GPU parallel program development using CUDA (Record no. 59063)

000 -LEADER
fixed length control field 02186cam a22001698i 4500
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781498750752 (hardback)
082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 005.275
Item number SOY/G
100 1# - MAIN ENTRY--AUTHOR NAME
Personal name Soyata, Tolga,
245 10 - TITLE STATEMENT
Title GPU parallel program development using CUDA
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication Boca Raton
Name of publisher CRC
Year of publication 2018
300 ## - PHYSICAL DESCRIPTION
Number of Pages 440p.
520 ## - SUMMARY, ETC.
Summary, etc GPU Parallel Program Development using CUDA teaches GPU programming by showing the differences among different families of GPUs. This approach prepares the reader for the next generation and future generations of GPUs. The book emphasizes concepts that will remain relevant for a long time, rather than concepts that are platform-specific. At the same time, the book also provides platform-dependent explanations that are as valuable as generalized GPU concepts.<br/><br/>The book consists of three separate parts; it starts by explaining parallelism using CPU multi-threading in Part I. A few simple programs are used to demonstrate the concept of dividing a large task into multiple parallel sub-tasks and mapping them to CPU threads. Multiple ways of parallelizing the same task are analyzed and their pros/cons are studied in terms of both core and memory operation.<br/><br/>Part II of the book introduces GPU massive parallelism. The same programs are parallelized on multiple Nvidia GPU platforms and the same performance analysis is repeated. Because the core and memory structures of CPUs and GPUs are different, the results differ in interesting ways. The end goal is to make programmers aware of all the good ideas, as well as the bad ideas, so readers can apply the good ideas and avoid the bad ideas in their own programs.<br/><br/>Part III of the book provides pointer for readers who want to expand their horizons. It provides a brief introduction to popular CUDA libraries (such as cuBLAS, cuFFT, NPP, and Thrust),the OpenCL programming language, an overview of GPU programming using other programming languages and API libraries (such as Python, OpenCV, OpenGL, and Apple’s Swift and Metal,) and the deep learning library cuDNN.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Parallel programming (Computer science)
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term CUDA (Computer architecture)
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Graphics processing units
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type BK
952 ## - LOCATION AND ITEM INFORMATION (KOHA)
Withdrawn status
Lost status
Damaged status
Holdings
Home library Date acquired Full call number Accession Number Koha item type
Kannur University Central Library 23/07/2020 005.275 SOY/G 51065 BK

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