Accelerating MATLAB with GPU Computing (Record no. 11901)

MARC details
000 -LEADER
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020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9780124080805
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 519.4
Item number Su36A
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Suh, Jung
Relator term Author
Language of a work English
9 (RLIN) 698
245 #0 - TITLE STATEMENT
Title Accelerating MATLAB with GPU Computing
Remainder of title : A Primer with Examples
Statement of responsibility, etc. / by Jung Suh and Youngmin Kim.
Medium [Electronic Resource]
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Waltham, MA
Name of publisher, distributor, etc. : Morgan Kaufmann,
Date of publication, distribution, etc. 2013
300 ## - PHYSICAL DESCRIPTION
Extent 248p.
520 ## - SUMMARY, ETC.
Summary, etc. Beyond simulation and algorithm development, many developers increasingly use MATLAB even for product deployment in computationally heavy fields. This often demands that MATLAB codes run faster by leveraging the distributed parallelism of Graphics Processing Units (GPUs). While MATLAB successfully provides high-level functions as a simulation tool for rapid prototyping, the underlying details and knowledge needed for utilizing GPUs make MATLAB users hesitate to step into it. Accelerating MATLAB with GPUs offers a primer on bridging this gap. Starting with the basics, setting up MATLAB for CUDA (in Windows, Linux and Mac OS X) and profiling, it then guides users through advanced topics such as CUDA libraries. The authors share their experience developing algorithms using MATLAB, C++ and GPUs for huge datasets, modifying MATLAB codes to better utilize the computational power of GPUs, and integrating them into commercial software products. Throughout the book, they demonstrate many example codes that can be used as templates of C-MEX and CUDA codes for readers'projects. Download example codes from the publisher's website: http://booksite.elsevier.com/9780124080805/Shows how to accelerate MATLAB codes through the GPU for parallel processing, with minimal hardware knowledgeExplains the related background on hardware, architecture and programming for ease of useProvides simple worked examples of MATLAB and CUDA C codes as well as templates that can be reused in real-world projects
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Graphics Processing Units
9 (RLIN) 239
Topical term or geographic name entry element MATLAB
9 (RLIN) 699
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Kim, Youngmin.
Relationship information [Author]
9 (RLIN) 241
856 ## - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=503587">http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=503587</a>
Electronic format type PDF
Link text Click to Access the Online Book
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type e-Book
Suppress in OPAC
Holdings
Withdrawn status Lost status Damaged status Use restrictions Not for loan Collection Home library Current library Shelving location Date acquired Source of acquisition Cost, normal purchase price Total Checkouts Full call number Barcode Date last seen Price effective from Koha item type Public note
      e-Book For Access   Textbook S. R. Ranganathan Learning Hub S. R. Ranganathan Learning Hub Online 2022-09-20 Infokart India Pvt. Ltd., New Delhi 82.74   519.4 Su36A EB0037 2022-09-20 2022-09-20 e-Book Platform : EBSCO