Logo Logo
Switch Language to German

Drontschenko, Viktoria; Graf, Daniel; Laqua, Henryk and Ochsenfeld, Christian (2021): Lagrangian-Based Minimal-Overhead Batching Scheme for the Efficient Integral-Direct Evaluation of the RPA Correlation Energy. In: Journal of Chemical Theory and Computation, Vol. 17, No. 9: pp. 5623-5634

Full text not available from 'Open Access LMU'.


A highly memory-efficient integral-direct random phase approximation (RPA) method based on our omega-CDGD-RI-RPA method [Graf, D. et al. J. Chem. Theory Comput. 2018, 14, 2505] is presented that completely alleviates the memory bottleneck of storing the multidimensional three-center integral tensor, which severely limited the tractable system sizes. Based on a Lagrangian formulation, we introduce an optimized batching scheme over the auxiliary and basis-function indices, which allows to compute the optimal number of batches for a given amount of system memory, while minimizing the batching overhead. Thus, our optimized batching constitutes the best tradeoff between program runtime and memory demand. Within this batching scheme, the half-transformed three-center integral tensor B-i mu(M) is recomputed for each batch of auxiliary and basis functions. This allows the computation of systems that were out of reach before. The largest system within this work consists of a DNA fragment comprising 1052 atoms and 11 230 basis functions calculated on a single node, which emphasizes the new possibilities of our integral-direct RPA method.

Actions (login required)

View Item View Item