YOKOTA Rio

J-GLOBAL         Last updated: Feb 20, 2018 at 15:32
 
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Name
YOKOTA Rio
E-mail
rioyokotagsic.titech.ac.jp
URL
http://www.rio.gsic.titech.ac.jp/en/index.html
Affiliation
Tokyo Institute of Technology
Section
Global Scientific Information and Computing Center, Global Scientific Information and Computing Center, 高性能計算先端応用分野
Job title
Associate Professor
Degree
Ph.D. (Engineering)(Keio University)
Research funding number
20760573

Research Areas

 
 

Academic & Professional Experience

 
Sep 2011
 - 
Today
Research Scientist, Applied Mathematics and Computer Science, King Abdullah University of Science and Technology
 
Sep 2010
 - 
Aug 2011
Post-doctoral Research Associate, Department of Mechanical Engineering, Boston University
 
Feb 2009
 - 
Aug 2010
Post-doctoral Research Associate, Department of Mathematics, University of Bristol
 

Education

 
Apr 2005
 - 
Mar 2009
School of Science for Open and Environmental Systems (PhD), Graduate School of Science and Technology, Keio University
 
Apr 2003
 - 
Mar 2005
School of Science for Open and Environmental Systems (Masters), Graduate School of Science and Technology, Keio University
 
Apr 1997
 - 
Mar 2003
Department of Mechanical Engineering, Faculty of Science and Technology, Keio University
 

Committee Memberships

 
Apr 2015
 - 
Today
Tokyo Institute of Technology, Global Scientific Information and Computing Center  Partnership Resource Allocations Committee
 
Apr 2015
 - 
Today
Tokyo Institute of Technology, Global Scientific Information and Computing Center  Global Collaboration Committee for Utilization of Information Resources
 
Apr 2015
 - 
Today
Tokyo Institute of Technology, Global Scientific Information and Computing Center  Computing Infrastructures Committee for Research
 
Apr 2015
 - 
Today
Tokyo Institute of Technology, Global Scientific Information and Computing Center  Steering Committee
 

Awards & Honors

 
2009
ACM Gordon Bell Prize (price/performance)
 

Published Papers

 
Fast Multipole Preconditioners for Sparse Matrices Arising from Elliptic Equations
IBEID Huda, YOKOTA Rio, PESTANA Jennifer, KEYES David
Computing and Visualization in Science      Dec 2016   [Refereed]
Communication Optimization of Distributed Memory FMM for Large Scale Boundary Element Methods
YOKOTA Rio
Simulation      Oct 2016   [Refereed][Invited]
Tradeoff Between FMM and H^2(HSS)-Matrices
YOKOTA Rio
Journal of the Japan Society for Computational Engineering and Science   21(4) 6-8   Oct 2016   [Refereed][Invited]
IBEID Huda, YOKOTA Rio, KEYES David
International Journal of High Performance Computing Applications   30(4) 423-437   Mar 2016   [Refereed]
CASTRILLON-CANDAS Julio, GENTON Marc, YOKOTA Rio
Spatial Statistics   18 105-124   Nov 2015   [Refereed]

Misc

 
R. Yokota, T. K. Sheel, and S. Obi
Journal of Computational Physics   226(2) 1589-1606   2007
The study of colliding vortex rings using a special-purpose computer and FMM
T. K. Sheel, R. Yokota, K.Yasuoka, and S. Obi
Transactions of the Japan Society for Computational Engineering and Science   20080003    2008
R. Yokota, T. Narumi, R. Sakamaki, S. Kameoka, S. Obi, and K. Yasuoka
Computer Physics Communications   180(11)    2066
2066-2078
T. Hamada, R. Yokota, K. Nitadori, T. Narumi, K. Yasuoka, M. Taiji, and K. Oguri
SC09, Gordon Bell prize (price/performance), Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis      2009
R. Yokota and S. Obi
International Journal for Numerical Methods in Fluids      2010

Books etc

 
High Performance Parallelism Pearls
YOKOTA Rio (Part:Joint Editor, N-body methods on Xeon Phi coprocessors)
Morgan Kaufmann   Nov 2014   
GPU Computing Gems
Morgan Kaufmann   2011   ISBN:0123849888

Conference Activities & Talks

 
Improving Data Locality of Fast Multipole Methods
YOKOTA Rio
Third Workshop on Programming Abstractions for Data Locality   24 Oct 2016   
Fast Multipole Method Library for Multiple Architectures and its Application to Molecular and Fluid Simulations
YOKOTA Rio
8th Symposium of the Joint Usage/Research Center for Interdisciplinary Large-scale Information Infrastructures   14 Jul 2016   
Perforamance Portability of FMM
YOKOTA Rio
21st Conference of Japan Computational Engineering Society   31 May 2016   
A Common API for Fast Multipole Methods
YOKOTA Rio
Accelerate Data Analytics and Computing Workshop   14 Jan 2016   
Tuning Parameters in FMM [Invited]
YOKOTA Rio
Seventh Symposium on Automatic Tuning Technology and its Application   25 Dec 2015   

Teaching Experience

 
 

Research Grants & Projects

 
Acceleration and economization of deep learning algorithms for image processing in social infrastructure
Japan Science and Technology Agency: CREST
Project Year: Nov 2016 - Mar 2019    Investigator(s): SHINODA Koichi
Grant-in-Aid for Scientific Research (B)
Japan Society for the Promotion of Science: Grants-in-Aid for Scientific Research
Project Year: Apr 2016 - Mar 2019    Investigator(s): MARUYAMA Naoya
Grant-in-Aid for Encouragement of Young Scientists (A)
Japan Society for the Promotion of Science: Grants-in-Aid for Scientific Research
Project Year: Apr 2016 - Mar 2018    Investigator(s): YOKOTA Rio
Grant-in-Aid for Research Activity start-up
Japan Society for the Promotion of Science: Grants-in-Aid for Scientific Research
Project Year: Aug 2015 - Mar 2017    Investigator(s): YOKOTA Rio