collaborative scientific data visualization framework
DESCRIPTION
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) [email protected]. SV2 Features. Java2D (promise for fast 2D rendering/animations). - PowerPoint PPT PresentationTRANSCRIPT
Collaborative Scientific Data Visualization
FrameworkKi, Klasky, Fox
Syracuse University (NPAC)[email protected]
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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)
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.
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.
SV2 System ArchitectureLocal Client
Client Manager
Data Viewer 1
Data Viewer 2
Local Client
Client Manager
Data Viewer 1
Data Viewer 2
CollaborationTool
Geometry Engine
Filter Engine
SV2 Server
Sample Screen Dump
RaytracingRotations of raytracing Surface & Contour Plots
IsosurfacesX,y animations
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.
Future Work• Filter/Map creator, users can hook filters together, and create new API’s for
those maps.
Compression
Downsize
Smooth
Isosurface
decimation
Mysv3d(name,time,g3d,n)
Downsize
VTK:raytrace
Compression
Myray(name,time,g3d,n)
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.
• 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.
SV2: Issues for rendering
• 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.
SV2: More issues
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.