Dr. Bin Dong is a Research Scientist in Lawrence Berkeley National Laboratory in Berkeley, California, USA. Bin has the Ph.D degree in computing science and technology. Bin has wide research interests in big scientific data analysis, parallel computing, parallel I/O, machine learning, etc. He has co-authored more than 62 technical publications.
Dr. Kesheng Wu is a Senior Scientist at Lawrence Berkeley National Laboratory. He works extensively on data management, data analysis, and scientific computing. He is the developer of a number of widely used algorithms including Fast Bit bitmap indexes for querying large scientific datasets, Thick-Restart Lanczos (TRLan) algorithm for solving eigenvalue problems, and IDEALEM for statistical data reduction and feature extraction. He has co-authored more than 200 technical publications.
Dr. Suren Byna is a Computer Scientist in the Scientific Data Management (SDM) Group at Lawrence Berkeley National Laboratory in Berkeley, California, USA. His research interests are in scalable scientific data management. More specifically, he works on optimizing parallel I/O and on developing systems for managing scientific data. He leads the Exa IO project in the Exascale Computing Project (ECP) that contributes advanced I/O features to HDF5 and develops a new file system called Unify FS. He also leads efforts that develop object-centric data management systems (Proactive Data Containers – PDC) and experimental and observational data (EOD) management strategies. He has co-authored more than 150 technical publications.
1 Ebooks door Kesheng Wu
Bin Dong & Kesheng Wu: User-Defined Tensor Data Analysis
The Springer Brief introduces Fas Tensor, a powerful parallel data programming model developed for big data applications. This book also provides a user’s guide for installing and using Fas Tensor. F …
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€64.19