research-article

A classification of scientific visualization algorithms for massive threading

Authors:

Kenneth Moreland,

Robert MaynardAuthors Info & Claims

UltraVis '13: Proceedings of the 8th International Workshop on Ultrascale Visualization

Article No.: 2, Pages 1 - 10

https://doi.org/10.1145/2535571.2535591

Published: 17 November 2013 Publication History

Abstract

As the number of cores in processors increase and accelerator architectures are becoming more common, an ever greater number of threads is required to achieve full processor utilization. Our current parallel scientific visualization codes rely on partitioning data to achieve parallel processing, but this approach will not scale as we approach massive threading in which work is distributed in such a fine level that each thread is responsible for a minute portion of data. In this paper we characterize the challenges of refactoring our current visualization algorithms by considering the finest portion of work each performs and examining the domain of input data, overlaps of output domains, and interdependencies among work instances. We divide our visualization algorithms into eight categories, each containing algorithms with the same interdependencies. By focusing our research efforts to solving these categorial challenges rather than this legion of individual algorithms, we can make attainable advancement for extreme computing.

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Cited By

Petersen MWerner KSchnorr AKuhlen TGarth C(2022)A Prototype for Pipeline-Composable Task-Based Visualization Algorithms2022 IEEE 12th Symposium on Large Data Analysis and Visualization (LDAV)10.1109/LDAV57265.2022.9966395(1-11)Online publication date: 16-Oct-2022
https://doi.org/10.1109/LDAV57265.2022.9966395
Moreland KSewell CUsher WLo LMeredith JPugmire DKress JSchroots HMa KChilds HLarsen MChen CMaynard RGeveci B(2016)VTK-m: Accelerating the Visualization Toolkit for Massively Threaded ArchitecturesIEEE Computer Graphics and Applications10.1109/MCG.2016.4836:3(48-58)Online publication date: May-2016
https://doi.org/10.1109/MCG.2016.48
Moreland KLarsen MChilds H(2015)Visualization for ExascaleSupercomputing Frontiers and Innovations: an International Journal10.5555/3026759.30267652:3(67-75)Online publication date: 1-Jul-2015
https://dl.acm.org/doi/10.5555/3026759.3026765
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cover image ACM Conferences

UltraVis '13: Proceedings of the 8th International Workshop on Ultrascale Visualization

November 2013

56 pages

ISBN:9781450325004

DOI:10.1145/2535571

Editors:
Kwan-Liu Ma
University of California, Davis
,
Venkatram Vishwanath
Argonne National Laboratory
,
Hongfeng Yu
University of Nebraska-Lincoln

Copyright © 2013 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 17 November 2013

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SC13: International Conference for High Performance Computing, Networking, Storage and Analysis

November 17 - 21, 2013

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UltraVis '13 Paper Acceptance Rate 6 of 7 submissions, 86%;

Overall Acceptance Rate 6 of 7 submissions, 86%

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Cited By

Petersen MWerner KSchnorr AKuhlen TGarth C(2022)A Prototype for Pipeline-Composable Task-Based Visualization Algorithms2022 IEEE 12th Symposium on Large Data Analysis and Visualization (LDAV)10.1109/LDAV57265.2022.9966395(1-11)Online publication date: 16-Oct-2022
https://doi.org/10.1109/LDAV57265.2022.9966395
Moreland KSewell CUsher WLo LMeredith JPugmire DKress JSchroots HMa KChilds HLarsen MChen CMaynard RGeveci B(2016)VTK-m: Accelerating the Visualization Toolkit for Massively Threaded ArchitecturesIEEE Computer Graphics and Applications10.1109/MCG.2016.4836:3(48-58)Online publication date: May-2016
https://doi.org/10.1109/MCG.2016.48
Moreland KLarsen MChilds H(2015)Visualization for ExascaleSupercomputing Frontiers and Innovations: an International Journal10.5555/3026759.30267652:3(67-75)Online publication date: 1-Jul-2015
https://dl.acm.org/doi/10.5555/3026759.3026765
Schroots HMa K(2015)Volume rendering with data parallel visualization frameworks for emerging high performance computing architecturesSIGGRAPH Asia 2015 Visualization in High Performance Computing10.1145/2818517.2818546(1-4)Online publication date: 2-Nov-2015
https://dl.acm.org/doi/10.1145/2818517.2818546

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