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.
| Original language | English (US) |
|---|---|
| Title of host publication | SIGGRAPH Asia 2015 Visualization in High Performance Computing, SA 2015 |
| Publisher | Association for Computing Machinery, Inc |
| ISBN (Electronic) | 9781450339292 |
| DOIs | |
| State | Published - Nov 2 2015 |
| Event | SIGGRAPH Asia, SA 2015 - Kobe, Japan Duration: Nov 2 2015 → Nov 6 2015 |
Other
| Other | SIGGRAPH Asia, SA 2015 |
|---|---|
| Country | Japan |
| City | Kobe |
| Period | 11/2/15 → 11/6/15 |
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Keywords
- Data parallel primitives
- Exascale computing
- Many integrated core
- Volume rendering
ASJC Scopus subject areas
- Computer Graphics and Computer-Aided Design
- Computer Vision and Pattern Recognition
- Human-Computer Interaction
Cite this
Volume rendering with data parallel visualization frameworks for emerging high performance computing architectures. / Schroots, Hendrik A.; Ma, Kwan Liu.
SIGGRAPH Asia 2015 Visualization in High Performance Computing, SA 2015. Association for Computing Machinery, Inc, 2015. 3.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Volume rendering with data parallel visualization frameworks for emerging high performance computing architectures
AU - Schroots, Hendrik A.
AU - Ma, Kwan Liu
PY - 2015/11/2
Y1 - 2015/11/2
N2 - 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.
AB - 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.
KW - Data parallel primitives
KW - Exascale computing
KW - Many integrated core
KW - Volume rendering
UR - http://www.scopus.com/inward/record.url?scp=84959496524&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84959496524&partnerID=8YFLogxK
U2 - 10.1145/2818517.2818546
DO - 10.1145/2818517.2818546
M3 - Conference contribution
AN - SCOPUS:84959496524
BT - SIGGRAPH Asia 2015 Visualization in High Performance Computing, SA 2015
PB - Association for Computing Machinery, Inc
ER -