Roman Shakhov

Google Summer of Code Student 2020


Education: Mathematics and Computer Science, Voronezh State University, Russia

project: Extend clad to compute Jacobians
In mathematics and computer algebra, automatic differentiation (AD) is a set of techniques to numerically evaluate the derivative of a function specified by a computer program. Automatic differentiation is an alternative technique to Symbolic differentiation and Numerical differentiation (the method of finite differences). CLAD is based on Clang which will provide the necessary facilities for code transformation. The AD library is able to differentiate non-trivial functions, to find a partial derivative for trivial cases and has good unit test coverage. Currently, clad does not provide an easy way to compute Jacobians.

Project Proposal: URL

Project Reports: Poster

Mentors: Vassil Vassilev, Alexander Penev