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Modeling a high-dimensional Hamiltonian system in reduced dimensions with respect to coarse-grained (CG) variables can greatly reduce computational cost and enable efficient bottom-up prediction of main features of the system for many…

Computational Engineering, Finance, and Science · Computer Science 2021-04-09 Shu Wang , Zhan Ma , Wenxiao Pan

The high-performance computing (HPC) community has recently seen a substantial diversification of hardware platforms and their associated programming models. From traditional multicore processors to highly specialized accelerators, vendors…

Plasma Physics · Physics 2024-11-11 Josef Ruzicka , Christian Asch , Esteban Meneses , Markus Rampp , Erwin Laure

Coarse-grained modeling and efficient computer simulations are critical to the study of complex molecular processes with many degrees of freedom and multiple spatiotemporal scales. Variational implicit-solvent model (VISM) for biomolecular…

Chemical Physics · Physics 2022-10-26 Shuang Liu , Zirui Zhang , Li-Tien Cheng , Bo Li

Current trends in parallel processors call for the design of efficient massively parallel algorithms for scientific computing. Parallel algorithms for Monte Carlo simulations of thermodynamic ensembles of particles have received little…

Computational Physics · Physics 2013-08-26 Joshua A. Anderson , Eric Jankowski , Thomas L. Grubb , Michael Engel , Sharon C. Glotzer

Vlasov solvers that operate on a phase-space grid are highly accurate but also numerically demanding. Coarse velocity space resolutions, which are unproblematic in particle-in-cell (PIC) simulations, can lead to numerical heating or…

Plasma Physics · Physics 2022-04-06 Florian Allmann-Rahn , Simon Lautenbach , Rainer Grauer

Due to the very long timescales involved (us-s), theoretical modeling of fundamental biological processes including folding, misfolding, and mechanical unraveling of biomolecules, under physiologically relevant conditions, is challenging…

Soft Condensed Matter · Physics 2010-03-08 A. Zhmurov , R. I. Dima , Y. Kholodov , V. Barsegov

An algorithm is derived for computer simulation of geodesics on the constant potential-energy hypersurface of a system of N classical particles. First, a basic time-reversible geodesic algorithm is derived by discretizing the geodesic…

Soft Condensed Matter · Physics 2013-01-29 Trond S. Ingebrigtsen , Søren Toxvaerd , Ole J. Heilmann , Thomas B. Schrøder , Jeppe C. Dyre

Kinetic simulations of collisionless (or weakly collisional) plasmas using the Vlasov equation are often infeasible due to high resolution requirements and the exponential scaling of computational cost with respect to dimension. Recently,…

Computational Physics · Physics 2022-10-12 Erika Ye , Nuno F. G. Loureiro

3D Gaussian Splatting (3DGS) has emerged as a mainstream solution for novel view synthesis and 3D reconstruction. By explicitly encoding a 3D scene using a collection of Gaussian kernels, 3DGS achieves high-quality rendering with superior…

Computer Vision and Pattern Recognition · Computer Science 2025-01-28 Lei Lan , Tianjia Shao , Zixuan Lu , Yu Zhang , Chenfanfu Jiang , Yin Yang

This paper presents the implementation of a HLLC finite volume solver using GPU technology for the solution of shallow water problems in two dimensions. It compares both CPU and GPU approaches for implementing all the solver's steps. The…

Computational Engineering, Finance, and Science · Computer Science 2018-07-03 Fabrice Zaoui

In this work, we present a discontinuous-Galerkin method for evolving relativistic hydrodynamics. We include an exploration of analytical and iterative methods to recover the primitive variables from the conserved variables for the ideal…

The discontinuous Galerkin (DG) finite element method is conservative, lends itself well to parallelization, and is high-order accurate due to its close affinity with the theory of quadrature and orthogonal polynomials. When applied with an…

Computational Physics · Physics 2022-03-01 D. W. Crews

Gaussian process (GP) regression is a popular surrogate modeling tool for computer simulations in engineering and scientific domains. However, it often struggles with high computational costs and low prediction accuracy when the simulation…

Machine Learning · Computer Science 2025-02-25 Lulu Kang , Minshen Xu

Despite the numerous uses of semidefinite programming (SDP) and its universal solvability via interior point methods (IPMs), it is rarely applied to practical large-scale problems. This mainly owes to the computational cost of IPMs that…

Optimization and Control · Mathematics 2024-03-19 Yifan Ran , Stefan Vlaski , Wei Dai

The next generation of Department of Energy supercomputers will be capable of exascale computation. For these machines, far more computation will be possible than that which can be saved to disk. As a result, users will be unable to rely on…

Machine Learning · Computer Science 2025-07-23 Michael Grosskopf , Kellin Rumsey , Ayan Biswas , Earl Lawrence

Semi-Lagrangian solvers for the Vlasov system offer noiseless solutions compared to Lagrangian particle methods and can handle larger time steps compared to Eulerian methods. In order to reduce the computational complexity of the…

Numerical Analysis · Mathematics 2025-10-24 Nils Schild , Mario Raeth Klaus Hallatschek , Katharina Kormann

We introduce a learning-based framework to optimize tensor programs for deep learning workloads. Efficient implementations of tensor operators, such as matrix multiplication and high dimensional convolution, are key enablers of effective…

Machine Learning · Computer Science 2019-01-10 Tianqi Chen , Lianmin Zheng , Eddie Yan , Ziheng Jiang , Thierry Moreau , Luis Ceze , Carlos Guestrin , Arvind Krishnamurthy

This paper proposes a novel set of trigonometric implementations which are 5x faster than the inbuilt C++ functions. The proposed implementation is also highly memory efficient requiring no precomputations of any kind. Benchmark comparisons…

Mathematical Software · Computer Science 2025-02-18 Nikhil Dev Goyal , Parth Arora

Mesoscopic simulations of hydrocarbon flow in source shales are challenging, in part due to the heterogeneous shale pores with sizes ranging from a few nanometers to a few micrometers. Additionally, the sub-continuum fluid-fluid and…

Computational Physics · Physics 2019-09-13 Yidong Xia , Ansel Blumers , Zhen Li , Lixiang Luo , Yu-Hang Tang , Joshua Kane , Hai Huang , Matthew Andrew , Milind Deo , Jan Goral

We consider the solution of the fully kinetic (including electrons) Vlasov-Amp\`ere system in a one-dimensional physical space and two-dimensional velocity space (1D-2V) for an arbitrary number of species with a time-implicit Eulerian…

Plasma Physics · Physics 2020-07-13 Steven E. Anderson , William T. Taitano , Luis Chacón , Andrei N. Simakov