KOUYA Tomonori

J-GLOBAL         Last updated: Nov 4, 2017 at 11:44
KOUYA Tomonori
Shizuoka Institute of Science and Technology
Faculty of Comprehensive Informatics
Job title
Ph.D(Nihon University)
Twitter ID

Research Areas


Academic & Professional Experience

- Lecturer, Shizuoka Institute of Science
and Technology


Graduate School, Division of Science and Engineering, Nihon University
Faculty of Science and Engineering, Tokyo University of Science

Committee Memberships

SIAM  General Member


KOUYA Tomonori
JSIAM Letters   8 21-24   May 2016   [Refereed]
It is well known that Strassen and Winograd algorithms can reduce the computational
costs associated with dense matrix multiplication. We have already shown
that they are also very effective for software-based multiple precision floating-point
Tomonori Kouya
International Journal of Numerical Methods and Applications, Vol.7, Issue 2, 2012, Pages 107 - 119      Nov 2014
We evaluate the performance of the Krylov subspace method by using highly
efficient multiple precision sparse matrix-vector multiplication (SpMV).
BNCpack is our multiple precision numerical computation library based on
MPFR/GMP, which is one of t...
Tomonori Kouya
JSIAM Letters   6 81-84   Oct 2014   [Refereed]
The Strassen algorithm and Winograd's variant accelerate matrix
multiplication by using fewer arithmetic operations than standard matrix
multiplication. Although many papers have been published to accelerate single-
as well as double-precision mat...
Tomonori Kouya
International Journal of Numerical Methods and Applications, Volume 9, Number 2, 2013, pp.85-108      Jun 2013
We propose a practical implementation of high-order fully implicit
Runge-Kutta(IRK) methods in a multiple precision floating-point environment.
Although implementations based on IRK methods in an IEEE754 double precision
environment have been repo...

Books etc

Elena Nikolaevskaya, Alexandr Khimich, Tamara Chistyakova
Springer   Apr 2014   ISBN:364243374X

Research Grants & Projects

Study on numerical properties for discrete Solutions of ordinary differential equations in multi-precision arithmetic environment
Study on Accurate and hiperformance numerical computation with PC Cluster and its related topics
Project Year: 2003   
Study on arbitrary precision computation based on empirical error estimation method (Classical Error Estimation, CEE)
Project Year: 2006   
We are developing numerical compuation algorithms based on empirical error estimation method in order to obtain user-required precision approximation by using existing old-style numerical algorithms or libraries.