Flexible analysis software for emerging architectures

Kenneth Moreland, Brad King, Robert Maynard, Kwan-Liu Ma

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations


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 languageEnglish (US)
Title of host publicationProceedings - 2012 SC Companion
Subtitle of host publicationHigh Performance Computing, Networking Storage and Analysis, SCC 2012
Number of pages6
StatePublished - Dec 1 2012
Event2012 SC Companion: High Performance Computing, Networking Storage and Analysis, SCC 2012 - Salt Lake City, UT, United States
Duration: Nov 10 2012Nov 16 2012


Other2012 SC Companion: High Performance Computing, Networking Storage and Analysis, SCC 2012
Country/TerritoryUnited States
CitySalt Lake City, UT

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Software


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