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oai:www.ideals.illinois.edu:2142/44414 2023-07-11 col_2142_5131 col_2142_10761 com_2142_5130 com_2142_10755 com_2142_234

Snir, Marc Wang, Shaowen Behzad, Babak 2013-05-24T22:15:18Z 2013-05-24T22:15:18Z 2015-05-24T10:01:23Z 2013-05 2013-05-24T22:15:18Z 2013-05 Reading and writing big data is increasingly becoming a major bottleneck of using high-performance computing systems as we are heading towards the Exascale era. An unprecedented amount of data is being produced everyday by different sources. On the other hand, the computation power of HPC systems is getting scaled to hundreds of thousands cores. However, for an application to be able to utilize this much data and computation power, using I/O effectively is a must. One of the fields dealing with huge amount of data is geographic information science. In this thesis, we have implemented a parallel I/O library specialized for spatial data analysis in GIScience, capable of treating different I/O patterns such as Row-Wise, Column-Wise and Block-Wise I/O. We then establish an auto-tuning framework for finding optimal parallel I/O configurations. This auto-tuning framework is based on genetic algorithm and works on a range of configurations from the parallel file system all the way up to spatial data-analysis applications. The results and findings of a set of I/O intensive experiments executed on large HPC systems are also presented to demonstrate the effectiveness of the framework. Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2013-04-22T18:10:42Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 1 Behzad_Babak.pdf: 980892 bytes, checksum: bd69cf9666973f6cf0c0c0cb3003c952 (MD5) Made available in DSpace on 2013-05-24T22:15:18Z (GMT). No. of bitstreams: 2 Babak_Behzad.pdf: 980892 bytes, checksum: bd69cf9666973f6cf0c0c0cb3003c952 (MD5) license.txt: 4061 bytes, checksum: fa3c827969ff68c5a2ca597a38d56984 (MD5) Restriction data tranferred 2014-07-01T11:35:39-05:00 Original Data Group with Access UIUC Users [automated] Release Date: 2015-05-24 17:18:31 UTC Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system Item marked as restricted to the 'UIUC Users [automated]' Group (id=2) by Seth Robbins (srobbins@illinois.edu) on 2013-05-24T22:18:40Z Item is restricted until 2015-05-24T22:18:31Z U of I Only Restriction Lifted for Item 44387 on 2015-05-24T10:01:23Z. http://hdl.handle.net/2142/44414 en Copyright 2013 Babak Behzad Parallel I/O GIScience High Performance Computing (HPC) Spatial Applications Auto-Tuning Auto-tuned optimized parallel I/O for GIScience and spatial applications text Computer Science 1434 Computer Science 0112 University of Illinois at Urbana-Champaign Thesis M.S. PHD:Computer Science -UIUC 10KS0112PHD