High-Performance, Graphics Processing Unit-Accelerated Fock Build Algorithm

Barca, Giuseppe M. J.; Galvez-Vallejo, Jorge L.; Poole, David; Rendell, Alistair P.; Gordon, Mark S.

doi:10.1021/acs.jctc.0c00768

Cited by 33 publications

(29 citation statements)

References 27 publications

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“…The power of multi-GPUs has been harnessed into a range of traditional computational chemistry tools, [3][4][5][6][7][8][9][10][11][12] however, only a handful of ab initio quantum chemical packages [9][10][11][12][13] are among them. Meanwhile, with multi-GPU nodes increasingly becoming common in contemporary supercomputer centers, opensource quantum chemical codes that can fully exploit their power are in demand.…”

Section: Introductionmentioning

confidence: 99%

“…A second, but a hybrid ERI engine, has been developed by Kussman and Ochsenfeld, 10 and quite recently, a fragmentation based Fock build algorithm with dynamic load balancing has been reported by Gordon and coworkers. 12 In the context of XC parallelization on multi-GPUs, Williams-Young et al 11 has documented a three level parallelization scheme. In such a scheme, the load balancing is achieved by pre-estimating the FLOPs incurred by batches of grid points.…”

Section: Introductionmentioning

confidence: 99%

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Harnessing the Power of Multi-GPU Acceleration into the Quantum Interaction Computational Kernel Program

Manathunga

Jin

Cruzeiro

et al. 2021

J. Chem. Theory Comput.

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We report a new multi-GPU capable ab initio Hartree-Fock/density functional theory implementation integrated into the open source QUantum Interaction Computational Kernel (QUICK) program. Details on the load balancing algorithms for electron repulsion integrals and exchange correlation quadrature across multiple GPUs are described. Benchmarking studies carried out on up to 4 GPU nodes, each containing 4 NVIDIA V100-SMX2 type GPUs demonstrate that our implementation is capable of achieving excellent load balancing and high parallel efficiency. For representative medium to large size protein/organic molecular systems, the observed efficiencies remained above 86%. The accelerations on NVIDIA A100, P100 and K80 platforms also have realized parallel efficiencies higher than 74%, paving the way for large-scale ab initio electronic structure calculations.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Harnessing the Power of Multi-GPU Acceleration into the Quantum Interaction Computational Kernel Program

Manathunga

Jin

Cruzeiro

et al. 2021

J. Chem. Theory Comput.

View full text Add to dashboard Cite

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“…Over the last few decades, an immense research effort directed towards the development of GPU accelerated Gaussian basis set KS-DFT, [268][269][270][271][272][273] a majority of which has been focused on the development of highly efficient algorithms for the evaluation and digestion of the electron repulsion integrals (ERI) required for the formation of the Coulomb and explicit exchange components of the Fock matrix. 61,65,255,268,[274][275][276][277][278][279][280] A major component of this effort in NWChemEx has been the development of an efficient and highly scalable algorithm for the numerical integration of the XC potential on clusters of GPU accelerators. 281 The key component of this algorithm is the reliance on highly tuned, microarchitecture optimized implementations of GPU accelerated batched level-3 BLAS operations such as matrix multiply (GEMM) and symmetric rank-2k updates (SYR2K)…”

Section: Newton-krylov Solver For Coupled-cluster Equationsmentioning

confidence: 99%

From NWChem to NWChemEx: Evolving with the Computational Chemistry Landscape

et al. 2021

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Since the advent of the first computers, chemists have been at the forefront of using computers to understand and solve complex chemical problems. As the hardware and software have evolved, so have the theoretical and computational chemistry methods and algorithms. Parallel computers clearly changed the common computing paradigm in the late 1970s and 80s, and the field has again seen a paradigm shift with the advent of graphical processing units. This review explores the challenges and some of the solutions in transforming software from the terascale to the petascale and now to the upcoming exascale computers. While discussing the field in general, NWChem and its redesign, NWChemEx, will be highlighted as one of the early co-design projects to take advantage of massively parallel computers and emerging software standards to enable large scientific challenges to be tackled.

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“…The HF-3c method uses three separate geometry-dependent formulas 38,39 to add energy corrections ("3c") for the various deficiencies of minimal basis set HF: one to account for some of the missing dispersion interactions, and two to mitigate the effects of basis set incompleteness errors. Several other techniques have been proposed in the literature [40][41][42][43][44][45][46][47][48][49][50][51][52][53][54] , reflecting the interest in developing computationally inexpensive methods for large systems.…”

Section: Introductionmentioning

confidence: 99%

Fast and accurate quantum mechanical modeling of large molecular systems using small basis set Hartree–Fock methods corrected with atom-centered potentials

Prasad

Otero-de-la-Roza

DiLabio

2022

Preprint

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There has been significant interest in developing fast and accurate quantum mechanical methods for modeling large molecular systems. In this work, by utilizing a machine-learning regression technique, we have developed new low-cost quantum mechanical approaches to model large molecular systems. The developed approaches rely on using one-electron Gaussian-type functions called atom-centered potentials (ACPs) to correct for the basis set incompleteness and the lack of correlation effects in the underlying minimal or small basis set Hartree-Fock (HF) methods. In particular, ACPs are proposed for ten elements common in organic and bio-organic chemistry (H, B, C, N, O, F, Si, P, S, and Cl) and four different base methods: two minimal basis sets (MINIs and MINIX) plus a double-ζ basis set (6-31G*) in combination with dispersion-corrected HF (HF-D3/MINIs, HF-D3/MINIX, HF-D3/6-31G*), and the HF-3c method. The new ACPs are trained on a very large set (73832 data points) of non-covalent properties (interaction and conformational energies) and validated additionally on a set of 32048 data points. All reference data is of complete basis set coupled-cluster quality, mostly CCSD(T)/CBS. The proposed ACP-corrected methods are shown to give errors in the tenths of a kcal/mol range for non-covalent interaction energies and up to 2 kcal/mol for molecular conformational energies. More importantly, the average errors are similar in the training and validation sets, confirming the robustness and applicability of these methods outside the boundaries of the training set. In addition, the performance of the new ACP-corrected methods is similar to complete basis set DFT but at a cost that is orders of magnitude lower, and the proposed ACPs can be used in any computational chemistry program that supports effective-core potentials without modification. It is also shown that ACPs improve the description of covalent and non-covalent bond geometries of the underlying methods and that the improvement brought about by the application of the ACPs is directly related to the number of atoms to which they are applied, allowing the treatment of systems containing some atoms for which ACPs are not available. Overall, the ACP-corrected methods proposed in this work constitute an alternative accurate, economical, and reliable quantum mechanical approach to describe the geometries, interaction energies, and conformational energies of systems with hundreds to thousands of atoms.

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High-Performance, Graphics Processing Unit-Accelerated Fock Build Algorithm

Cited by 33 publications

References 27 publications

Harnessing the Power of Multi-GPU Acceleration into the Quantum Interaction Computational Kernel Program

Harnessing the Power of Multi-GPU Acceleration into the Quantum Interaction Computational Kernel Program

From NWChem to NWChemEx: Evolving with the Computational Chemistry Landscape

Fast and accurate quantum mechanical modeling of large molecular systems using small basis set Hartree–Fock methods corrected with atom-centered potentials

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