RESCU: a Real Space Electronic Structure Method
Vincent Michaud-Rioux, Lei Zhang, and Hong Guo

TL;DR
RESCU is an efficient MATLAB-based KS-DFT solver capable of handling thousands of atoms with modest computational resources by employing novel algorithms and optimizations that improve scalability and reduce computational costs.
Contribution
RESCU introduces a new scalable KS-DFT method that significantly improves efficiency and can handle large systems up to 14,000 atoms using modest computing resources.
Findings
Scales as approximately O(N^{2.3}) for large systems
Successfully computed electronic structures of systems with over 5,000 atoms
Achieved convergence within hours on modest computer clusters
Abstract
In this work we present RESCU, a powerful MATLAB-based Kohn-Sham density functional theory (KS-DFT) solver. We demonstrate that RESCU can compute the electronic structure properties of systems comprising many thousands of atoms using modest computer resources, e.g. 16 to 256 cores. Its computational efficiency is achieved from exploiting four routes. First, we use numerical atomic orbital (NAO) techniques to efficiently generate a good quality initial subspace which is crucially required by Chebyshev filtering methods. Second, we exploit the fact that only a subspace spanning the occupied Kohn-Sham states is required, and solving accurately the KS equation using eigensolvers can generally be avoided. Third, by judiciously analyzing and optimizing various parts of the procedure in RESCU, we delay the scaling to large , and our tests show that RESCU scales consistently as…
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