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Finding an appropriate turbulence model for a given flow case usually calls for extensive experimentation with both models and numerical solution methods. This work presents the design and implementation of a flexible, programmable software…

Computational Engineering, Finance, and Science · Computer Science 2011-07-21 Mikael Mortensen , Hans Petter Langtangen , Garth N. Wells

The PySCF package has emerged as a powerful and flexible open-source platform for quantum chemistry simulations. However, the efficiency of electronic structure calculations can vary significantly depending on the choice of computational…

Chemical Physics · Physics 2025-06-10 Zhichen Pu , Qiming Sun

In this work, we propose KPerfIR, a novel multilevel compiler-centric infrastructure to enable the development of customizable, extendable, and portable profiling tools tailored for modern artificial intelligence (AI) workloads on modern…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-05-29 Yue Guan , Yuanwei Fang , Keren Zhou , Corbin Robeck , Manman Ren , Zhongkai Yu , Yufei Ding , Adnan Aziz

Modeling and simulation of fluid-structure interactions are crucial to the success of aerospace engineering. This work addresses a novel hybrid algorithm that models the close coupling between compressible flows and deformable materials…

Computational Physics · Physics 2025-04-16 Mingshuo Han , Shiwei Hu , Tianbai Xiao , Yonghao Zhang

We investigate and characterize the performance of an important class of operations on GPUs and Many Integrated Core (MIC) architectures. Our work is motivated by applications that analyze low-dimensional spatial datasets captured by high…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-11-05 George Teodoro , Tahsin Kurc , Jun Kong , Lee Cooper , Joel Saltz

Deep learning frameworks have often focused on either usability or speed, but not both. PyTorch is a machine learning library that shows that these two goals are in fact compatible: it provides an imperative and Pythonic programming style…

The amazing advances being made in the fields of machine and deep learning are a highlight of the Big Data era for both enterprise and research communities. Modern applications require resources beyond a single node's ability to provide.…

Fluid driven fractures propagate in the upper earth crust either naturally or in response to engineered fluid injections. The quantitative prediction of their evolution is critical in order to better understand their dynamics as well as to…

Computational Engineering, Finance, and Science · Computer Science 2020-05-28 Haseeb Zia , Brice Lecampion

Physics-Informed Neural Networks (PINNs) have shown promise in solving incompressible Navier-Stokes equations, yet existing approaches are predominantly designed for single-flow settings. When extended to multi-flow scenarios, these methods…

Computer Vision and Pattern Recognition · Computer Science 2026-03-12 Dengdi Sun , Jie Chen , Xiao Wang , Jin Tang

PyMembrane is a software package for simulating liquid and elastic membranes using a discretisation of the continuum description based on unstructured triangulated two-dimensional meshes embedded in three-dimensional space. The package is…

Soft Condensed Matter · Physics 2023-08-25 D. A. Matoz-Fernandez , Siyu Li , Monica Olvera de la Cruz , Rastko Sknepnek

In this work, we detail the GPU-porting of an in-house pseudo-spectral solver tailored towards large-scale simulations of interface-resolved simulation of drop- and bubble-laden turbulent flows. The code relies on direct numerical…

Fluid Dynamics · Physics 2024-06-04 Alessio Roccon

We address the challenges associated with deploying neural networks on CPUs, with a particular focus on minimizing inference time while maintaining accuracy. Our novel approach is to use the dataflow (i.e., computation order) of a neural…

Hardware Architecture · Computer Science 2023-11-27 Cyrus Zhou , Zack Hassman , Ruize Xu , Dhirpal Shah , Vaugnn Richard , Yanjing Li

We present the Fluid Transport Accelerated Solver, FluTAS, a scalable GPU code for multiphase flows with thermal effects. The code solves the incompressible Navier-Stokes equation for two-fluid systems, with a direct FFT-based Poisson…

Simulations based on particle methods, such as Smoothed Particle Hydrodynamics (SPH), are known to be computationally demanding. While such methods have for long been executed in parallel on multi-core CPUs, in recent years the increasing…

Computational Engineering, Finance, and Science · Computer Science 2026-03-18 Xiangyu Hu , Alberto Guarnieri

We present MARUT, a scalable multi-GPU computational fluid dynamics (CFD) framework designed for high-fidelity simulations of compressible flows spanning subsonic to hypersonic regimes, including chemically reacting nonequilibrium flows…

Computational Physics · Physics 2026-05-29 Trishit Mondal , Ameya D. Jagtap

Exascale computing delivers the raw power to simulate ever larger and more chemically realistic systems, but realizing this potential requires codes that can efficiently use thousands of processors. Our real-space multigrid (RMG) density…

Materials Science · Physics 2026-01-19 R. J. Morelock , S. Bagchi , E. L. Briggs , W. Lu , J. Bernholc , P. Ganesh

Growing code bases of modern applications have led to a steady increase in the number of vulnerabilities. Control-Flow Integrity (CFI) is one promising mitigation that is more and more widely deployed and prevents numerous exploits. CFI…

Cryptography and Security · Computer Science 2022-03-01 Claudio Canella , Sebastian Dorn , Daniel Gruss , Michael Schwarz

Many or-parallel Prolog models exploiting implicit parallelism have been proposed in the past. Arguably, one of the most successful models is environment copying for shared memory architectures. With the increasing availability and…

Programming Languages · Computer Science 2013-02-01 Rui Vieira , Ricardo Rocha , Fernando Silva

We present an exponentially convergent semi-implicit meshless algorithm for the solution of Navier-Stokes equations in complex domains. The algorithm discretizes partial derivatives at scattered points using radial basis functions as…

Numerical Analysis · Mathematics 2021-06-15 Shantanu Shahane , Surya Pratap Vanka

We propose an explicit partitioned (loosely coupled) scheme for fluid structure interaction (FSI) problems, specifically designed to achieve high computational efficiency in modern engineering simulations. The FSI problem under…

Numerical Analysis · Mathematics 2025-10-16 Shihan Guo , Ping Lin , Yifan Wang , Xiaohe Yue , Haibiao Zheng
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