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44a527dfa5
by tweaking the filename and adding 2 categories:
Troubleshooting and Advanced
* use the EXCLUDE_SYMBOLS to clean the class list
(insteaded of a homemade bash script)
* remove the broken "exemple list"
* re-structure the unsupported directory as mentionned in the ML and
integrate the doc as follow:
- snippets of the unsupported directory are directly imported from the
main snippets/CMakefile.txt (no need to duplicate code)
- add a top level "Unsupported modules" group
- unsupported modules have to defined their own sub group and nest it
using \ingroup Unsupported_modules
- then a pair of //@{ //@} will put everything in the submodule
- this is just a proposal !
39 lines
1.6 KiB
Plaintext
39 lines
1.6 KiB
Plaintext
namespace Eigen {
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/** \page FixedSizeVectorizable Advanced - Fixed-size vectorizable Eigen objects
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The goal of this page is to explain what we mean by "fixed-size vectorizable".
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\section summary Executive Summary
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An Eigen object is called "fixed-size vectorizable" if it has fixed size and that size is a multiple of 16 bytes.
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Examples include:
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\li Eigen::Vector2d
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\li Eigen::Vector4d
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\li Eigen::Vector4f
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\li Eigen::Matrix2d
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\li Eigen::Matrix2f
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\li Eigen::Matrix4d
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\li Eigen::Matrix4f
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\li Eigen::Transform3d
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\li Eigen::Transform3f
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\li Eigen::Quaterniond
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\li Eigen::Quaternionf
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\section explanation Explanation
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First, "fixed-size" should be clear: an Eigen object has fixed size if its number of rows and its number of columns are fixed at compile-time. So for example Matrix3f has fixed size, but MatrixXf doesn't (the opposite of fixed-size is dynamic-size).
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The array of coefficients of a fixed-size Eigen object is a plain "static array", it is not dynamically allocated. For example, the data behind a Matrix4f is just a "float array[16]".
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Fixed-size objects are typically very small, which means that we want to handle them with zero runtime overhead -- both in terms of memory usage and of speed.
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Now, vectorization (both SSE and AltiVec) works with 128-bit packets. Moreover, for performance reasons, these packets need to be have 128-bit alignment.
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So it turns out that the only way that fixed-size Eigen objects can be vectorized, is if their size is a multiple of 128 bits, or 16 bytes. Eigen will then request 16-byte alignment for these object, and henceforth rely on these objects being aligned so no runtime check for alignment is performed.
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*/
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}
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