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Semi-empirical quantum chemical approaches are known to compromise accuracyfor feasibility of calculations on huge molecules. However, the need forultrafast calculations in interactive quantum mechanical studies,high-throughput virtual screening, and for data-driven machine learning hasshifted the emphasis towards calculation runtimes recently. This comes with newconstraints for the software implementation as many fast calculations wouldsuffer from a large overhead of manual setup and other procedures that arecomparatively fast when studying a single molecular structure, but which becomeprohibitively slow for high-throughput demands. In this work, we discuss theeffect of various well-established semi-empirical approximations on calculationspeed and relate this to data transfer rates from the raw-data source computerto the results visualization front end. For the former, we consider desktopcomputers, local high performance computing, as well as remote cloud servicesin order to elucidate the effect on interactive calculations, for web and cloudinterfaces in local applications, and in world-wide interactive virtualsessions. The models discussed in this work have been implemented into ouropen-source software SCINE Sparrow.

Ultra-Fast Semi-Empirical Quantum Chemistry for High-Throughput Computational Campaigns with Sparrow