  We report on the status of GNA --- a new framework for fitting large-scale
physical models. GNA utilizes the data flow concept within which a model is
represented by a directed acyclic graph. Each node is an operation on an array
(matrix multiplication, derivative or cross section calculation, etc). The
framework enables the user to create flexible and efficient large-scale lazily
evaluated models, handle large numbers of parameters, propagate parameters'
uncertainties while taking into account possible correlations between them, fit
models, and perform statistical analysis. The main goal of the paper is to give
an overview of the main concepts and methods as well as reasons behind their
design. Detailed technical information is to be published in further works.

Mathematical Software