Title
Visdsi: Locality Aware I/O Solution For Large Scale Data Visualization
Keywords
Data Intensive; Distributed Computing; I/O Bandwidth; Parallel Computing; Scientific Visualization
Abstract
The computational science community is approaching petascale level simulations that will produce massive amount of datasets. While the computational power of supercomputers keep increasing, the I/O systems have not kept pace, resulting in a significant performance bottle neck. We propose a solution, VisDSI, to address the problem by 1) using traditional high performance clusters with disks directly attached within each node, 2) deploying a data-intensive distributed file system on the cluster, and 3) developing a POSIX-compatible I/O layer to enable the traditional visualization applications to smoothly port to this new platform as well as to provide a new I/Osemantic of retrieving the data location with respect to the POSIX standards. In particular, VisDSI guarantees the colocated compute and data storage by introducing a scheduling of work assignments to nodes with local copies of needed data. Compared with the original visualization application, our solution runs at least 10 times faster. © 2013 IEEE.
Publication Date
1-1-2013
Publication Title
Proceedings - 2013 IEEE/ACM 6th International Conference on Utility and Cloud Computing, UCC 2013
Number of Pages
278-281
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/UCC.2013.60
Copyright Status
Unknown
Socpus ID
84901660289 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84901660289
STARS Citation
Ng, Willie; Yu, Yang; Zhu, Yongqing; Wang, Jun; and Juniarto, Samsudin, "Visdsi: Locality Aware I/O Solution For Large Scale Data Visualization" (2013). Scopus Export 2010-2014. 7592.
https://stars.library.ucf.edu/scopus2010/7592