Accelerating MATLAB with GPU computing: a primer with examples
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Amsterdam
Morgan Kaufmann/Elsevier
2014
|
| Ausgabe: | First edition |
| Schlagworte: | |
| Online-Zugang: | FAW01 FAW02 |
| Beschreibung: | Print version record |
| Beschreibung: | 1 online resource (x, 248 pages) illustrations |
| ISBN: | 9780124079168 0124079164 0124080804 9780124080805 |
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| 505 | 8 | |a "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 knowledge -- Explains the related background on hardware, architecture and programming for ease of use -- Provides simple worked examples of MATLAB and CUDA C codes as well as templates that can be reused in real-world projects."--Provided by publisher | |
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Datensatz im Suchindex
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| any_adam_object | |
| author | Suh, Jung W. |
| author_facet | Suh, Jung W. |
| author_role | aut |
| author_sort | Suh, Jung W. |
| author_variant | j w s jw jws |
| building | Verbundindex |
| bvnumber | BV043958123 |
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| contents | Accelerating MATLAB without GPU -- Configurations for MATLAB and CUDA -- Optimization planning through profiling -- CUDA coding with c-mex -- MATLAB and parallel computing toolbox -- Using CUDA-accelerated libraries -- Example in computer graphics -- CUDA conversion example : 3D image processing "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 knowledge -- Explains the related background on hardware, architecture and programming for ease of use -- Provides simple worked examples of MATLAB and CUDA C codes as well as templates that can be reused in real-world projects."--Provided by publisher |
| ctrlnum | (ZDB-4-EBA)ocn872703168 (ZDB-4-ITC)ocn872703168 (OCoLC)872703168 (DE-599)BVBBV043958123 |
| dewey-full | 519.4 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.4 |
| dewey-search | 519.4 |
| dewey-sort | 3519.4 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik |
| edition | First edition |
| format | Electronic eBook |
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| indexdate | 2024-07-10T07:39:43Z |
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| language | English |
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| spelling | Suh, Jung W. Verfasser aut Accelerating MATLAB with GPU computing a primer with examples Jung W. Suh, Youngmin Kim First edition Amsterdam Morgan Kaufmann/Elsevier 2014 © 2014 1 online resource (x, 248 pages) illustrations txt rdacontent c rdamedia cr rdacarrier Print version record Accelerating MATLAB without GPU -- Configurations for MATLAB and CUDA -- Optimization planning through profiling -- CUDA coding with c-mex -- MATLAB and parallel computing toolbox -- Using CUDA-accelerated libraries -- Example in computer graphics -- CUDA conversion example : 3D image processing "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 knowledge -- Explains the related background on hardware, architecture and programming for ease of use -- Provides simple worked examples of MATLAB and CUDA C codes as well as templates that can be reused in real-world projects."--Provided by publisher MATLAB. MATLAB. fast COMPUTERS / General bisacsh Graphics processing units fast Numerical analysis / Data processing fast Datenverarbeitung Graphics processing units Numerical analysis Data processing Grafikprozessor (DE-588)4582114-8 gnd rswk-swf MATLAB (DE-588)4329066-8 gnd rswk-swf MATLAB (DE-588)4329066-8 s Grafikprozessor (DE-588)4582114-8 s 1\p DE-604 Kim, Youngmin Sonstige oth Erscheint auch als Druck-Ausgabe Suh, Jung W . Accelerating MATLAB with GPU computing 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Suh, Jung W. Accelerating MATLAB with GPU computing a primer with examples Accelerating MATLAB without GPU -- Configurations for MATLAB and CUDA -- Optimization planning through profiling -- CUDA coding with c-mex -- MATLAB and parallel computing toolbox -- Using CUDA-accelerated libraries -- Example in computer graphics -- CUDA conversion example : 3D image processing "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 knowledge -- Explains the related background on hardware, architecture and programming for ease of use -- Provides simple worked examples of MATLAB and CUDA C codes as well as templates that can be reused in real-world projects."--Provided by publisher MATLAB. MATLAB. fast COMPUTERS / General bisacsh Graphics processing units fast Numerical analysis / Data processing fast Datenverarbeitung Graphics processing units Numerical analysis Data processing Grafikprozessor (DE-588)4582114-8 gnd MATLAB (DE-588)4329066-8 gnd |
| subject_GND | (DE-588)4582114-8 (DE-588)4329066-8 |
| title | Accelerating MATLAB with GPU computing a primer with examples |
| title_auth | Accelerating MATLAB with GPU computing a primer with examples |
| title_exact_search | Accelerating MATLAB with GPU computing a primer with examples |
| title_full | Accelerating MATLAB with GPU computing a primer with examples Jung W. Suh, Youngmin Kim |
| title_fullStr | Accelerating MATLAB with GPU computing a primer with examples Jung W. Suh, Youngmin Kim |
| title_full_unstemmed | Accelerating MATLAB with GPU computing a primer with examples Jung W. Suh, Youngmin Kim |
| title_short | Accelerating MATLAB with GPU computing |
| title_sort | accelerating matlab with gpu computing a primer with examples |
| title_sub | a primer with examples |
| topic | MATLAB. MATLAB. fast COMPUTERS / General bisacsh Graphics processing units fast Numerical analysis / Data processing fast Datenverarbeitung Graphics processing units Numerical analysis Data processing Grafikprozessor (DE-588)4582114-8 gnd MATLAB (DE-588)4329066-8 gnd |
| topic_facet | MATLAB. COMPUTERS / General Graphics processing units Numerical analysis / Data processing Datenverarbeitung Graphics processing units Numerical analysis Data processing Grafikprozessor MATLAB |
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