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This paper presents a GPU-accelerated implementation of time-dependent density functional theory with the minimal auxiliary basis approach (TDDFT-risp) within the GPU4PySCF framework. The implementation leverages GPU acceleration for three-center integral evaluation and tensor contractions, combined with exchange-space truncation and a host memory assisted Davidson solver. Benchmarking on systems of 300-3000 atoms demonstrates that the method enables TDA-risp calculations of 15 low-lying excited states with 蠅B97XD/def2-SVP on a single A100 GPU in minutes to hours, achieving errors of 0.03-0.05 eV relative to standard TDA.
Calculating excited states of molecules with thousands of atoms, previously a computational bottleneck, is now practical on a single GPU thanks to a new implementation of TDDFT-risp.
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 the EXTEST42 benchmark set, 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 $\omega$B97XD/def2-SVP complete on a single A100 GPU with wall times ranging from minutes to hours. These results position GPU-TDDFT-risp as a practical route toward excited-state calculations for large organic and biomolecular systems with thousands of atoms.
