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Author: F.X. le Dimet
Publisher: Springer Science & Business Media
ISBN: 9401100330
Category : Science
Languages : en
Pages : 271
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Book Description
High Performance Computing in the Geosciences surveys the state of the art of programs presently being developed which require high performance computing for their implementation, provides a guide for decision making in regard to computing directions in future numerical models, and provides an overview of future developments in massively parallel processing and their implications for numerical modelling in the geosciences.
Author: F.X. le Dimet
Publisher: Springer Science & Business Media
ISBN: 9401100330
Category : Science
Languages : en
Pages : 271
Get Book Here
Book Description
High Performance Computing in the Geosciences surveys the state of the art of programs presently being developed which require high performance computing for their implementation, provides a guide for decision making in regard to computing directions in future numerical models, and provides an overview of future developments in massively parallel processing and their implications for numerical modelling in the geosciences.
Author: Organización del Tratado del Atlántico Norte Advanced Research Workshop
Publisher:
ISBN:
Category :
Languages : en
Pages : 261
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Book Description
Author: Malgorzata Peszynska
Publisher:
ISBN:
Category :
Languages : en
Pages : 105
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Book Description
Author: Wenwu Tang
Publisher: Springer Nature
ISBN: 3030479986
Category : Technology & Engineering
Languages : en
Pages : 298
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Book Description
This volume fills a research gap between the rapid development of High Performance Computing (HPC) approaches and their geospatial applications. With a focus on geospatial applications, the book discusses in detail how researchers apply HPC to tackle their geospatial problems. Based on this focus, the book identifies the opportunities and challenges revolving around geospatial applications of HPC. Readers are introduced to the fundamentals of HPC, and will learn how HPC methods are applied in various specific areas of geospatial study. The book begins by discussing theoretical aspects and methodological uses of HPC within a geospatial context, including parallel algorithms, geospatial data handling, spatial analysis and modeling, and cartography and geovisualization. Then, specific domain applications of HPC are addressed in the contexts of earth science, land use and land cover change, urban studies, transportation studies, and social science. The book will be of interest to scientists and engineers who are interested in applying cutting-edge HPC technologies in their respective fields, as well as students and faculty engaged in geography, environmental science, social science, and computer science.
Author: Yuzhu Wang
Publisher: Mdpi AG
ISBN: 9783036581804
Category : Science
Languages : en
Pages : 0
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Book Description
In total, this Special Issue includes 11 papers. Firstly, Qi et al. conducted research on the large-scale non-uniform parallel solution of the two-dimensional Saint-Venant equations for flood behavior modeling. Zhang et al. proposed an efficient deep learning-based mineral identification method. Subsequently, Huang et al. proposed a named entity recognition method for geological news based on BERT model. Yang et al. proposed an automatic landslide identification method to solve the problem of the time-consuming nature and low efficiency of traditional landslide identification methods. Du et al. analyzed the potential of unsupervised machine learning methods for submarine landslide prediction. Wang et al. performed parallel computations on the inversion algorithm of the two-dimensional ZTEM. Xu et al. used the sliding window method and gray relational analysis to extract features from multi-source real-time monitoring data of landslides. Furthermore, Cao et al. proposed a new method called dual encoder transform (DualET) for the short-term prediction of photovoltaic power. Hao et al. conducted a series of parallel optimizations and large-scale parallel simulations on the high-resolution ocean model. Wang et al. proposed a time series prediction model for landslide displacements using mean-based low-rank autoregressive tensor completion. Finally, Yang et al. developed a measure of site-level gross primary productivity (GPP) using the GeoMAN model.
Author: Dany Kemmler
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Author: Ronald E. Cohen
Publisher:
ISBN:
Category : Earth sciences
Languages : en
Pages : 104
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Book Description
Author: Gonzalo Hernandez
Publisher: Springer
ISBN: 3662454831
Category : Computers
Languages : en
Pages : 267
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Book Description
This book constitutes the refereed proceedings of the First HPCLATAM - CLCAR Joint Latin American High Performance Computing Conference, CARLA 2014, held in Valparaiso, Chile, in October 2014. The 17 revised full papers and the one paper presented were carefully reviewed and selected from 42 submissions. The papers are organized in topical sections on grid and cloud computing; HPC architectures and tools; parallel programming; scientific computing.
Author: Alice-Agnes Gabriel
Publisher: Frontiers Media SA
ISBN: 2832523056
Category : Science
Languages : en
Pages : 185
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Book Description
Author: United States. Congress. House. Committee on Science, Space, and Technology. Subcommittee on Science
Publisher:
ISBN:
Category : Business & Economics
Languages : en
Pages : 288
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Book Description
