2024
DOI: 10.1016/j.cpc.2023.108946
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A multi-GPU implementation of Real-Time Time-Dependent Auxiliary Density Functional Theory for the investigation of nanosystems irradiations

Pablo Antonio Martínez,
Theresa Vock,
Liliane Racha Kharchi
et al.
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Cited by 5 publications
(5 citation statements)
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“…In a last section, we have then described currently ongoing time resolved measurements to study radiation‐induced molecular processes in DNA and future perspectives using FEL facilities. We anticipate that an increased collaboration between theoreticians and experimentalists will allow significant progress in the field, notably regarding charge transfer and energy deposition, for instance thanks to state‐of‐the‐art methods using graphical processor units to run parallelized calculations using time‐dependent density‐functional theory [60] …”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…In a last section, we have then described currently ongoing time resolved measurements to study radiation‐induced molecular processes in DNA and future perspectives using FEL facilities. We anticipate that an increased collaboration between theoreticians and experimentalists will allow significant progress in the field, notably regarding charge transfer and energy deposition, for instance thanks to state‐of‐the‐art methods using graphical processor units to run parallelized calculations using time‐dependent density‐functional theory [60] …”
Section: Discussionmentioning
confidence: 99%
“…We anticipate that an increased collaboration between theoreticians and experimentalists will allow significant progress in the field, notably regarding charge transfer and energy deposition, for instance thanks to state-of-the-art methods using graphical processor units to run parallelized calculations using timedependent density-functional theory. [60]…”
Section: Discussionmentioning
confidence: 99%
“…In the case depicted in Figure 3, one could use up to 400 CPUs with appreciable gain and to further strongly decrease the cost of the simulation [19]. To go one step beyond in terms of efficiency, we have recently developed a hybrid CPU/GPU code with very encouraging results [86]. In our current implementation, matrix Note the change of scale between the two graphs.…”
Section: High-performance Computingmentioning
confidence: 99%
“…In our current implementation, matrix Note the change of scale between the two graphs. Adapted with permission from [79] and [86].…”
Section: High-performance Computingmentioning
confidence: 99%
“…All simulations have been carried out with our multi-GPU implementation of RT-TD-DFT in the deMon2k code (version 6.1.6) using 4 GPU and 40 CPU or 8 GPU and 64 CPU . For electronic integral calculations, we used a mixed scheme for electronic repulsion and adaptive grids of high accuracy for the exchange-correlation contributions (10 –7 Ha, following deMon2k nomenclature). , deMon2k relies on the auxiliary DFT formalism (ADFT) whereby variationally fitted electron densities are introduced to avoid cumbersome four-index electronic-repulsion-integral calculations and to simplify the numerical integration of XC contributions.…”
Section: Gaussian-type Orbitals For the Continuummentioning
confidence: 99%