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Molecular Physics
An International Journal at the Interface Between Chemistry and Physics
Volume 119, 2021 - Issue 21-22: Special Issue of Molecular Physics in Honour of John Stanton
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John Stanton Special Issue: Theory Meets Experiment

Energy correction and analytic energy gradients due to triples in CCSD(T) with spin–orbit coupling on graphic processing units using single-precision data

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Article: e1974591 | Received 11 Jun 2021, Accepted 18 Aug 2021, Published online: 07 Sep 2021
 

ABSTRACT

Calculating the contribution of triples ((T)) to the correlation energy, the density matrices and the constant terms in the Λ equation is the most expensive steps in obtaining analytic energy gradients for the CCSD(T) approach. In this work, we report the implementation of these steps for the CCSD(T) method with spin–orbit coupling (SOC) included in post-self-consistent-field calculations (SOC-CCSD(T)) using single-precision data on a consumer GPU card to accelerate calculations. The developed program can be used for calculations on GPU with single-precision data or on CPU with either single- or double-precision data. According to our results, calculating the (T) correlation energy in SOC-CCSD(T) on GPU with single-precision data is about 7–10 times faster for the investigated molecules than that on CPU with double-precision data, and it is 5–9 times faster in calculating the (T) part of analytic energy gradients for the SOC-CCSD(T) method. Our results indicate that loss of accuracy for energy gradients and equilibrium structures using single-precision data is negligible, while a mixed-precision calculation is needed for the (T) correlation energy. In calculating harmonic frequencies based on finite difference of analytic energy gradients, a larger step size is required to achieve accurate results for certain vibrational modes with single-precision data.

GRAPHICAL ABSTRACT

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the National Natural Science Foundation of China (Nos. 21773160 and 21703020).

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