1 namespace Eigen { 2 3 /** \page TopicFixedSizeVectorizable Fixed-size vectorizable Eigen objects 4 5 The goal of this page is to explain what we mean by "fixed-size vectorizable". 6 7 \section summary Executive Summary 8 9 An Eigen object is called "fixed-size vectorizable" if it has fixed size and that size is a multiple of 16 bytes. 10 11 Examples include: 12 \li Eigen::Vector2d 13 \li Eigen::Vector4d 14 \li Eigen::Vector4f 15 \li Eigen::Matrix2d 16 \li Eigen::Matrix2f 17 \li Eigen::Matrix4d 18 \li Eigen::Matrix4f 19 \li Eigen::Affine3d 20 \li Eigen::Affine3f 21 \li Eigen::Quaterniond 22 \li Eigen::Quaternionf 23 24 \section explanation Explanation 25 26 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). 27 28 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]". 29 30 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. 31 32 Now, vectorization (both SSE and AltiVec) works with 128-bit packets. Moreover, for performance reasons, these packets need to be have 128-bit alignment. 33 34 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. 35 36 */ 37 38 } 39
