ERmod‐OpenACC: GPU Acceleration of Solvation Free Energy Calculation With Energy‐Representation Theory

ERmod-OpenACC is a GPU-accelerated implementation of a calculation package for the solvation free energy. In the implementation, the most computationally intensive processes-the calculation of the pair energies and the construction of the correlation function-have been optimized for GPUs. ERmod-OpenACC also supports single precision to maximize performance on RTX series GPUs, which are commonly used in molecular dynamics simulations. A common problem with OpenACC is data transfer between the CPU and GPU. By minimizing data transfer, the package's performance has been significantly improved. Compared to a single Xeon core (3.1 GHz), ERmod-OpenACC achieves a speedup of up to approximately <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mn>16</mml:mn> <mml:mo>.</mml:mo> <mml:mn>5</mml:mn> <mml:mo>×</mml:mo></mml:mrow> <mml:annotation>$$ 16.5\times $$</mml:annotation></mml:semantics> </mml:math> when running on RTX 4080 SUPER. The package also supports multiple GPUs via MPI, achieving a speedup of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mn>2</mml:mn> <mml:mo>×</mml:mo></mml:mrow> <mml:annotation>$$ 2\times $$</mml:annotation></mml:semantics> </mml:math> with 2 GPUs and approximately <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mn>14</mml:mn> <mml:mo>.</mml:mo> <mml:mn>5</mml:mn> <mml:mo>×</mml:mo></mml:mrow> <mml:annotation>$$ 14.5\times $$</mml:annotation></mml:semantics> </mml:math> with 16 GPUs. The only external library required to compile ERmod-ACC is NVIDIA HPC SDK. The package is available at https://github.com/drmaruyama/ermod-openacc.

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Publication Details

Journal
Journal of Computational Chemistry
Published
2025-06-08
DOI
https://doi.org/10.1002/jcc.70152
Citations
2
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
1.04

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article

ERmod‐OpenACC: GPU Acceleration of Solvation Free Energy Calculation With Energy‐Representation Theory

Yutaka Maruyama, Nobuyuki Matubayasi, H. Kojima
2 citations
Journal of Computational Chemistry
Machine Learning in Materials Science
1.04
article

ERmod‐OpenACC: GPU Acceleration of Solvation Free Energy Calculation With Energy‐Representation Theory

Yutaka Maruyama, Nobuyuki Matubayasi, H. Kojima
article en
2 citations

Abstract

ERmod-OpenACC is a GPU-accelerated implementation of a calculation package for the solvation free energy. In the implementation, the most computationally intensive processes-the calculation of the pair energies and the construction of the correlation function-have been optimized for GPUs. ERmod-OpenACC also supports single precision to maximize performance on RTX series GPUs, which are commonly used in molecular dynamics simulations. A common problem with OpenACC is data transfer between the CPU and GPU. By minimizing data transfer, the package's performance has been significantly improved. Compared to a single Xeon core (3.1 GHz), ERmod-OpenACC achieves a speedup of up to approximately <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mn>16</mml:mn> <mml:mo>.</mml:mo> <mml:mn>5</mml:mn> <mml:mo>×</mml:mo></mml:mrow> <mml:annotation>$$ 16.5\times $$</mml:annotation></mml:semantics> </mml:math> when running on RTX 4080 SUPER. The package also supports multiple GPUs via MPI, achieving a speedup of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mn>2</mml:mn> <mml:mo>×</mml:mo></mml:mrow> <mml:annotation>$$ 2\times $$</mml:annotation></mml:semantics> </mml:math> with 2 GPUs and approximately <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mn>14</mml:mn> <mml:mo>.</mml:mo> <mml:mn>5</mml:mn> <mml:mo>×</mml:mo></mml:mrow> <mml:annotation>$$ 14.5\times $$</mml:annotation></mml:semantics> </mml:math> with 16 GPUs. The only external library required to compile ERmod-ACC is NVIDIA HPC SDK. The package is available at https://github.com/drmaruyama/ermod-openacc.

Journal of Computational ChemistryVol. 46(16)
Maruho (Japan) (JP), The University of Osaka (JP)
Ministry of Education, Culture, Sports, Science and Technology, University of Tsukuba, Japan Society for the Promotion of Science
Affordable and clean energy
Openalex Percentile: Top 25%
Machine Learning in Materials Science
1.04
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