Misc,
The Stan Math Library: Reverse-Mode Automatic Differentiation in C++
(2015)cite arxiv:1509.07164Comment: 96 pages, 9 figures.
Abstract
As computational challenges in optimization and statistical inference grow
ever harder, algorithms that utilize derivatives are becoming increasingly more
important. The implementation of the derivatives that make these algorithms so
powerful, however, is a substantial user burden and the practicality of these
algorithms depends critically on tools like automatic differentiation that
remove the implementation burden entirely. The Stan Math Library is a C++,
reverse-mode automatic differentiation library designed to be usable, extensive
and extensible, efficient, scalable, stable, portable, and redistributable in
order to facilitate the construction and utilization of such algorithms.
Usability is achieved through a simple direct interface and a cleanly
abstracted functional interface. The extensive built-in library includes
functions for matrix operations, linear algebra, differential equation solving,
and most common probability functions. Extensibility derives from a
straightforward object-oriented framework for expressions, allowing users to
easily create custom functions. Efficiency is achieved through a combination of
custom memory management, subexpression caching, traits-based metaprogramming,
and expression templates. Partial derivatives for compound functions are
evaluated lazily for improved scalability. Stability is achieved by taking care
with arithmetic precision in algebraic expressions and providing stable,
compound functions where possible. For portability, the library is
standards-compliant C++ (03) and has been tested for all major compilers for
Windows, Mac OS X, and Linux.
