Abhi Acherjee

IRIS-HEP Fellow

email: acherjan@mail.uc.edu

Education: Computer Sciences B.S. + M.S , University of Cincinnati, OH

Ongoing project: Extend the Automatic Differentiation Support in RooFit
In terms of minimization time, Roofit offers faster results even with numerical differentiation techniques as compared to minimizing a likelihood function that is written by hand in C++, due its complex caching logic. Automatic differentiation gives an additional speedup and more accuracy and scalability for problems with large number of parameters. The purpose of this project will be to firstly use Minuit as an optimization algorithm with externally provided gradients, extend support to cover HistFactory and other parts of RooFit, and finally to optimize Clad generated derivatives a nd further explore how they can be parallelized (OpenMP or CUDA).

Project Proposal: URL

Mentors: Vassil Vassilev, David Lange

Presentations



Extending Automatic Differentiation Support in RooFit. Roadmap, Slides, Team Meeting, 6 September 2023
Extending Automatic Differentiation Support in RooFit. Roadmap, Slides, Team Meeting, 6 September 2023