VTK-m: Accelerating the Visualization Toolkit for Massively Threaded Architectures

Kenneth Moreland, Christopher Sewell, William Usher, Li Ta Lo, Jeremy Meredith, David Pugmire, James Kress, Hendrik Schroots, Kwan-Liu Ma, Hank Childs, Matthew Larsen, Chun Ming Chen, Robert Maynard, Berk Geveci

Research output: Contribution to journalArticle

38 Citations (Scopus)

Abstract

One of the most critical challenges for high-performance computing (HPC) scientific visualization is execution on massively threaded processors. Of the many fundamental changes we are seeing in HPC systems, one of the most profound is a reliance on new processor types optimized for execution bandwidth over latency hiding. Our current production scientific visualization software is not designed for these new types of architectures. To address this issue, the VTK-m framework serves as a container for algorithms, provides flexible data representation, and simplifies the design of visualization algorithms on new and future computer architecture.

Original languageEnglish (US)
Article number7466740
Pages (from-to)48-58
Number of pages11
JournalIEEE Computer Graphics and Applications
Volume36
Issue number3
DOIs
StatePublished - May 1 2016

Fingerprint

Data visualization
Visualization
Computer architecture
Containers
Bandwidth

Keywords

  • algorithmic structures
  • computer graphics
  • high-performance computing
  • massively threaded processors
  • parallel algorithms
  • visualization software
  • VTK-m framework

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design

Cite this

Moreland, K., Sewell, C., Usher, W., Lo, L. T., Meredith, J., Pugmire, D., ... Geveci, B. (2016). VTK-m: Accelerating the Visualization Toolkit for Massively Threaded Architectures. IEEE Computer Graphics and Applications, 36(3), 48-58. [7466740]. https://doi.org/10.1109/MCG.2016.48

VTK-m : Accelerating the Visualization Toolkit for Massively Threaded Architectures. / Moreland, Kenneth; Sewell, Christopher; Usher, William; Lo, Li Ta; Meredith, Jeremy; Pugmire, David; Kress, James; Schroots, Hendrik; Ma, Kwan-Liu; Childs, Hank; Larsen, Matthew; Chen, Chun Ming; Maynard, Robert; Geveci, Berk.

In: IEEE Computer Graphics and Applications, Vol. 36, No. 3, 7466740, 01.05.2016, p. 48-58.

Research output: Contribution to journalArticle

Moreland, K, Sewell, C, Usher, W, Lo, LT, Meredith, J, Pugmire, D, Kress, J, Schroots, H, Ma, K-L, Childs, H, Larsen, M, Chen, CM, Maynard, R & Geveci, B 2016, 'VTK-m: Accelerating the Visualization Toolkit for Massively Threaded Architectures', IEEE Computer Graphics and Applications, vol. 36, no. 3, 7466740, pp. 48-58. https://doi.org/10.1109/MCG.2016.48
Moreland K, Sewell C, Usher W, Lo LT, Meredith J, Pugmire D et al. VTK-m: Accelerating the Visualization Toolkit for Massively Threaded Architectures. IEEE Computer Graphics and Applications. 2016 May 1;36(3):48-58. 7466740. https://doi.org/10.1109/MCG.2016.48
Moreland, Kenneth ; Sewell, Christopher ; Usher, William ; Lo, Li Ta ; Meredith, Jeremy ; Pugmire, David ; Kress, James ; Schroots, Hendrik ; Ma, Kwan-Liu ; Childs, Hank ; Larsen, Matthew ; Chen, Chun Ming ; Maynard, Robert ; Geveci, Berk. / VTK-m : Accelerating the Visualization Toolkit for Massively Threaded Architectures. In: IEEE Computer Graphics and Applications. 2016 ; Vol. 36, No. 3. pp. 48-58.
@article{5cab24c9b9e041bd8635fb8241bcbdab,
title = "VTK-m: Accelerating the Visualization Toolkit for Massively Threaded Architectures",
abstract = "One of the most critical challenges for high-performance computing (HPC) scientific visualization is execution on massively threaded processors. Of the many fundamental changes we are seeing in HPC systems, one of the most profound is a reliance on new processor types optimized for execution bandwidth over latency hiding. Our current production scientific visualization software is not designed for these new types of architectures. To address this issue, the VTK-m framework serves as a container for algorithms, provides flexible data representation, and simplifies the design of visualization algorithms on new and future computer architecture.",
keywords = "algorithmic structures, computer graphics, high-performance computing, massively threaded processors, parallel algorithms, visualization software, VTK-m framework",
author = "Kenneth Moreland and Christopher Sewell and William Usher and Lo, {Li Ta} and Jeremy Meredith and David Pugmire and James Kress and Hendrik Schroots and Kwan-Liu Ma and Hank Childs and Matthew Larsen and Chen, {Chun Ming} and Robert Maynard and Berk Geveci",
year = "2016",
month = "5",
day = "1",
doi = "10.1109/MCG.2016.48",
language = "English (US)",
volume = "36",
pages = "48--58",
journal = "IEEE Computer Graphics and Applications",
issn = "0272-1716",
publisher = "IEEE Computer Society",
number = "3",

}

TY - JOUR

T1 - VTK-m

T2 - Accelerating the Visualization Toolkit for Massively Threaded Architectures

AU - Moreland, Kenneth

AU - Sewell, Christopher

AU - Usher, William

AU - Lo, Li Ta

AU - Meredith, Jeremy

AU - Pugmire, David

AU - Kress, James

AU - Schroots, Hendrik

AU - Ma, Kwan-Liu

AU - Childs, Hank

AU - Larsen, Matthew

AU - Chen, Chun Ming

AU - Maynard, Robert

AU - Geveci, Berk

PY - 2016/5/1

Y1 - 2016/5/1

N2 - One of the most critical challenges for high-performance computing (HPC) scientific visualization is execution on massively threaded processors. Of the many fundamental changes we are seeing in HPC systems, one of the most profound is a reliance on new processor types optimized for execution bandwidth over latency hiding. Our current production scientific visualization software is not designed for these new types of architectures. To address this issue, the VTK-m framework serves as a container for algorithms, provides flexible data representation, and simplifies the design of visualization algorithms on new and future computer architecture.

AB - One of the most critical challenges for high-performance computing (HPC) scientific visualization is execution on massively threaded processors. Of the many fundamental changes we are seeing in HPC systems, one of the most profound is a reliance on new processor types optimized for execution bandwidth over latency hiding. Our current production scientific visualization software is not designed for these new types of architectures. To address this issue, the VTK-m framework serves as a container for algorithms, provides flexible data representation, and simplifies the design of visualization algorithms on new and future computer architecture.

KW - algorithmic structures

KW - computer graphics

KW - high-performance computing

KW - massively threaded processors

KW - parallel algorithms

KW - visualization software

KW - VTK-m framework

UR - http://www.scopus.com/inward/record.url?scp=84969645967&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84969645967&partnerID=8YFLogxK

U2 - 10.1109/MCG.2016.48

DO - 10.1109/MCG.2016.48

M3 - Article

AN - SCOPUS:84969645967

VL - 36

SP - 48

EP - 58

JO - IEEE Computer Graphics and Applications

JF - IEEE Computer Graphics and Applications

SN - 0272-1716

IS - 3

M1 - 7466740

ER -