![]() Since Eigen takes care of declaring 128-bit alignment, all members that need it are automatically 128-bit aligned relatively to the class. Should I then put all the members of Eigen types at the beginning of my class? The solution is to let class Foo have an aligned "operator new", as we showed in the previous section. If the foo pointer wasn't aligned, then foo->v won't be aligned either! The alignment attribute of the member v is then relative to the start of the class, foo. Eigen matrices have a range of methods that reduce them to a vector or even a. An eigenvector associated with 1 is a nontrivial solutionv1 to. ![]() When you have a class Foo like above, and you dynamically allocate a new Foo as above, then, since Foo doesn't have aligned "operator new", the returned pointer foo is not necessarily 128-bit aligned. Now consider the problem of finding the eigenvectors for the eigenvalues 1 and 2. Matrix ), pybind11 returns the vector as a 2D array to numpy.Thus, normally, you don't have to worry about anything, Eigen handles alignment for you. Eigen is C++ header-based library for dense and sparse linear algebra. As a learning exercise, creating a matrix class can be extremely beneficial as it often covers dynamic memory allocation (if not using std::vector s) and.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |