPC, I/O Performance, Characterization, Storage Systems
Conference
1553-572X
Citations 
PageRank 
References 
0
0.34
0
Authors
7
Name
Order
Citations
PageRank
Laércio Pioli100.34
Eduardo Camilo Inacio2175.28
Douglas D. J. de Macedo36215.65
Victor StröEle42911.27
José Maria N. David5134.14
Jean-François Méhaut600.34
Mario A. R. Dantas76925.60