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Related papers: Accelerating CCSD(T) on Graphical Processing Units…

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In this paper, we explore the acceleration of tensor product operations in finite element methods, leveraging the computational power of the NVIDIA A100 GPU Tensor Cores. We provide an accessible overview of the necessary mathematical…

Mathematical Software · Computer Science 2024-07-16 Cu Cui

The study and prediction of chemical reactivity is one of the most important application areas of molecular quantum chemistry. Large-scale, fully error-tolerant quantum computers could provide exact or near-exact solutions to the underlying…

Quantum Physics · Physics 2019-09-12 Michael Kühn , Sebastian Zanker , Peter Deglmann , Michael Marthaler , Horst Weiß

The extension of the highly-optimized local natural orbital (LNO) CCSD(T) method is presented for high-spin open-shell molecules. The techniques enabling the outstanding efficiency of the closed-shell LNO-CCSD(T) variant are adopted,…

Chemical Physics · Physics 2023-11-17 P. Bernát Szabó , József Csóka , Mihály Kállay , Péter R. Nagy

Computational Fluid Dynamics (CFD) is the simulation of fluid flow undertaken with the use of computational hardware. The underlying equations are computationally challenging to solve and necessitate high performance computing (HPC) to…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-04-04 Zachary Cooper-Baldock , Brenda Vara Almirall , Kiao Inthavong

Detailed analysis of efficiency and pollutant emission characteristics of practical turbulent combustion devices using complex combustion kinetics often depend on the interactions between the combustion chemistry involving both gasses…

Computational Physics · Physics 2020-05-26 Sudip Adhikari , Alan Sayre , Abhilash J Chandy

The Coupled Cluster (CC) method is used to compute the electronic correlation energy in atoms and molecules and often leads to highly accurate results. However, due to its single-reference nature, standard CC in its projected form fails to…

Monte Carlo (MC) simulation is commonly considered to be the most accurate dose calculation method in radiotherapy. However, its efficiency still requires improvement for many routine clinical applications. In this paper, we present our…

Medical Physics · Physics 2015-05-28 Xun Jia , Xuejun Gu , Yan Jiang Graves , Michael Folkerts , Steve B. Jiang

The Graphics Processing Unit (GPU) is a powerful tool for parallel computing. In the past years the performance and capabilities of GPUs have increased, and the Compute Unified Device Architecture (CUDA) - a parallel computing architecture…

Computational Physics · Physics 2009-12-17 Ferenc Molnar , Tamas Szakaly , Robert Meszaros , Istvan Lagzi

The Kernel Polynomial Method (KPM) is one of the fast diagonalization methods used for simulations of quantum systems in research fields of condensed matter physics and chemistry. The algorithm has a difficulty to be parallelized on a…

Computational Physics · Physics 2011-05-30 Shixun Zhang , Shinichi Yamagiwa , Masahiko Okumura , Seiji Yunoki

We present a General-purpose computing on graphics processing units (GPGPU) based computational program and framework for the electronic dynamics of atomic systems under intense laser fields. We present our results using the case of…

Computational Physics · Physics 2014-03-25 Cathal Ó Broin , L. A. A Nikolopoulos

Path integral Monte Carlo (PIMC) and path integral molecular dynamics (PIMD) provide the golden standard for the ab initio simulations of identical particles. In this work, we achieved significant GPU acceleration based on PIMD, which is…

Computational Physics · Physics 2026-03-31 Yunuo Xiong

We report the implementation of electronic excited states for semi-empirical quantum chemical methods at the configuration interaction singles (CIS) and time-dependent Hartree-Fock (TDHF) level of theory in the PySEQM software. Built on…

Tensor cores (TCs) are a type of Application-Specific Integrated Circuit (ASIC) and are a recent addition to Graphics Processing Unit (GPU) architectures. As such, TCs are purposefully designed to greatly improve the performance of Matrix…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-11-21 Benoit Gallet , Michael Gowanlock

Using GPU-accelerated state-vector emulation, we propose to embed a quantum computing ansatz into density-functional theory via density-based basis-set corrections (DBBSC) to obtain quantitative quantum-chemistry results on molecules that…

Recently, graph neural networks (GNNs), as the backbone of graph-based machine learning, demonstrate great success in various domains (e.g., e-commerce). However, the performance of GNNs is usually unsatisfactory due to the highly sparse…

Machine Learning · Computer Science 2023-06-02 Yuke Wang , Boyuan Feng , Zheng Wang , Guyue Huang , Yufei Ding

Many computational methods in ab initio quantum chemistry are formulated in terms of high-order tensor contractions, whose cost determines the size of system that can be studied. We introduce stochastic tensor contraction to perform such…

Chemical Physics · Physics 2026-05-11 Jiace Sun , Garnet Kin-Lic Chan

We present an approach to molecular-dynamics simulations of ferrofluids on graphics processing units (GPUs). Our numerical scheme is based on a GPU-oriented modification of the Barnes-Hut (BH) algorithm designed to increase the parallelism…

Computational Physics · Physics 2013-04-30 A. Yu. Polyakov , T. V. Lyutyy , S. Denisov , V. V. Reva , P. Hanggi

Basis set convergence of correlation effects on molecular atomization energies beyond the CCSD (coupled cluster with singles and doubles) approximation has been studied near the one-particle basis set limit. Quasiperturbative connected…

Chemical Physics · Physics 2008-08-17 Amir Karton , Peter R. Taylor , Jan M. L. Martin

We present the working equations for a reduced-scaling method of evaluating the perturbative triples (T) energy in coupled-cluster theory, through the tensor hypercontraction (THC) of the triples amplitudes ($t_{ijk}^{abc}$). Through our…

Chemical Physics · Physics 2024-06-12 Andy Jiang , Justin M. Turney , Henry F. Schaefer

The clustering coefficient and the transitivity ratio are concepts often used in network analysis, which creates a need for fast practical algorithms for counting triangles in large graphs. Previous research in this area focused on…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-08-09 Adam Polak
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