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<div class="chapter" id="Vectorization-and-Faster-Code-Execution">
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Next: <a href="Nonlinear-Equations.html" accesskey="n" rel="next">Nonlinear Equations</a>, Previous: <a href="Linear-Algebra.html" accesskey="p" rel="prev">Linear Algebra</a> [<a href="index.html#SEC_Contents" title="Table of contents" rel="contents">Contents</a>][<a href="Concept-Index.html" title="Index" rel="index">Index</a>]</p>
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<span id="Vectorization-and-Faster-Code-Execution-1"></span><h2 class="chapter">19 Vectorization and Faster Code Execution</h2>
<span id="index-vectorization"></span>
<span id="index-vectorize"></span>
<p>Vectorization is a programming technique that uses vector operations
instead of element-by-element loop-based operations. Besides frequently
producing more succinct Octave code, vectorization also allows for better
optimization in the subsequent implementation. The optimizations may occur
either in Octave’s own Fortran, C, or C++ internal implementation, or even at a
lower level depending on the compiler and external numerical libraries used to
build Octave. The ultimate goal is to make use of your hardware’s vector
instructions if possible or to perform other optimizations in software.
</p>
<p>Vectorization is not a concept unique to Octave, but it is particularly
important because Octave is a matrix-oriented language. Vectorized
Octave code will see a dramatic speed up (10X–100X) in most cases.
</p>
<p>This chapter discusses vectorization and other techniques for writing faster
code.
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<li><a href="Basic-Vectorization.html" accesskey="1">Basic Vectorization</a></li>
<li><a href="Broadcasting.html" accesskey="2">Broadcasting</a></li>
<li><a href="Function-Application.html" accesskey="3">Function Application</a></li>
<li><a href="Accumulation.html" accesskey="4">Accumulation</a></li>
<li><a href="Miscellaneous-Techniques.html" accesskey="5">Miscellaneous Techniques</a></li>
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