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							38 lines
						
					
					
						
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				| namespace Eigen { | |
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| /** \eigenManualPage TopicFixedSizeVectorizable 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: | |
| \li Eigen::Vector2d | |
| \li Eigen::Vector4d | |
| \li Eigen::Vector4f | |
| \li Eigen::Matrix2d | |
| \li Eigen::Matrix2f | |
| \li Eigen::Matrix4d | |
| \li Eigen::Matrix4f | |
| \li Eigen::Affine3d | |
| \li Eigen::Affine3f | |
| \li Eigen::Quaterniond | |
| \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 objects, 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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