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Accelerating MATLAB Performance

Yair M. Altman
€81.99
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advanced MATLAB speed improvement guide
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algorithm performance analysis
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Author_Yair M. Altman
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Category1=Non-Fiction
Category=UB
Category=UY
cell
Cell Array
code
compiled code acceleration
Computer Science
COP=United Kingdom
CUDA Kernel
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Engineering
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file
functions
GPU
GPU Device
GPU Memory
GUI Control
Language_English
Mathematics
MATLAB
MATLAB Editor
MATLAB File Exchange
MATLAB Function
MATLAB Memory
MATLAB Path
MATLAB Release
MATLAB Session
MATLAB Worker
memory management strategies
mex
MEX File
Mex Function
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parallel processing techniques
Performance Hotspot
Performance Tuning
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scientific computing optimization
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vectorization methods

Product details

  • ISBN 9781032917528
  • Weight: 1620g
  • Dimensions: 178 x 254mm
  • Publication Date: 14 Oct 2024
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
  • Language: English
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Description

The MATLAB® programming environment is often perceived as a platform suitable for prototyping and modeling but not for "serious" applications. One of the main complaints is that MATLAB is just too slow.

Accelerating MATLAB Performance aims to correct this perception by describing multiple ways to greatly improve MATLAB program speed. Packed with thousands of helpful tips, it leaves no stone unturned, discussing every aspect of MATLAB.

Ideal for novices and professionals alike, the book describes MATLAB performance in a scale and depth never before published. It takes a comprehensive approach to MATLAB performance, illustrating numerous ways to attain the desired speedup.

The book covers MATLAB, CPU, and memory profiling and discusses various tradeoffs in performance tuning. It describes both the application of standard industry techniques in MATLAB, as well as methods that are specific to MATLAB such as using different data types or built-in functions.

The book covers MATLAB vectorization, parallelization (implicit and explicit), optimization, memory management, chunking, and caching. It explains MATLAB’s memory model and details how it can be leveraged. It describes the use of GPU, MEX, FPGA, and other forms of compiled code, as well as techniques for speeding up deployed applications. It details specific tips for MATLAB GUI, graphics, and I/O. It also reviews a wide variety of utilities, libraries, and toolboxes that can help to improve performance.

Sufficient information is provided to allow readers to immediately apply the suggestions to their own MATLAB programs. Extensive references are also included to allow those who wish to expand the treatment of a particular topic to do so easily.

Supported by an active website, and numerous code examples, the book will help readers rapidly attain significant reductions in development costs and program run times.

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