Paper Info
Title
Volume rendering with data parallel visualization frameworks for emerging high performance computing architectures.
Abstract
Future exascale computing is demanding more and more parallelism from current software if peak computation rates are to be realized. However, exploiting this additional parallelism is not trivial. One approach is to identify finer grained parallelism using data parallel primitives (DPP). Visualization frameworks such as Dax and VTK-m are being developed using DPP for this purpose. Our work presents an exploratory study of how volume rendering maps to current and future super computing architectures. We implement a ray casting and cell projection volume renderer in Dax using DPP and compare their performance on three different hardware architectures. Despite the portability provided by these frameworks, we observe that additional architecture specific modifications are necessary to achieve acceptable performance on some architectures.
Year
DOI
Venue
2015
10.1145/2818517.2818546
SIGGRAPH Asia Visualization in High Performance Computing
Field
DocType
Citations 
Exascale computing,Computer architecture,Volume rendering,Supercomputer,Visualization,Computer science,Parallel computing,Data parallelism,Software portability,Cell projection,Rendering (computer graphics)
Conference
3
PageRank 
References 
Authors
0.40
9
2
Name
Order
Citations
PageRank
Hendrik A. Schroots130.40
Kwan-Liu Ma25145334.46