Woohyuk Choi

SAMSUNG CSC

     Ms-PhD. Student
     E-mail: whchoi (at) unist.ac.kr

 

 

 

Research Interests

  • Volume rendering & Domain Specific Language
  • GPU attached MapReduce Framework

Education

  • B.S. in Electrical Computer Engineering, UNIST, Ulsan, Korea (2014)

Work Experience

Publications

  • [PDF] S. Hong, W. Choi, and W. Jeong, “GPU in-memory processing using spark for iterative computation,” 2017 17th IEEE/ACM international symposium on cluster, cloud and grid computing (CCGrid), 2017.
    [Bibtex]
    @article{hong_ccgrid_2017,
    title = "{GPU} in-memory processing using Spark for iterative computation",
    year = "2017",
    author = "Sumin Hong and Woohyuk Choi and Won-Ki Jeong",
    journal = {2017 17th {IEEE}/{ACM} International Symposium on Cluster, Cloud and Grid Computing ({CCG}rid)}
    }

 

  • [DOI] D. G. C. Hildebrand, M. Cicconet, R. M. Torres, W. Choi, T. M. Quan, J. Moon, A. W. Wetzel, A. Scott Champion, B. J. Graham, O. Randlett, G. S. Plummer, R. Portugues, I. H. Bianco, S. Saalfeld, A. D. Baden, K. Lillaney, R. Burns, J. T. Vogelstein, A. F. Schier, W. A. Lee, W. Jeong, J. W. Lichtman, and F. Engert, “Whole-brain serial-section electron microscopy in larval zebrafish,” Nature, vol. 545, iss. 7654, pp. 345-349, 2017.
    [Bibtex]
    @Article{hildebrand_nature_2017,
    author={Hildebrand, David Grant Colburn
    and Cicconet, Marcelo
    and Torres, Russel Miguel
    and Choi, Woohyuk
    and Quan, Tran Minh
    and Moon, Jungmin
    and Wetzel, Arthur Willis
    and Scott Champion, Andrew
    and Graham, Brett Jesse
    and Randlett, Owen
    and Plummer, George Scott
    and Portugues, Ruben
    and Bianco, Isaac Henry
    and Saalfeld, Stephan
    and Baden, Alexander David
    and Lillaney, Kunal
    and Burns, Randal
    and Vogelstein, Joshua Tzvi
    and Schier, Alexander Franz
    and Lee, Wei-Chung Allen
    and Jeong, Won-Ki
    and Lichtman, Jeff William
    and Engert, Florian},
    title={Whole-brain serial-section electron microscopy in larval zebrafish},
    journal={Nature},
    year={2017},
    month={May},
    day={18},
    publisher={Macmillan Publishers Limited, part of Springer Nature. All rights reserved.},
    volume={545},
    number={7654},
    pages={345-349},
    note={Letter},
    issn={0028-0836},
    url={http://dx.doi.org/10.1038/nature22356},
    doi = {10.1038/nature22356}
    }

 

  • [PDF] [DOI] W. Choi, S. Hong, and W. Jeong, “Vispark: GPU-Accelerated Distributed Visual Computing Using Spark,” SIAM Journal on Scientific Computing (SISC), vol. 38, iss. 5, p. S700-S719, 2016.
    [Bibtex]
    @article{woohyuk_2016_vispark,
    author={Woohyuk Choi and Sumin Hong and Won-Ki Jeong},
    title={{Vispark: {GPU}-Accelerated Distributed Visual Computing Using Spark}},
    journal={{SIAM Journal on Scientific Computing (SISC)}},
    publisher={Society for Industrial and Applied Mathematics},
    volume = {38},
    number = {5},
    pages = {S700-S719},
    year = {2016},
    doi = {10.1137/15M1026407},
    URL = {
    http://dx.doi.org/10.1137/15M1026407
    },
    eprint = {
    http://dx.doi.org/10.1137/15M1026407
    }
    }

 

  • [PDF] [DOI] H. Choi, W. Choi, T. M. Quan, D. G. C. Hildebrand, H. Pfister, and W. Jeong, “Vivaldi: a domain-specific language for volume processing and visualization on distributed heterogeneous systems,” IEEE transactions on visualization and computer graphics, vol. 20, iss. 12, pp. 2407-2416, 2014.
    [Bibtex]
    @article{choi_vivaldi_2014,
    title = {Vivaldi: A Domain-Specific Language for Volume Processing and Visualization on Distributed Heterogeneous Systems},
    volume = {20},
    issn = {1077-2626},
    shorttitle = {Vivaldi},
    doi = {10.1109/TVCG.2014.2346322},
    abstract = {As the size of image data from microscopes and telescopes increases, the need for high-throughput processing and visualization of large volumetric data has become more pressing. At the same time, many-core processors and {GPU} accelerators are commonplace, making high-performance distributed heterogeneous computing systems affordable. However, effectively utilizing {GPU} clusters is difficult for novice programmers, and even experienced programmers often fail to fully leverage the computing power of new parallel architectures due to their steep learning curve and programming complexity. In this paper, we propose Vivaldi, a new domain-specific language for volume processing and visualization on distributed heterogeneous computing systems. Vivaldi's Python-like grammar and parallel processing abstractions provide flexible programming tools for non-experts to easily write high-performance parallel computing code. Vivaldi provides commonly used functions and numerical operators for customized visualization and high-throughput image processing applications. We demonstrate the performance and usability of Vivaldi on several examples ranging from volume rendering to image segmentation.},
    number = {12},
    journal = {{IEEE} Transactions on Visualization and Computer Graphics},
    author = {Choi, H. and Choi, W. and Quan, T.M. and Hildebrand, D.G.C. and Pfister, H. and Jeong, W.},
    month = dec,
    year = {2014},
    keywords = {computational modeling, Data models, Data visualization, distributed heterogeneous systems, Domain-specific language, {GPU} computing, graphics processing units, image classification, parallel processing, rendering (computer graphics), volume rendering},
    pages = {2407--2416},
    file = {{IEEE} Xplore Abstract Record:H\:\\Zotero\\storage\\ED5RN7ME\\articleDetails.html:text/html;{IEEE} Xplore Full Text PDF:H\:\\Zotero\\storage\\XKKZSRWV\\Choi et al. - 2014 - Vivaldi A Domain-Specific Language for Volume Pro.pdf:application/pdf}
    }

 

Honor / Award