https://public.kitware.com/Wiki/index.php?title=SC10_Coprocessing_Tutorial&feed=atom&action=historySC10 Coprocessing Tutorial - Revision history2024-03-29T07:29:48ZRevision history for this page on the wikiMediaWiki 1.38.6https://public.kitware.com/Wiki/index.php?title=SC10_Coprocessing_Tutorial&diff=30445&oldid=prevKmorel at 19:24, 17 September 20102010-09-17T19:24:21Z<p></p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 19:24, 17 September 2010</td>
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<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>''In-situ'' visualization is a term for running a solver in tandem with visualization. By coupling these together we can utilize the high performance computing for post processing, and we can circumvent the bottlenecks associated with storing and retrieving data in disk storage. To simplify the integration of visualization and post processing into computational code, we present the coprocessing library provided as part of the ParaView framework. ParaView is a powerful open-source turnkey application for analyzing and visualizing large data sets in parallel. The coprocessing library provides a programmatic interface to the ParaView framework that simplifies integration with existing codes. Attendees will learn the structure of the coprocessing API and how to bind it to C, C++, <del style="font-weight: bold; text-decoration: none;">FORTRAN</del>, and Python. Attendees will also receive instructions on customizing the ParaView build to a particular code, minimizing the memory footprint, and simplifying the specification of analysis tasks via integration with the ParaView application.</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>''In-situ'' visualization is a term for running a solver in tandem with visualization. By coupling these together we can utilize the high performance computing for post processing, and we can circumvent the bottlenecks associated with storing and retrieving data in disk storage. To simplify the integration of visualization and post processing into computational code, we present the coprocessing library provided as part of the ParaView framework. ParaView is a powerful open-source turnkey application for analyzing and visualizing large data sets in parallel. The coprocessing library provides a programmatic interface to the ParaView framework that simplifies integration with existing codes. Attendees will learn the structure of the coprocessing API and how to bind it to C, C++, <ins style="font-weight: bold; text-decoration: none;">Fortran</ins>, and Python. Attendees will also receive instructions on customizing the ParaView build to a particular code, minimizing the memory footprint, and simplifying the specification of analysis tasks via integration with the ParaView application.</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br/></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br/></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>This tutorial is being held on the afternoon of Sunday, November 14 as part of the [http://sc10.supercomputing.org/ Supercomputing 2010 Conference]. See the [http://sc10.supercomputing.org/schedule/event_detail.php?evid=tut110 Supercomputing tutorial page] for more information on the time, the location, and to register (be sure to register for the Sunday tutorials).</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>This tutorial is being held on the afternoon of Sunday, November 14 as part of the [http://sc10.supercomputing.org/ Supercomputing 2010 Conference]. See the [http://sc10.supercomputing.org/schedule/event_detail.php?evid=tut110 Supercomputing tutorial page] for more information on the time, the location, and to register (be sure to register for the Sunday tutorials).</div></td></tr>
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</table>Kmorelhttps://public.kitware.com/Wiki/index.php?title=SC10_Coprocessing_Tutorial&diff=26606&oldid=prevKmorel at 18:52, 5 August 20102010-08-05T18:52:38Z<p></p>
<table style="background-color: #fff; color: #202122;" data-mw="interface">
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 18:52, 5 August 2010</td>
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<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>In-situ visualization is a term for running a solver in tandem with visualization. By coupling these together we can utilize the high performance computing for post processing, and we can circumvent the bottlenecks associated with storing and retrieving data in disk storage. To simplify the integration of visualization and post processing into computational code, we present the coprocessing library provided as part of the ParaView framework. ParaView is a powerful open-source turnkey application for analyzing and visualizing large data sets in parallel. The coprocessing library provides a programmatic interface to the ParaView framework that simplifies integration with existing codes. Attendees will learn the structure of the coprocessing API and how to bind it to C, C++, FORTRAN, and Python. Attendees will also receive instructions on customizing the ParaView build to a particular code, minimizing the memory footprint, and simplifying the specification of analysis tasks via integration with the ParaView application.</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">''</ins>In-situ<ins style="font-weight: bold; text-decoration: none;">'' </ins>visualization is a term for running a solver in tandem with visualization. By coupling these together we can utilize the high performance computing for post processing, and we can circumvent the bottlenecks associated with storing and retrieving data in disk storage. To simplify the integration of visualization and post processing into computational code, we present the coprocessing library provided as part of the ParaView framework. ParaView is a powerful open-source turnkey application for analyzing and visualizing large data sets in parallel. The coprocessing library provides a programmatic interface to the ParaView framework that simplifies integration with existing codes. Attendees will learn the structure of the coprocessing API and how to bind it to C, C++, FORTRAN, and Python. Attendees will also receive instructions on customizing the ParaView build to a particular code, minimizing the memory footprint, and simplifying the specification of analysis tasks via integration with the ParaView application.</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br/></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br/></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>This tutorial is being held on the afternoon of Sunday, November 14 as part of the [http://sc10.supercomputing.org/ Supercomputing 2010 Conference]. See the [http://sc10.supercomputing.org/schedule/event_detail.php?evid=tut110 Supercomputing tutorial page] for more information on the time, the location, and to register.</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>This tutorial is being held on the afternoon of Sunday, November 14 as part of the [http://sc10.supercomputing.org/ Supercomputing 2010 Conference]. See the [http://sc10.supercomputing.org/schedule/event_detail.php?evid=tut110 Supercomputing tutorial page] for more information on the time, the location, and to register <ins style="font-weight: bold; text-decoration: none;">(be sure to register for the Sunday tutorials)</ins>.</div></td></tr>
</table>Kmorelhttps://public.kitware.com/Wiki/index.php?title=SC10_Coprocessing_Tutorial&diff=26604&oldid=prevKmorel: Created page with 'In-situ visualization is a term for running a solver in tandem with visualization. By coupling these together we can utilize the high performance computing for post processing, a…'2010-08-05T18:42:27Z<p>Created page with 'In-situ visualization is a term for running a solver in tandem with visualization. By coupling these together we can utilize the high performance computing for post processing, a…'</p>
<p><b>New page</b></p><div>In-situ visualization is a term for running a solver in tandem with visualization. By coupling these together we can utilize the high performance computing for post processing, and we can circumvent the bottlenecks associated with storing and retrieving data in disk storage. To simplify the integration of visualization and post processing into computational code, we present the coprocessing library provided as part of the ParaView framework. ParaView is a powerful open-source turnkey application for analyzing and visualizing large data sets in parallel. The coprocessing library provides a programmatic interface to the ParaView framework that simplifies integration with existing codes. Attendees will learn the structure of the coprocessing API and how to bind it to C, C++, FORTRAN, and Python. Attendees will also receive instructions on customizing the ParaView build to a particular code, minimizing the memory footprint, and simplifying the specification of analysis tasks via integration with the ParaView application.<br />
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This tutorial is being held on the afternoon of Sunday, November 14 as part of the [http://sc10.supercomputing.org/ Supercomputing 2010 Conference]. See the [http://sc10.supercomputing.org/schedule/event_detail.php?evid=tut110 Supercomputing tutorial page] for more information on the time, the location, and to register.</div>Kmorel