Accelerating MATLAB with GPU Computing (Record no. 11901)
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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 | |
Link text | Click to Access the Online Book |
942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
Koha item type | e-Book |
Suppress in OPAC |
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 |
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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 |