fuchsia / third_party / eigen / 64baccc877717d32db291a400c2d5726402fdeb9 / . / doc / FixedSizeVectorizable.dox

namespace Eigen { | |

/** \eigenManualPage TopicFixedSizeVectorizable Fixed-size vectorizable Eigen objects | |

The goal of this page is to explain what we mean by "fixed-size vectorizable". | |

\section FixedSizeVectorizable_summary Executive Summary | |

An Eigen object is called "fixed-size vectorizable" if it has fixed size and that size is a multiple of 16 bytes. | |

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 | |

\section FixedSizeVectorizable_explanation Explanation | |

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). | |

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]". | |

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. | |

Now, vectorization (both SSE and AltiVec) works with 128-bit packets. Moreover, for performance reasons, these packets need to be have 128-bit alignment. | |

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. | |

*/ | |

} |