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GPU Solutions to Multi-scale Problems in Science and Engineering: Lecture Notes in Earth System Sciences

Editat de David A. Yuen, Long Wang, Xuebin Chi, Lennart Johnsson, Wei Ge, Yaolin Shi
en Limba Engleză Hardback – 8 ian 2013
This book covers the new topic of GPU computing with many applications involved, taken from diverse fields such as networking, seismology, fluid mechanics, nano-materials, data-mining , earthquakes ,mantle convection, visualization. It will show the public why GPU computing is important and easy to use. It will offer a reason why GPU computing is useful and how to implement codes in an everyday situation.
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Specificații

ISBN-13: 9783642164040
ISBN-10: 3642164048
Pagini: 260
Ilustrații: XIII, 693 p.
Dimensiuni: 155 x 235 x 45 mm
Greutate: 1.13 kg
Ediția:2013
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Lecture Notes in Earth System Sciences

Locul publicării:Berlin, Heidelberg, Germany

Public țintă

Research

Cuprins

Initial-value problems associated with viscoelasticity in the geosciences.- The geophysical phenomenon of Glacial Isostatic Adjustment.- Initial Value Approach with the MOL.- Elastic and Viscoelastic Responses.- Current Numerical Methods for integrating VIP.- GPU Hardware aspects.- GPU Software aspects.- Philosophy of GPU Implementation of the MOL in VIP problems.- Code conversion versus Code implementation using CUDA or Open CL.- Examples of Postglacial Rebound.- Future Perspectives of VIP on GPU.

Textul de pe ultima copertă

This book covers the new topic of GPU computing with many applications involved, taken from diverse fields such as networking, seismology, fluid mechanics, nano-materials, data-mining , earthquakes ,mantle convection, visualization. It will show the public why GPU computing is important and easy to use. It will offer a reason why GPU computing is useful and how to implement codes in an everyday situation.

Caracteristici

Shows how GPU are used in many diverse problems in science and engineering gives examples of codes Written in CUDA for diverse problems Shows how algorithms can be implemented on GPU Includes supplementary material: sn.pub/extras