TY - JOUR A1 - Allen, Gabrielle A1 - Davis, K. A1 - Goodale, Tom A1 - Hutanu, Andrei A1 - Kaiser, Hartmut A1 - Kielmann, Thilo A1 - Merzky, Andre A1 - Nieuwpoort, R. A1 - Reinefeld, Alexander A1 - Schintke, Florian A1 - Schütt, Thorsten A1 - Seidel, Edward A1 - Ullmer, Brygg T1 - The Grid Application Toolkit: Toward Generic and Easy Appliction Programming Interfaces for the Grid JF - Procceedings of the IEEE Y1 - 2005 U6 - https://doi.org/10.1109/JPROC.2004.842755 VL - 93 IS - 3 SP - 534 EP - 550 PB - IEEE Computer Society Press ER - TY - CHAP A1 - Hege, Hans-Christian A1 - Hutanu, Andrei A1 - Kähler, Ralf A1 - Merzky, André A1 - Radke, Thomas A1 - Seidel, Edward A1 - Ullmer, Brygg T1 - Progressive Retrieval and Hierarchical Visualization of Large Remote Data T2 - Proceedings of the 2003 Workshop on Adaptive Grid Middleware Y1 - 2003 SP - 60 EP - 72 ER - TY - GEN A1 - Hege, Hans-Christian A1 - Hutanu, Andrei A1 - Kähler, Ralf A1 - Merzky, André A1 - Radke, Thomas A1 - Seidel, Edward A1 - Ullmer, Brygg T1 - Progressive Retrieval and Hierarchical Visualization of Large Remote Data N2 - \noindent The size of data sets produced on remote supercomputer facilities frequently exceeds the processing capabilities of local visualization workstations. This phenomenon increasingly limits scientists when analyzing results of large-scale scientific simulations. That problem gets even more prominent in scientific collaborations, spanning large virtual organizations, working on common shared sets of data distributed in Grid environments. In the visualization community, this problem is addressed by distributing the visualization pipeline. In particular, early stages of the pipeline are executed on resources closer to the initial (remote) locations of the data sets. \noindent This paper presents an efficient technique for placing the first two stages of the visualization pipeline (data access and data filter) onto remote resources. This is realized by exploiting the ``extended retrieve'' feature of GridFTP for flexible, high performance access to very large HDF5 files. We reduce the number of network transactions for filtering operations by utilizing a server side data processing plugin, and hence reduce latency overhead compared to GridFTP partial file access. The paper further describes the application of hierarchical rendering techniques on remote uniform data sets, which make use of the remote data filtering stage. T3 - ZIB-Report - 03-40 KW - remote data access KW - large files KW - visualization pipeline KW - hdf5 KW - grid Y1 - 2003 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-7623 ER - TY - CHAP A1 - Ullmer, Brygg A1 - Hutanu, Andrei A1 - Benger, Werner A1 - Hege, Hans-Christian ED - Staadt, Oliver T1 - Emerging Tangible Interfaces for Facilitating Collaborative Immersive Visualizations T2 - Proc. of NSF Lake Tahoe Workshop on Collaborative Virtual Reality and Visualization (extended abstract) Y1 - 2003 ER - TY - JOUR A1 - Hutanu, Andrei A1 - Allen, Gabrielle A1 - Beck, Stephen A1 - Holub, Petr A1 - Kaiser, Hartmut A1 - Kulshrestha, Archit A1 - Liska, Milos A1 - MacLaren, Jon A1 - Matyska, Ludek A1 - Paruchuri, Ravi A1 - Prohaska, Steffen A1 - Seidel, Edward A1 - Ullmer, Brygg A1 - Venkataraman, Shalini T1 - Distributed and collaborative visualization of large data sets using high-speed networks JF - Future Generation Comp. Syst Y1 - 2006 U6 - https://doi.org/10.1016/j.future.2006.03.026 VL - 22(8) SP - 1004 EP - 1010 ER -