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Programming in parallel with CUDA : = a practical guide /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Programming in parallel with CUDA :/ Richard Ansorge.
Reminder of title:	a practical guide /
Author:	Ansorge, Richard,
Description:	1 online resource (xxi, 454 pages) :digital, PDF file(s). :
Notes:	Title from publisher's bibliographic system (viewed on 07 Apr 2022).
Subject:	Parallel programming (Computer science) -
Online resource:	https://doi.org/10.1017/9781108855273
ISBN:	9781108855273 (ebook)

Programming in parallel with CUDA : = a practical guide /
Ansorge, Richard,

Programming in parallel with CUDA :a practical guide /Richard Ansorge. - First edition. - 1 online resource (xxi, 454 pages) :digital, PDF file(s).

Title from publisher's bibliographic system (viewed on 07 Apr 2022).

CUDA is now the dominant language used for programming GPUs, one of the most exciting hardware developments of recent decades. With CUDA, you can use a desktop PC for work that would have previously required a large cluster of PCs or access to a HPC facility. As a result, CUDA is increasingly important in scientific and technical computing across the whole STEM community, from medical physics and financial modelling to big data applications and beyond. This unique book on CUDA draws on the author's passion for and long experience of developing and using computers to acquire and analyse scientific data. The result is an innovative text featuring a much richer set of examples than found in any other comparable book on GPU computing. Much attention has been paid to the C++ coding style, which is compact, elegant and efficient. A code base of examples and supporting material is available online, which readers can build on for their own projects.

ISBN: 9781108855273 (ebook)Subjects--Topical Terms:

557472
Parallel programming (Computer science)

LC Class. No.: QA76.642 / .A57 2022

Dewey Class. No.: 005.2/75

Programming in parallel with CUDA : = a practical guide /
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520 $a CUDA is now the dominant language used for programming GPUs, one of the most exciting hardware developments of recent decades. With CUDA, you can use a desktop PC for work that would have previously required a large cluster of PCs or access to a HPC facility. As a result, CUDA is increasingly important in scientific and technical computing across the whole STEM community, from medical physics and financial modelling to big data applications and beyond. This unique book on CUDA draws on the author's passion for and long experience of developing and using computers to acquire and analyse scientific data. The result is an innovative text featuring a much richer set of examples than found in any other comparable book on GPU computing. Much attention has been paid to the C++ coding style, which is compact, elegant and efficient. A code base of examples and supporting material is available online, which readers can build on for their own projects.
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