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Autor(en): 
  • Altman Yair M.
  • Accelerating MATLAB Performance: 1001 Tips to Speed Up MATLAB Programs 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 7-14 Tagen versandfertig
    Veröffentlichung:  Dezember 2014  
    Genre:  EDV / Informatik 
     
    advanced MATLAB speed improvement guide / algorithm performance analysis / compiled code acceleration / COMPUTERS / Mathematical & Statistical Software / Mathematical & statistical software / Mathematical and statistical software / memory management strategies / Parallel Processing Techniques
    ISBN:  9781482211290 
    EAN-Code: 
    9781482211290 
    Verlag:  Taylor and Francis 
    Einband:  Gebunden  
    Sprache:  English  
    Dimensionen:  H 254 mm / B 178 mm / D 48 mm 
    Gewicht:  1380 gr 
    Seiten:  792 
    Illustration:  schwarz-weiss Illustrationen, farbige Illustrationen, Tabellen, schwarz-weiss 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    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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