Zobrazeno 1 - 10
of 69
pro vyhledávání: '"RIO YOKOTA"'
Autor:
Rio YOKOTA, Shinnosuke OBI
Publikováno v:
Journal of Fluid Science and Technology, Vol 6, Iss 1, Pp 14-29 (2011)
Vortex methods are a group of Lagrangian and semi-Lagrangian methods based on the vorticity-streamfunction or vorticity-velocity formulation of the Navier-Stokes equation, and provide an interesting alternative to grid based methods for external flow
Externí odkaz:
https://doaj.org/article/bfef34c5d2064f3aba6bce805fd4b027
Autor:
Rio Yokota, Weigang Wu
It constitutes the refereed proceedings of the 4th Asian Supercomputing Conference, SCFA 2018, held in Singapore in March 2018. Supercomputing Frontiers will be rebranded as Supercomputing Frontiers Asia (SCFA), which serves as the technical programm
Autor:
Rio Yokota, Muhammad Ridwan Apriansyah
Publikováno v:
ACM Transactions on Mathematical Software. 48:1-28
We present two new algorithms for Householder QR factorization of Block Low-Rank (BLR) matrices: one that performs block-column-wise QR, and another that is based on tiled QR. We show how the block-column-wise algorithm exploits BLR structure to achi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dc6b6652abec0ebdb79de77087cfd872
https://doi.org/10.1145/3538647
https://doi.org/10.1145/3538647
Autor:
Hiroyuki Ootomo, Rio Yokota
Publikováno v:
Proceedings of the International Conference on High Performance Computing in Asia-Pacific Region.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c1b451b1283d8692872ccd75a16828d2
https://doi.org/10.1145/3578178.3578238
https://doi.org/10.1145/3578178.3578238
Publikováno v:
Proceedings of the 28th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::163ac09c982b2f36f151fcc600b26e8d
https://doi.org/10.1145/3572848.3577516
https://doi.org/10.1145/3572848.3577516
Publikováno v:
Parallel and Distributed Computing, Applications and Technologies ISBN: 9783031299261
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5e372a54532ff5209e263e697b23cca8
https://doi.org/10.1007/978-3-031-29927-8_28
https://doi.org/10.1007/978-3-031-29927-8_28
Factorization of large dense matrices are ubiquitous in engineering and data science applications, e.g. preconditioners for iterative boundary integral solvers, frontal matrices in sparse multifrontal solvers, and computing the determinant of covaria
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::888a6f8958fb04fd33a86abbeb81c819
http://arxiv.org/abs/2208.10907
http://arxiv.org/abs/2208.10907
Autor:
Hiroyuki Ootomo, Rio Yokota
Tensor Core is a mixed-precision matrix–matrix multiplication unit on NVIDIA GPUs with a theoretical peak performance of more than 300 TFlop/s on Ampere architectures. Tensor Cores were developed in response to the high demand of dense matrix multi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2e5dabf63cd53154f4e43f33b4c0a8ec
http://arxiv.org/abs/2203.03341
http://arxiv.org/abs/2203.03341
Autor:
Hirokatsu Kataoka, Ryo Hayamizu, Ryosuke Yamada, Kodai Nakashima, Sora Takashima, Xinyu Zhang, Edgar Josafat Martinez-Noriega, Nakamasa Inoue, Rio Yokota
In the present work, we show that the performance of formula-driven supervised learning (FDSL) can match or even exceed that of ImageNet-21k without the use of real images, human-, and self-supervision during the pre-training of Vision Transformers (
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e20112254f6b8e1188961a5292ed0915
Autor:
APRIANSYAH, M. RIDWAN1 ridwan@rio.gsic.titech.ac.jp, RIO YOKOTA2 rioyokota@gsic.titech.ac.jp
Publikováno v:
ACM Transactions on Mathematical Software. Sep2022, Vol. 48 Issue 3, p1-28. 28p.