Title : 
In situ fragment detection at scale
         
        
        
            Author_Institution : 
Sandia National Laboratories
         
        
        
        
        
        
            Abstract : 
We explore the problem of characterizing fragments using Par-aView in situ with an explosion simulation. By running in situ we can see a much higher temporal view of the data as well as potentially compress the output to only those statistics about fragments we care about. However, the fragment finding must be able to scale as well as the simulation. In order to achieve the necessary scales, we borrow operations the simulation is already doing and take advantage of them within Para View, demonstrating the resulting improvement in scaling performance.
         
        
            Keywords : 
data analysis; data visualisation; digital simulation; Par-aView; data temporal view; explosion simulation; fragment characterization; in situ fragment detection; scaling performance; Adaptation models; Algorithm design and analysis; Analytical models; Data models; Materials; Shape; Surface reconstruction; coprocessing; in situ; scaling; simulation;
         
        
        
        
            Conference_Titel : 
Large Data Analysis and Visualization (LDAV), 2012 IEEE Symposium on
         
        
            Conference_Location : 
Seattle, WA
         
        
            Print_ISBN : 
978-1-4673-4732-7
         
        
        
            DOI : 
10.1109/LDAV.2012.6378983