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GROMACS is one of the most widely used HPC software packages using the Molecular Dynamics (MD) simulation technique. In this work, we quantify GROMACS parallel performance using different configurations, HPC systems, and FFT libraries…

Computational Physics · Physics 2023-08-02 Måns I. Andersson , N. Arul Murugan , Artur Podobas , Stefano Markidis

We introduce a GPU-accelerated multigrid Gaussian-Plane-Wave density fitting (FFTDF) approach for efficient Fock builds and nuclear gradient evaluations within Kohn-Sham density functional theory, as implemented in the GPU4PySCF module of…

Chemical Physics · Physics 2026-03-27 Rui Li , Xing Zhang , Qiming Sun , Yuanheng Wang , Junjie Yang , Garnet Kin-Lic Chan

Ab initio molecular dynamics (AIMD) is a powerful tool to predict properties of molecular and condensed matter systems. The quality of this procedure is based on accurate electronic structure calculations. The development of quantum…

We present a new method to accelerate real time-time dependent density functional theory (rt-TDDFT) calculations with hybrid exchange-correlation functionals. For large basis set, the computational bottleneck for large scale calculations is…

Computational Physics · Physics 2019-07-24 Weile Jia , Lin Lin

Machine-learned interatomic potentials can offer near first-principles accuracy but are computationally expensive, limiting their application to large-scale molecular dynamics simulations. Inspired by quantum mechanics/molecular mechanics…

Materials Science · Physics 2025-11-21 Fraser Birks , Matthew Nutter , Thomas D Swinburne , James R Kermode

The "IMP Science Gateway Portal" (http://scigate.imp.kiev.ua) for complex workflow management and integration of distributed computing resources (like clusters, service grids, desktop grids, clouds) is presented. It is created on the basis…

Computational Engineering, Finance, and Science · Computer Science 2014-04-23 Yuri Gordienko , Lev Bekenov , Olexandr Gatsenko , Elena Zasimchuk , Valentin Tatarenko

Machine learning (ML)-based steering can improve the performance of ensemble-based simulations by allowing for online selection of more scientifically meaningful computations. We present DeepDriveMD, a framework for ML-driven steering of…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-07-13 Alexander Brace , Igor Yakushin , Heng Ma , Anda Trifan , Todd Munson , Ian Foster , Arvind Ramanathan , Hyungro Lee , Matteo Turilli , Shantenu Jha

We describe a combination of all-atom simulations with CABS, a well-established coarse-grained protein modeling tool, into a single multiscale protocol. The simulation method has been tested on the C-terminal beta hairpin of protein G, a…

Biological Physics · Physics 2013-08-13 Jacek Wabik , Sebastian Kmiecik , Dominik Gront , Maksim Kouza , Andrzej Kolinski

Quantum effects due to the spatial delocalization of light atoms are treated in molecular simulation via the path integral technique. Among several methods, Path Integral (PI) Molecular Dynamics (MD) is nowadays a powerful tool to…

Chemical Physics · Physics 2015-09-30 Animesh Agarwal , Luigi Delle Site

This paper presents a Graphics Processing Units (GPUs) acceleration method of an iterative scheme for gas-kinetic model equations. Unlike the previous GPU parallelization of explicit kinetic schemes, this work features a fast converging…

Computational Physics · Physics 2020-01-08 Lianhua Zhu , Peng Wang , Songze Chen , Zhaoli Guo , Yonghao Zhang

Cycle-level simulators such as gem5 are widely used in microarchitecture design, but they are prohibitively slow for large-scale design space explorations. We present Concorde, a new methodology for learning fast and accurate performance…

This paper summarizes the ideas and key concepts in MISE (Memory Interference-induced Slowdown Estimation), which was published in HPCA 2013 [97], and examines the work's significance and future potential. Applications running concurrently…

Hardware Architecture · Computer Science 2018-05-16 Lavanya Subramanian , Vivek Seshadri , Yoongu Kim , Ben Jaiyen , Onur Mutlu

Computing-in-Memory (CIM) macros have gained popularity for deep learning acceleration due to their highly parallel computation and low power consumption. However, limited macro size and ADC precision introduce throughput and accuracy…

Hardware Architecture · Computer Science 2026-05-01 Ming-Han Lin , Tian-Sheuan Chang

We propose a high-speed and accurate hybrid dynamic density functional theory for the computer simulations of the phase separation processes of polymer melts and blends. The proposed theory is a combination of the dynamic self-consistent…

Soft Condensed Matter · Physics 2009-11-11 Takashi Honda , Toshihiro Kawakatsu

We present a distilled multi-time-step (DMTS) strategy to accelerate molecular dynamics simulations using foundation neural network models. DMTS uses a dual-level neural network where the target accurate potential is coupled to a simpler…

The performance of biomolecular molecular dynamics simulations has steadily increased on modern high performance computing resources but acceleration of the analysis of the output trajectories has lagged behind so that analyzing simulations…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-03-31 Mahzad Khoshlessan , Ioannis Paraskevakos , Geoffrey C. Fox , Shantenu Jha , Oliver Beckstein

We report a novel hybrid method of simultaneous atomistic simulation of solids in critical regions (contacts surfaces, cracks areas, etc.), along with continuum modeling of other parts. The continuum is treated in terms of quasi-atoms of…

Materials Science · Physics 2026-02-17 Artem Chuprov , Egor E. Nuzhin , Alexey A. Tsukanov , Nikolay V. Brilliantov

A new algorithm for calculating intermolecular pair forces in Molecular Dynamics (MD) simulations on a distributed parallel computer is presented. The Arbitrary Interacting Cells Algorithm (AICA) is designed to operate on geometrical…

Computational Engineering, Finance, and Science · Computer Science 2007-05-23 Graham B. Macpherson , Jason M. Reese

Functionals of the meta-generalized gradient approximation (MGGA) are nowadays widely used in chemistry and solid-state physics for the simulation of electronic systems like molecules, solids, or surfaces. Due to their dependency on the…

Materials Science · Physics 2022-05-31 Jan Doumont , Fabien Tran , Peter Blaha

Bulk-bitwise processing-in-memory (PIM), where large bitwise operations are performed in parallel by the memory array itself, is an emerging form of computation with the potential to mitigate the memory wall problem. This paper examines the…

Hardware Architecture · Computer Science 2023-09-29 Ben Perach , Ronny Ronen , Benny Kimelfeld , Shahar Kvatinsky
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