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1 Slides presented by Hank Childs at the VACET/SDM workshop at the SDM Center All-Hands Meeting. November 26, 2007 Snoqualmie, Wa Work performed under.

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Presentation on theme: "1 Slides presented by Hank Childs at the VACET/SDM workshop at the SDM Center All-Hands Meeting. November 26, 2007 Snoqualmie, Wa Work performed under."— Presentation transcript:

1 1 Slides presented by Hank Childs at the VACET/SDM workshop at the SDM Center All-Hands Meeting. November 26, 2007 Snoqualmie, Wa Work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under contract W-7405-Eng-48. Lawrence Livermore National Laboratory, P.O. Box 808, Livermore, Ca, Work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under contract W-7405-Eng-48. Lawrence Livermore National Laboratory, P.O. Box 808, Livermore, Ca, This is presentation UCRL-PRES

2 2 Overview Our mission: form a plan to more efficiently visualize and analyze data using FastBit My slides: –What is VisIt –Describe why VisIt’s architecture is well positioned for FastBit –Introduce known unknowns for group discussion John’s slides (if necessary) –HDF5 + FastBit

3 3 VisIt is a richly featured, turnkey application VisIt is an open source, end user visualization and analysis tool for simulated and experimental data –Used by: physicists, engineers, code developers, vis experts –>20 simulation codes & 300 users at LLNL, >50K downloads on web Terribly named!! Made for: –Data Exploration –Quantitative Analysis –Debugging –Comparative Analysis –Presentations VisIt Overview

4 4 What are the types of postprocessing needs being considered by VisIt? Data Exploration Visual Debugging Quantitative Analysis Presentations = ? Comparative Analysis Postprocessing goes beyond visualization. Overview of postprocessing needs

5 5 Lawrence Livermore National Laboratory, P.O. Box 808, Livermore, Ca, A 27B element Rayleigh-Taylor Instability (MIRANDA, BG/L)

6 6 VisIt employs a parallelized client-server architecture. Client-server observations: –Good for remote visualization –Leverages available resources –Scales well –No need to move data Additional design considerations: –Plugins –Multiple UIs: GUI (Qt), CLI (Python), more… –Third party libraries: VTK, Qt, Python, Mesa, +I/O libs remote machine Parallel vis resources User data localhost – Linux, Windows, Mac Graphics Hardware The principal architectural decisions – client/server, VTK, Qt, Python, plugins, etc – were put in place 6 years ago … VisIt has been building on that base ever since. The principal architectural decisions – client/server, VTK, Qt, Python, plugins, etc – were put in place 6 years ago … VisIt has been building on that base ever since. VisIt Overview

7 7 Parallelization covers data input, data processing, and rendering. Identical data flow networks on each processor. –Networks differentiated by portion of data they operate on. –“Scattered/gather” No distribution (i.e. scatter), because scatter is done with choice of what data to read. Gather: done when rendering P1 P2P3P0 I/O Parallel Simulation Code P0 P1 P3 P2 Data Input Parallelized Server Proc 0Proc 1Proc 2 Data Processing Rendering

8 8 Contracts are an extension to the standard data flow network design. Work is performed by a pipeline A pipeline consists of data objects and components (sources, filters, and sinks) File Reader (Source) Slice Filter Contour Filter Renderer (Sink) V0V1 V2Exec Update Execute Data Flow Networks “101”: Extension: Contracts are coupled with the Update phase Pipeline execution begins with a “pull”, which starts Update phase Data flows from component to component during the Execute phase

9 9 Operating on Optimal Subset of Data … Slice Filter V( I ) … V( I+1 ) Filter (base class) (inheritance) Slice Filter Hundreds of others Contract * SliceFilter::ModifyContract (Contract *V(I)) {... return V(I+1); } 1)Get meta-data 2)Determine domains that intersect slice 3)Restrict list of domains to process in V( I +1)

10 10 Operating on Optimal Subset of Data … Slice Filter V( I ) … V( I+1 ) 1)Get meta-data 2)Determine domains that intersect slice 3)Restrict list of domains to process in V( I +1) D3D2D1D0 D3D2D1D0

11 11 Alternate execution: instead of getting meta- data, just send constraints up the pipeline … Slice Filter V( I ) … V( I+1 ) D3D2D1D0 D3D2D1D0 Plane equation ViSUS reader D3D2D1D0 Plane equation

12 12 This mode should work for FastBit. … Threshold Filter V( I ) … V( I+1 ) D3D2D1D0 D3D2D1D0 Range Query Reader that is FastBit aware D3D2D1D0 Range Query

13 13 Where to go from here? Marching orders: construct a plan I’ve presented a simplified view: –What are the targets? (GTC?) –API (HDF5, NetCDF?) –Parallel coordinates? –Do we understand the requirements? Time handling? What kinds of queries? –Vary by domain? –Suggested discussion from Wes: Performance expectations Utilizing parallel platforms Image: Sean Ahern, ORNL

14 14 Parallel coordinates + Threshold Image: Sean Ahern, ORNL


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