Webinar 42 by István Ladjánszki: GPU Computing with Q-Chem and BrianQC

Abstract

The BrianQC project aims to exploit the enormous raw power of GPUs in the field of quantum chemistry. For this, we tailored several widely used algorithms to the special features of GPUs to get the most out of this massively parallel hardware. The capabilities currently implemented include one- and two-electron integral evaluation over Gaussian type orbital (GTO) basis functions, exchange-correlation density functionals and quadrature for density functional theory (DFT), Hartree-Fock nuclear gradients, parts of the coupled perturbed Hartree-Fock (CPHF) equations and vibrational analysis, DIIS algorithm, efficient Fock matrix diagonalization, initial SCF guesses besides others. In this webinar, we would like to present our work emphasizing the most recent advances in capabilities and performance. We will introduce the main techniques behind our software, present benchmark results, and discuss upcoming features to be included in the future.

About the presenter

István Ladjánszki is the Chief Scientist of the BrianQC project, works in the field of high-speed GPU implementation of quantum chemistry-related calculations. He received his degree in theoretical physics from the Budapest University of Technology and Economics (BUTE) in 2011. His thesis on Reduced scaling Hartree-Fock calculations using tensor decomposition and neural network was awarded first prize on the National Scientific Students’ Associations Conference. From 2010 to 2013 he worked at BUTE as an associate researcher on the MRCC quantum chemistry program package. He has experience in the implementation of quantum chemistry-related integral and Hartree-Fock level approximation codes and machine learning methods.

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