High-Performance Evaluation of High Angular Momentum 4-Center Gaussian Integrals on Modern Accelerated Processors

Asadchev, Andrey; Valeev, Edward F.

doi:10.1021/acs.jpca.3c04574

J. Phys. Chem. A

2023

DOI: 10.1021/acs.jpca.3c04574

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High-Performance Evaluation of High Angular Momentum 4-Center Gaussian Integrals on Modern Accelerated Processors

Andrey Asadchev,

Edward F. Valeev

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2024

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Cited by 7 publications

References 51 publications

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GPU Acceleration of the Boys Function Evaluation in Computational Quantum Chemistry

Tsuji,

Ito,

Nakano

et al. 2024

Concurrency and Computation

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The Boys function, a mathematical integral function, plays a pivotal role and is frequently evaluated in ab initio molecular orbital computations. The main contribution of this paper is to accelerate the bulk evaluation of the Boys function through the effective utilization of GPUs. The proposed GPU implementation addresses GPU‐specific programming issues such as warp divergence and coalesced/stride access to global memory, and we employ the optimal numerical evaluation method from four methods based on input values to ensure efficient computation with sufficient accuracy. Moreover, to consider actual computation of molecular integrals, we have implemented and evaluated the proposed method in two scenarios: single evaluation, which computes a single value of the Boys function for a single input, and incremental evaluation, which computes multiple values of the Boys function incrementally. The execution time of the proposed GPU implementation was evaluated for both scenarios using an NVIDIA A100 Tensor Core GPU. As a result, the GPU‐accelerated bulk evaluation has achieved a throughput of computing the values of the Boys function times per second for the single evaluation and times per second for the incremental evaluation, respectively. Our parallelized CPU and GPU implementation is available at https://github.com/sstsuji/Boys‐function‐GPU‐library.

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GPU Acceleration of the Boys Function Evaluation in Computational Quantum Chemistry

Tsuji,

Ito,

Nakano

et al. 2024

Concurrency and Computation

View full text Add to dashboard Cite

show abstract

Multi-GPU RI-HF Energies and Analytic Gradients─Toward High-Throughput Ab Initio Molecular Dynamics

Stocks,

Palethorpe,

Barca

2024

J. Chem. Theory Comput.

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Acceleration without Disruption: DFT Software as a Service

Ju,

Wei,

Huang

et al. 2024

J. Chem. Theory Comput.

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Density functional theory (DFT) has been a cornerstone in computational chemistry, physics, and materials science for decades, benefiting from advancements in computational power and theoretical methods. This paper introduces a novel, cloud-native application, Accelerated DFT, which offers an order of magnitude acceleration in DFT simulations. By integrating state-of-the-art cloud infrastructure and redesigning algorithms for graphic processing units (GPUs), Accelerated DFT achieves highspeed calculations without sacrificing accuracy. It provides a userfriendly and scalable solution for the increasing demands of DFT calculations in scientific communities. The implementation details, examples, and benchmark results illustrate how Accelerated DFT can significantly expedite scientific discovery across various domains.

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High-Performance Evaluation of High Angular Momentum 4-Center Gaussian Integrals on Modern Accelerated Processors

Cited by 7 publications

References 51 publications

GPU Acceleration of the Boys Function Evaluation in Computational Quantum Chemistry

GPU Acceleration of the Boys Function Evaluation in Computational Quantum Chemistry

Multi-GPU RI-HF Energies and Analytic Gradients─Toward High-Throughput Ab Initio Molecular Dynamics

Acceleration without Disruption: DFT Software as a Service

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