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This presentation highlights the significant applications of grid computing in environmental science, particularly climate research, as well as in biology for genomic studies. It showcases how various institutions utilize grid networks to archive, access, and analyze vast data sets—such as climate data visualizing sea ice extent and surface temperatures. Additionally, it discusses the computational challenges in sequence alignment and disease research, underscoring the need for efficient algorithms and collaborative efforts using grid technologies.
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UMICH GMU UAH UARK UVA GPN USC DUKE SC TTU GaTech TACC UAB GSU Tulane LSU SURAGrid UNC-C also a member See presentation on Nov 22, 2005 from SURAGrid team.
Earth Science Gridhttps://www.earthsystemgrid.org/ • Producing, archiving, and providing access to climate data that informs research on global climate change. This image displays data from ESG and shows sea ice extent (white/gray), sea ice motion, sea surface temperatures (colors), and atmospheric sea level pressure (contours). ESG uses Globus software for security, data movement, and system monitoring. Image provided by UCAR.
http://www.qub.ac.uk/escience/dev/article.php?tag=genegrid_summaryhttp://www.qub.ac.uk/escience/dev/article.php?tag=genegrid_summary
Sequence alignment problem • Sequences used to find biologically meaning relationships among organisms • Evolutionary information • Determining diseases, causes, cures • Finding out information about proteins • Problem especially compute intensive for long sequences • Needleman and Wunsch (1970) - optimal global alignment • Smith and Waterman (1981) - optimal local alignment • Taylor (1987) - multiple sequence alignment by pairwise alignment • BLAST trades off optimal results for faster computation • Challenge - achieve optimal results without sacrificing speed
https://www.ud.com/company/news/files/2004_11_nytimes.pdf#search='grid%20computing%20genes'https://www.ud.com/company/news/files/2004_11_nytimes.pdf#search='grid%20computing%20genes'
http://www.technologyreview.com/articles/05/02/wo/wo_hoffman020105.asphttp://www.technologyreview.com/articles/05/02/wo/wo_hoffman020105.asp
Modeling Black Holes Cactuscode.org • Einstein’s equations of General Relativity: Gab = 0 • One of the most complex set of equations in physics • Mixed hyperbolic-elliptic initial value problem • 3 Dimensional, multiple scales • 12 or more equations, with thousands of terms • Require diverse distributed collaborations & many large scale simulations: • Parallelization, optimization • Parallel IO, data management, viz • Checkpointing, steering, interaction t=100 t=0
Using Distributed Experimental Equipment in a Grid Infrastructure
http://www.dma.unina.it/~murli/GridSummerSchool2005/repository/thursday-21/gridschool-present-050716.pdfhttp://www.dma.unina.it/~murli/GridSummerSchool2005/repository/thursday-21/gridschool-present-050716.pdf