Enabling Fortran Standard Parallelism in GAMESS for Accelerated Quantum Chemistry Calculations

Alkan, Melisa; Pham, Buu Q.; Hammond, Jeff R.; Gordon, Mark S.

doi:10.1021/acs.jctc.3c00380

Cited by 5 publications

(1 citation statement)

References 26 publications

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“…The study highlights the potential for personalized medicine and groundbreaking treatments facilitated by Nvidia's hardware. Alkan et al (2023) displayed the power of Nvidia GPUs, including HPC, A100, and V100, in accelerating complex quantum chemistry calculations. Utilizing the DO CONCURRENT (DC) feature of Fortran 2008, they achieve a 3x speedup compared to traditional offloading methods like OpenACC and OpenMP.…”

Section: Literature Reviewmentioning

confidence: 99%

A Comprehensive Analysis of Nvidia's Technological Innovations, Market Strategies, and Future Prospects

Wang,

Hsu,

Qin

2024

International Journal of Information Technologies and Systems Approach

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The article provides an in-depth analysis of Nvidia's technological evolution and its profound impact on Machine Learning, Big Data, and Artificial Intelligence (AI) on a global scale. Nvidia has emerged as a trailblazer, reshaping computational capabilities, and establishing itself as a prominent player in a fiercely competitive landscape. The examination meticulously scrutinizes the role of Nvidia's graphics processing unit (GPU) technologies in spearheading a transformative computing revolution, emphasizing the collaborative prowess inherent in Nvidia's developer ecosystem. The analysis extends to the dynamics of GPU innovation, its disruptive influence on the market, and the robust innovation engine ingrained within Nvidia's culture of calculated risk-taking. Internal and external factors contributing to Nvidia's remarkable success, and its consequential industry dominance are thoroughly investigated. Special attention is directed towards Nvidia's strategic development, technological advancements, influence on the industry, global footprint, and anticipated future implications.

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Section: Literature Reviewmentioning

confidence: 99%

A Comprehensive Analysis of Nvidia's Technological Innovations, Market Strategies, and Future Prospects

Wang,

Hsu,

Qin

2024

International Journal of Information Technologies and Systems Approach

View full text Add to dashboard Cite

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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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LibERI—A portable and performant multi-GPU accelerated library for electron repulsion integrals via OpenMP offloading and standard language parallelism

Alkan,

Pham,

Del Angel Cruz

et al. 2024

The Journal of Chemical Physics

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A portable and performant graphics processing unit (GPU)-accelerated library for electron repulsion integral (ERI) evaluation, named LibERI, has been developed and implemented via directive-based (e.g., OpenMP and OpenACC) and standard language parallelism (e.g., Fortran DO CONCURRENT). Offloaded ERIs consist of integrals over low and high contraction s, p, and d functions using the rotated-axis and Rys quadrature methods. GPU codes are factorized based on previous developments [Pham et al., J. Chem. Theory Comput. 19(8), 2213–2221 (2023)] with two layers of integral screening and quartet presorting. In this work, the density screening is moved to the GPU to enhance the computational efficacy for large molecular systems. The L-shells in the Pople basis set are also separated into pure S and P shells to increase the ERI homogeneity and reduce atomic operations and the memory footprint. LibERI is compatible with any quantum chemistry drivers supporting the MolSSI Driver Interface. Benchmark calculations of LibERI interfaced with the GAMESS software package were carried out on various GPU architectures and molecular systems. The results show that the LibERI performance is comparable to other state-of-the-art GPU-accelerated codes (e.g., TeraChem and GMSHPC) and, in some cases, outperforms conventionally developed ERI CUDA kernels (e.g., QUICK) while fully maintaining portability.

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Enabling Fortran Standard Parallelism in GAMESS for Accelerated Quantum Chemistry Calculations

Cited by 5 publications

References 26 publications

A Comprehensive Analysis of Nvidia's Technological Innovations, Market Strategies, and Future Prospects

A Comprehensive Analysis of Nvidia's Technological Innovations, Market Strategies, and Future Prospects

Acceleration without Disruption: DFT Software as a Service

LibERI—A portable and performant multi-GPU accelerated library for electron repulsion integrals via OpenMP offloading and standard language parallelism

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