StAnD: A Dataset of Linear Static Analysis Problems
This provides a resource for researchers and engineers in structural engineering to evaluate and optimize sparse linear solvers, though it is incremental as it focuses on data creation rather than new solver methods.
The authors tackled the lack of data for developing and comparing solvers for sparse linear systems in structural engineering by introducing StAnD, a dataset of 303,000 static analysis problems, and provided a benchmark comparing solver running times on CPU and GPU.
Static analysis of structures is a fundamental step for determining the stability of structures. Both linear and non-linear static analyses consist of the resolution of sparse linear systems obtained by the finite element method. The development of fast and optimized solvers for sparse linear systems appearing in structural engineering requires data to compare existing approaches, tune algorithms or to evaluate new ideas. We introduce the Static Analysis Dataset (StAnD) containing 303.000 static analysis problems obtained applying realistic loads to simulated frame structures. Along with the dataset, we publish a detailed benchmark comparison of the running time of existing solvers both on CPU and GPU. We release the code used to generate the dataset and benchmark existing solvers on Github. To the best of our knowledge, this is the largest dataset for static analysis problems and it is the first public dataset of sparse linear systems (containing both the matrix and a realistic constant term).