Abstract
We are on the threshold of a transformative change in the basic architecture of high-performance computing. The use of accelerator processors, characterized by large core counts, shared but asymmetrical memory, and heavy thread loading, is quickly becoming the norm in high performance computing. These accelerators represent significant challenges in updating our existing base of software. An intrinsic problem with this transition is a fundamental programming shift from message passing processes to much more fine thread scheduling with memory sharing. Another problem is the lack of stability in accelerator implementation; processor and compiler technology is currently changing rapidly. In this paper we describe our approach to address these two immediate problems with respect to scientific analysis and visualization algorithms. Our approach to accelerator programming forms the basis of the Dax toolkit, a framework to build data analysis and visualization algorithms applicable to exascale computing.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings - 2012 SC Companion |
| Subtitle of host publication | High Performance Computing, Networking Storage and Analysis, SCC 2012 |
| Pages | 821-826 |
| Number of pages | 6 |
| DOIs | |
| State | Published - Dec 1 2012 |
| Event | 2012 SC Companion: High Performance Computing, Networking Storage and Analysis, SCC 2012 - Salt Lake City, UT, United States Duration: Nov 10 2012 → Nov 16 2012 |
Other
| Other | 2012 SC Companion: High Performance Computing, Networking Storage and Analysis, SCC 2012 |
|---|---|
| Country | United States |
| City | Salt Lake City, UT |
| Period | 11/10/12 → 11/16/12 |
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ASJC Scopus subject areas
- Computational Theory and Mathematics
- Computer Science Applications
- Software
Cite this
Flexible analysis software for emerging architectures. / Moreland, Kenneth; King, Brad; Maynard, Robert; Ma, Kwan-Liu.
Proceedings - 2012 SC Companion: High Performance Computing, Networking Storage and Analysis, SCC 2012. 2012. p. 821-826 6495897.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Flexible analysis software for emerging architectures
AU - Moreland, Kenneth
AU - King, Brad
AU - Maynard, Robert
AU - Ma, Kwan-Liu
PY - 2012/12/1
Y1 - 2012/12/1
N2 - We are on the threshold of a transformative change in the basic architecture of high-performance computing. The use of accelerator processors, characterized by large core counts, shared but asymmetrical memory, and heavy thread loading, is quickly becoming the norm in high performance computing. These accelerators represent significant challenges in updating our existing base of software. An intrinsic problem with this transition is a fundamental programming shift from message passing processes to much more fine thread scheduling with memory sharing. Another problem is the lack of stability in accelerator implementation; processor and compiler technology is currently changing rapidly. In this paper we describe our approach to address these two immediate problems with respect to scientific analysis and visualization algorithms. Our approach to accelerator programming forms the basis of the Dax toolkit, a framework to build data analysis and visualization algorithms applicable to exascale computing.
AB - We are on the threshold of a transformative change in the basic architecture of high-performance computing. The use of accelerator processors, characterized by large core counts, shared but asymmetrical memory, and heavy thread loading, is quickly becoming the norm in high performance computing. These accelerators represent significant challenges in updating our existing base of software. An intrinsic problem with this transition is a fundamental programming shift from message passing processes to much more fine thread scheduling with memory sharing. Another problem is the lack of stability in accelerator implementation; processor and compiler technology is currently changing rapidly. In this paper we describe our approach to address these two immediate problems with respect to scientific analysis and visualization algorithms. Our approach to accelerator programming forms the basis of the Dax toolkit, a framework to build data analysis and visualization algorithms applicable to exascale computing.
UR - http://www.scopus.com/inward/record.url?scp=84876549359&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84876549359&partnerID=8YFLogxK
U2 - 10.1109/SC.Companion.2012.115
DO - 10.1109/SC.Companion.2012.115
M3 - Conference contribution
SN - 9780769549569
SP - 821
EP - 826
BT - Proceedings - 2012 SC Companion
ER -