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pro vyhledávání: '"Choi, Jee W"'
Autor:
Nguyen, Andy, Helal, Ahmed E., Checconi, Fabio, Laukemann, Jan, Tithi, Jesmin Jahan, Soh, Yongseok, Ranadive, Teresa, Petrini, Fabrizio, Choi, Jee W.
Tensor decomposition (TD) is an important method for extracting latent information from high-dimensional (multi-modal) sparse data. This study presents a novel framework for accelerating fundamental TD operations on massively parallel GPU architectur
Externí odkaz:
http://arxiv.org/abs/2201.12523
Autor:
Chakaravarthy, Venkatesan T., Choi, Jee W., Joseph, Douglas J., Murali, Prakash, Pandian, Shivmaran S., Sabharwal, Yogish, Sreedhar, Dheeraj
The Tucker decomposition generalizes the notion of Singular Value Decomposition (SVD) to tensors, the higher dimensional analogues of matrices. We study the problem of constructing the Tucker decomposition of sparse tensors on distributed memory syst
Externí odkaz:
http://arxiv.org/abs/1804.09494
Autor:
Chakaravarthy, Venkatesan T, Choi, Jee W, Joseph, Douglas J, Liu, Xing, Murali, Prakash, Sabharwal, Yogish, Sreedhar, Dheeraj
The Tucker decomposition expresses a given tensor as the product of a small core tensor and a set of factor matrices. Apart from providing data compression, the construction is useful in performing analysis such as principal component analysis (PCA)a
Externí odkaz:
http://arxiv.org/abs/1707.05594
Autor:
Choi, Jee W.
Advances in wireless technology and the growing popularity of multimedia applications have brought about a need for energy efficient and cost effective portable supercomputers capable of delivering performance beyond the capabilities of current micro
Externí odkaz:
http://hdl.handle.net/1853/4970
Autor:
Choi, Jee W., Vuduc, Richard W.
Publikováno v:
2016 IEEE International Parallel & Distributed Processing Symposium Workshops (IPDPSW); 2016, p79-88, 10p
Autor:
Liu, Xing, Buono, Daniele, Checconi, Fabio, Choi, Jee W., Que, Xinyu, Petrini, Fabrizio, Gunnels, John A., Stuecheli, Jeff A.
Publikováno v:
2016 IEEE International Parallel & Distributed Processing Symposium (IPDPS); 2016, p263-272, 10p
Akademický článek
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Autor:
Choi, Jee Whan
The overarching goal of this thesis is to provide an algorithm-centric approach to analyzing the relationship between time, energy, and power. This research is aimed at algorithm designers and performance tuners so that they may be able to make decis
Externí odkaz:
http://hdl.handle.net/1853/53561