Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Multi-GPU Implementations of Parallel 3D Sweeping Algorithms with Application to Geological Folding
Linköping University, Department of Management and Engineering. Linköping University, Faculty of Science & Engineering. Simula Research Lab, Norway.
Simula Research Lab, Norway; University of Oslo, Norway.
Simula Research Lab, Norway; University of Oslo, Norway.
2015 (English)In: INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE, ICCS 2015 COMPUTATIONAL SCIENCE AT THE GATES OF NATURE, ELSEVIER SCIENCE BV , 2015, Vol. 51, 1494-1503 p.Conference paper, Published paper (Refereed)
Resource type
Text
Abstract [en]

This paper studies the CUDA programming challenges with using multiple GPUs inside a single machine to carry out plane-by-plane updates in parallel 3D sweeping algorithms. In particular, care must be taken to mask the overhead of various data movements between the GPUs. Multiple OpenMP threads on the CPU side should be combined multiple CUDA streams per GPU to hide the data transfer cost related to the halo computation on each 2D plane. Moreover, the technique of peer-to-peer data motion can be used to reduce the impact of 3D volumetric data shuffles that have to be done between mandatory changes of the grid partitioning. We have investigated the performance improvement of 2-and 4-GPU implementations that are applicable to 3D anisotropic front propagation computations related to geological folding. In comparison with a straightforward multi-GPU implementation, the overall performance improvement due to masking of data movements on four GPUs of the Fermi architecture was 23%. The corresponding improvement obtained on four Kepler GPUs was 47%.

Place, publisher, year, edition, pages
ELSEVIER SCIENCE BV , 2015. Vol. 51, 1494-1503 p.
Series
Procedia Computer Science, ISSN 1877-0509
Keyword [en]
NVIDIA GPU; CUDA programming; OpenMP; 3D sweeping; anisotropic front propagation
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:liu:diva-127767DOI: 10.1016/j.procs.2015.05.339ISI: 000373939100152OAI: oai:DiVA.org:liu-127767DiVA: diva2:927460
Conference
15th Annual International Conference on Computational Science (ICCS)
Available from: 2016-05-12 Created: 2016-05-12 Last updated: 2016-06-01

Open Access in DiVA

fulltext(924 kB)77 downloads
File information
File name FULLTEXT01.pdfFile size 924 kBChecksum SHA-512
39470c16f1c7f05418a7c457c2d9a5288f58ad7d2da25f3e75415967b944c7a3583626895a0189685b49b553ebd4d524317025a02b96fe3b9e39333588a92664
Type fulltextMimetype application/pdf

Other links

Publisher's full text

Search in DiVA

By author/editor
Krishnasamy, Ezhilmathi
By organisation
Department of Management and EngineeringFaculty of Science & Engineering
Computer and Information Science

Search outside of DiVA

GoogleGoogle Scholar
Total: 77 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 35 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf