Demonstrates GPU-accelerated TDDFT efficiency in large molecule excited-state calculations, suggesting a new computational method.
We introduce a GPU-accelerated implementation of time-dependent density functional theory with the minimal auxiliary basis approach (TDDFT-risp) in GPU4PySCF, together with large system demonstrations carried out using the Tamm-Dancoff approximation (TDA-risp). The method combines GPU-accelerated three-center integral evaluation, tensor contractions, exchange-space truncation, omission of hydrogen atoms from the auxiliary basis, and a host memory assisted Davidson solver. On a benchmark test set of 42 molecules (13-99 atoms), a conservative 40 eV exchange cutoff yields excitation-energy errors relative to standard TDA of about 0.03-0.05 eV for low-lying states. For systems of 300 to 3000 atoms, we demonstrate that TDA-risp calculations of 15 low-lying excited states with ωB97XD/def2-SVP complete on a single A100 GPU with wall times ranging from minutes to hours. Relative to RIJCOSX TDDFT in ORCA (32 MPI processes), GPU TDA-risp yields wall-time speedups of roughly 140-340× on systems with 72-480 atoms, using ωB97X-D3BJ/def2-TZVP. These results position GPU-TDDFT-risp as a practical route toward excited-state calculations for large organic and biomolecular systems with thousands of atoms.
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Zhou et al. (2026) studied this question.
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