1 / 14

Collaborative Scientific Data Visualization Framework

SV2. See me at the NPACI/Alliance booth for a live demo. See me at the CRPC booth for a live demo. Collaborative Scientific Data Visualization Framework. Ki, Klasky , Fox Syracuse University (NPAC) scott@npac.syr.edu. SV2 Features. Java2D (promise for fast 2D rendering/animations).

yetta-terrell
Download Presentation

Collaborative Scientific Data Visualization Framework

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. SV2 See me at the NPACI/Alliance booth for a live demo See me at the CRPC booth for a live demo Collaborative Scientific Data Visualization Framework Ki, Klasky, Fox Syracuse University (NPAC) scott@npac.syr.edu

  2. SV2 Features • Java2D (promise for fast 2D rendering/animations). • Java3D (promise for fast 3D graphics on all platforms). • Voluminous data server (compression schemes to allow for fast data transfers). • Multiplexing (efficient collaboration data server along with TANGO)

  3. OBJECTIVE • Our goal of this collaborative system is to use recent computing technology, Java, to build a multi-user collaborative scientific design and analysis environments which can run on all platforms. • The objective was to develop the scientific software environment where multiple users can create, share, manipulate, analyze, simulate, and visualize complex data sets over a heterogeneous network of PC’s, workstations and supercomputers.

  4. Scivis->SV2 • Our SV2 research and design is based on the success of Scivis. Scivis is a collaborative scientific data visualization package written in Java. • Scivis allows users to visualize their data, which is piped in via sockets. • Although Scivis has been widely used in the “Binary Black Hole Grand Challenge”, it still had major limitations. • One of the most common complaints against Scivis was that users could only collaborate with other Scivis users. • SV2 is being designed such that users of Scivis3d (a Java3D version of Scivis), AVS, & VRML can collaborate together.

  5. SV2 System Architecture Local Client Local Client Data Viewer 1 Data Viewer 1 Data Viewer 2 Data Viewer 2 Client Manager Client Manager Collaboration Tool Geometry Engine Filter Engine SV2 Server

  6. Sample Screen Dump Surface & Contour Plots Raytracing Rotations of raytracing Isosurfaces X,y animations

  7. USE JNI to incorporate quality visualization code. • The Stanford Volpack routines for raytracing. (written in C). • Isosurface rouintes with • We provide API’s too incorporate such routines into the SV2 server with minimal pain. • Eventually we will provide API’s to incorporate VTK filters too. (C++ routines) • Users can customize routines for their own use.

  8. Future Work • Filter/Map creator, users can hook filters together, and create new API’s for those maps. Mysv3d(name,time,g3d,n) Myray(name,time,g3d,n) Downsize Downsize VTK:raytrace Smooth Isosurface Compression decimation Compression

  9. SV2-Client Window • Data is sent from simulations, or files, to the SV2 server. • Data from the SV2 server is stored (in memory, and on disk). • Data file headers are sent to SV2-clients. • Clients can request to visualize the data. • To keep support for Scivis alive, we allow users to pipe data directly to SV2 clients.

  10. SV2: Issues for rendering • For enhanced interactively, the image should be refined progressively as the data comes in from the remote server. • Image quality must be controlled as a function of the network's load and client's hardware setup. • In order to store and transmit large scale data sets,compression schemes have to be utilized. • In order to avoid full decompression, a sophisticated rendering method should carry out computations in compression domains at the client side. • For the above two issues, wavelet compression is an obvious choice in our system.

  11. SV2: More issues • With upcoming network computers, the capabilities of a local client might be reduced significantly. • A data representation and rendering method is required, which will avoid the full expansion of the data in the clients memory. • Java-3D allows programmers to specify geometry using a binary geometry compression format. This compression format is used with APIs, and can be used both as a run-time in-memory format for describing geometry, as well as a storage and network format.

  12. SV2: Visualization • Once Data-headers are on the client, users can select different methods to visualize the data. • For example, for a 3D data set, users can select either isosurface or raytracing. • Users can also select methods to filter this data, such as triangle decimation. • Clients request data from the server, the server performs the appropriate filter(s), and then sends back the geometry (or image, or actual x,(y,(z)) data) back to the client. • The client (Scivis3D,VRML(not yet implemented)) visualizes the data.

More Related