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Energy system optimization models are increasing in scope and resolution, yielding large and challenging linear programs. For a long time, the standard way to address such problems has relied on shared-memory interior-point methods (IPM),…

Optimization and Control · Mathematics 2026-05-07 Janina Zittel , Annika Buchholz , Michael Bussieck , Frederik Fiand , Thorsten Koch , Lukas Mehl , Niels Lindner , Manuel Wetzel

We propose a GPU-based distributed optimization algorithm, aimed at controlling optimal power flow in multi-phase and unbalanced distribution systems. Typically, conventional distributed optimization algorithms employed in such scenarios…

Optimization and Control · Mathematics 2023-10-17 Minseok Ryu , Geunyeong Byeon , Kibaek Kim

We present an alternative GPU acceleration for plane waves pseudopotentials electronic structure codes designed for systems that have small unit cells but require a large number of k points to sample the Brillouin zone as happens, for…

Materials Science · Physics 2025-07-31 Xuejun Gong , Andrea Dal Corso

We introduce a fusion of GPU accelerated primal heuristics for Mixed Integer Programming. Leveraging GPU acceleration enables exploration of larger search regions and faster iterations. A GPU-accelerated PDLP serves as an approximate LP…

Optimization and Control · Mathematics 2025-10-31 Akif Çördük , Piotr Sielski , Alice Boucher , Kumar Aatish

We present the GPU calculation with the common unified device architecture (CUDA) for the Wolff single-cluster algorithm of the Ising model. Proposing an algorithm for a quasi-block synchronization, we realize the Wolff single-cluster Monte…

Computational Physics · Physics 2012-01-10 Yukihiro Komura , Yutaka Okabe

This paper presents a GPU-accelerated framework for solving block tridiagonal linear systems that arise naturally in numerous real-time applications across engineering and scientific computing. Through a multi-stage permutation strategy…

Optimization and Control · Mathematics 2026-01-08 Roland Schwan , Daniel Kuhn , Colin N. Jones

We present a GPU-accelerated version of the real-space SPARC electronic structure code for performing Kohn-Sham density functional theory calculations within the local density and generalized gradient approximations. In particular, we…

Computational Physics · Physics 2023-06-14 Abhiraj Sharma , Alfredo Metere , Phanish Suryanarayana , Lucas Erlandson , Edmond Chow , John E. Pask

Due to their highly parallel multi-cores architecture, GPUs are being increasingly used in a wide range of computationally intensive applications. Compared to CPUs, GPUs can achieve higher performances at accelerating the programs'…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-10-05 Frédéric Magoulès , Abal-Kassim Cheik Ahamed , Alban Desmaison , Jean-Christophe Léchenet , François Mayer , Haifa Ben Salem , Thomas Zhu

We discuss the efficiency of parallelization on graphical processing units (GPUs) for the simulation of the one dimensional Potts model with long range interactions via parallel tempering. We investigate the behaviour of some thermodynamic…

Statistical Mechanics · Physics 2015-06-17 A. Boer

This work presents the GPU acceleration of the open-source code CaNS for very fast massively-parallel simulations of canonical fluid flows. The distinct feature of the many-CPU Navier-Stokes solver in CaNS is its fast direct solver for the…

Fluid Dynamics · Physics 2021-02-15 Pedro Costa , Everett Phillips , Luca Brandt , Massimiliano Fatica

This paper presents an implicit method for the discrete unified gas-kinetic scheme (DUGKS) to speed up the simulations of the steady flows in all flow regimes. The DUGKS is a multi-scale scheme finite volume method (FVM) for all flow…

Fluid Dynamics · Physics 2018-10-18 Dongxin Pan , Chengwen Zhong , Congshan Zhuo

In this paper, the high-order compact gas-kinetic scheme (CGKS) on three-dimensional hybrid unstructured mesh is further developed with the p-multigrid technique for steady-state solution acceleration. The p-multigrid strategy is a…

Computational Physics · Physics 2021-09-22 Xing Ji , Wei Shyy , Kun Xu

Reduction operations are extensively employed in many computational problems. A reduction consists of, given a finite set of numeric elements, combining into a single value all elements in that set, using for this a combiner function. A…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-10-23 Walid Jradi , Hugo do Nascimento , Wellington Martins

This paper proposes a GPU-accelerated optimization framework for collision avoidance problems where the controlled objects and the obstacles can be modeled as the finite union of convex polyhedra. A novel collision avoidance constraint is…

Robotics · Computer Science 2024-06-12 Zeming Wu , Zhuping Wang , Hao Zhang

Although the performance of commodity computers has improved drastically with the introduction of multicore processors and GPU computing, the standard R distribution is still based on single-threaded model of computation, using only a small…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-03-21 Bogdan Oancea , Richard Pospisil

Immersed boundary methods (IBMs) facilitate the simulation of flows around stationary, moving, and deforming bodies on Cartesian grids. However, extending these simulations to the large grid sizes required for realistic flow problems…

Fluid Dynamics · Physics 2026-03-16 Sushrut Kumar , Joshua Romero , Jung-Hee Seo , Massimiliano Fatica , Rajat Mittal

Lattice Boltzmann method models offer a novel framework for the simulation of high Reynolds number dilute gravity currents. The numerical algorithm is well suited to acceleration via implementation on massively parallel computer…

Simulations of physical phenomena are essential to the expedient design of precision components in aerospace and other high-tech industries. These phenomena are often described by mathematical models involving partial differential equations…

Computational Physics · Physics 2017-01-05 Daniel Magee , Kyle E Niemeyer

Simulating large-scale microswimmer dynamics in viscous fluid poses significant challenges due to the coupled high spatial and temporal complexity. Conventional high-performance computing (HPC) methods often address these two dimensions in…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-04-15 Ruixiang Huang , Weifan Liu

Single-cell sequencing technologies reveal cellular heterogeneity at high resolution, advancing our understanding of biological complexity. As datasets start to scale to tens of millions of cells, computational workflows face substantial…