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We describe an implementation of compressible inviscid fluid solvers with block-structured adaptive mesh refinement on Graphics Processing Units using NVIDIA's CUDA. We show that a class of high resolution shock capturing schemes can be…

Cosmology and Nongalactic Astrophysics · Physics 2014-11-20 Peng Wang , Tom Abel , Ralf Kaehler

When simulating a lattice system near its critical temperature, local algorithms for modeling the system's evolution can introduce very large autocorrelation times into sampled data. This critical slowing down places restrictions on the…

High Energy Physics - Lattice · Physics 2023-03-01 Tristan Protzman , Joel Giedt

Highly-parallel graphics processing units (GPUs) can improve the speed of micromagnetic simulations significantly as compared to conventional computing using central processing units (CPUs). We present a strategy for performing…

Computational Physics · Physics 2015-12-18 C. L. Jermain , G. E. Rowlands , R. A. Buhrman , D. C. Ralph

As an important application of spatial databases in pathology imaging analysis, cross-comparing the spatial boundaries of a huge amount of segmented micro-anatomic objects demands extremely data- and compute-intensive operations, requiring…

Databases · Computer Science 2012-08-02 Kaibo Wang , Yin Huai , Rubao Lee , Fusheng Wang , Xiaodong Zhang , Joel H. Saltz

Large-scale molecular dynamics simulations with high accuracy have been increasingly popular for their capability to bridge the gap between atomistic modeling and mesoscale phenomena. Both machine learning potentials and enhanced sampling…

Computational Physics · Physics 2026-03-24 Haoting Zhang , Qiuhan Jia , Zhennan Zhang , Yijie Zhu , Zhongwei Zhang , Junjie Wang , Jiuyang Shi , Zheyong Fan , Jian Sun

Modern graphics hardware is designed for highly parallel numerical tasks and provides significant cost and performance benefits. Graphics hardware vendors are now making available development tools to support general purpose high…

High Energy Physics - Lattice · Physics 2009-01-22 Kipton Barros , Ronald Babich , Richard Brower , Michael A. Clark , Claudio Rebbi

The graphics processing unit (GPU) has emerged as a powerful and cost effective processor for general performance computing. GPUs are capable of an order of magnitude more floating-point operations per second as compared to modern central…

Computation · Statistics 2012-07-24 Mark Franey , Pritam Ranjan , Hugh Chipman

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…

The exponential growth of floating point power in graphics processing units (GPUs), together with their low cost, has given rise to an attractive platform upon which to deploy lattice QCD calculations. GPUs are essentially many (O(100))…

High Energy Physics - Lattice · Physics 2010-11-05 M. A. Clark

Astronomers have come to rely on the increasing performance of computers to reduce, analyze, simulate and visualize their data. In this environment, faster computation can mean more science outcomes or the opening up of new parameter spaces…

Instrumentation and Methods for Astrophysics · Physics 2010-01-14 Benjamin R. Barsdell , David G. Barnes , Christopher J. Fluke

In this work, we survey the role of GPUs in real-time systems. Originally designed for parallel graphics workloads, GPUs are now widely used in time-critical applications such as machine learning, autonomous vehicles, and robotics due to…

This paper presents the benchmarking and scaling studies of a GPU accelerated three dimensional compressible magnetohydrodynamic code. The code is developed keeping an eye to explain the large and intermediate scale magnetic field…

Usage of GPUs as co-processors is a well-established approach to accelerate costly algorithms operating on matrices and vectors. We aim to further improve the performance of the Global Neutrino Analysis framework (GNA) by adding GPU support…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-04-23 Anna Fatkina , Maxim Gonchar , Liudmila Kolupaeva , Dmitry Naumov , Konstantin Treskov

This paper consists of three parts. The first part provides a unified programming model for heterogeneous computing with CPU and accelerator (like GPU, FPGA, Google TPU, Atos QPU, and more) technologies. To some extent, this new programming…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-05-31 Yuqing Xiong

We present the results of gravitational direct $N$-body simulations using the Graphics Processing Unit (GPU) on a commercial NVIDIA GeForce 8800GTX designed for gaming computers. The force evaluation of the $N$-body problem is implemented…

Astrophysics · Physics 2008-11-26 Robert G. Belleman , Jeroen Bedorf , Simon Portegies Zwart

We equip dynamic geometry software (DGS) with a user-friendly method that enables massively parallel calculations on the graphics processing unit (GPU). This interplay of DGS and GPU opens up various applications in education and…

Mathematical Software · Computer Science 2018-08-15 Aaron Montag , Jürgen Richter-Gebert

The Random Phase Approximation (RPA) for correlation energy in the grid-based projector augmented wave (gpaw) code is accelerated by porting to the Graphics Processing Unit (GPU) architecture. The acceleration is achieved by grouping…

Computational Physics · Physics 2013-07-31 Jun Yan , Lin Li , Christopher O'Grady

The expedient design of precision components in aerospace and other high-tech industries requires simulations of physical phenomena often described by partial differential equations (PDEs) without exact solutions. Modern design problems…

Computational Physics · Physics 2018-01-11 Daniel J Magee , Kyle E Niemeyer

We report on our implementation of the RHMC algorithm for the simulation of lattice QCD with two staggered flavors on Graphics Processing Units, using the NVIDIA CUDA programming language. The main feature of our code is that the GPU is not…

High Energy Physics - Lattice · Physics 2012-01-26 Claudio Bonati , Guido Cossu , Massimo D'Elia , Pietro Incardona

In this work, we present an extension of Gaussian process (GP) models with sophisticated parallelization and GPU acceleration. The parallelization scheme arises naturally from the modular computational structure w.r.t. datapoints in the…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-10-21 Zhenwen Dai , Andreas Damianou , James Hensman , Neil Lawrence
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