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We review the architecture of massively parallel machines used for lattice QCD simulations and present benchmarks for the performance of popular algorithms on these platforms. We cover commercial supercomputers, PC clusters, and…

High Energy Physics - Lattice · Physics 2016-09-01 Tilo Wettig

In this work, we present accLB, a high-performance Fortran-based lattice Boltzmann (LB) solver tailored to multiphase turbulent flows on multi-GPU architectures. The code couples a conservative phase-field formulation of the Allen-Cahn…

Nowadays, several industrial applications are being ported to parallel architectures. These applications take advantage of the potential parallelism provided by multiple core processors. Many-core processors, especially the GPUs(Graphics…

Distributed, Parallel, and Cluster Computing · Computer Science 2011-03-28 Wendell Rodrigues , Frédéric Guyomarc'h , Jean-Luc Dekeyser

We present $\texttt{SIMULATeQCD}$, HotQCD's software for performing lattice QCD calculations on GPUs. Started in late 2017 and intended as a full replacement of the previous single GPU lattice QCD code used by the HotQCD collaboration, our…

Memory-bound algorithms show complex performance and energy consumption behavior on multicore processors. We choose the lattice-Boltzmann method (LBM) on an Intel Sandy Bridge cluster as a prototype scenario to investigate if and how…

Performance · Computer Science 2015-05-25 Markus Wittmann , Georg Hager , Thomas Zeiser , Jan Treibig , Gerhard Wellein

This paper describes `Ludwig', a versatile code for the simulation of Lattice-Boltzmann (LB) models in 3-D on cubic lattices. In fact `Ludwig' is not a single code, but a set of codes that share certain common routines, such as I/O and…

Soft Condensed Matter · Physics 2009-10-31 Jean-Christophe Desplat , Ignacio Pagonabarraga , Peter Bladon

We assess the performance of the hybrid Open Accelerator (OpenACC) and Message Passing Interface (MPI) approach for multi-graphics processing units (GPUs) accelerated thermal lattice Boltzmann (LB) simulation. The OpenACC accelerates…

Fluid Dynamics · Physics 2022-11-21 Ao Xu , Bo-Tao Li

Parallel computing is a standard approach to achieving high-performance computing (HPC). Three commonly used methods to implement parallel computing include: 1) applying multithreading technology on single-core or multi-core CPUs; 2)…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-09-18 Xinyao Yi

Immersed boundary-lattice Boltzmann method (IB-LBM) has been widely used for simulation of particle-laden flows recently. However, it was limited to small-scale simulations with no more than O(103) particles. Here, we expand IB-LBM for…

Computational Physics · Physics 2020-02-21 Maoqiang Jiang , Jing Li , Zhaohui Liu

Parallel programs in high performance computing (HPC) continue to grow in complexity and scale in the exascale era. The diversity in hardware and parallel programming models make developing, optimizing, and maintaining parallel software…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-05-15 Daniel Nichols , Aniruddha Marathe , Harshitha Menon , Todd Gamblin , Abhinav Bhatele

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…

The rise of exascale supercomputers has fueled competition among GPU vendors, driving lattice QCD developers to write code that supports multiple APIs. Moreover, new developments in algorithms and physics research require frequent updates…

We utilize the Open Accelerator (OpenACC) approach for graphics processing unit (GPU) accelerated particle-resolved thermal lattice Boltzmann (LB) simulation. We adopt the momentum-exchange method to calculate fluid-particle interactions to…

Fluid Dynamics · Physics 2023-10-06 Ao Xu , Bo-Tao Li

Running large-scale computer codes for huge fluid flow problems requires not only large supercomputers but also efficient and well-optimized computer codes that save the resources of those supercomputers. This paper evaluates the…

Computational Physics · Physics 2024-08-02 Maja Bacza , Tadeusz Tomczak , Maciej Matyka

We implement and analyse a sparse / indirect-addressing data structure for the Lattice Boltzmann Method to support efficient compute kernels for fluid dynamics problems with a high number of non-fluid nodes in the domain, such as in porous…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-08-14 Philipp Suffa , Markus Holzer , Harald Köstler , Ulrich Rüde

Simulations of systems with quenched disorder are extremely demanding, suffering from the combined effect of slow relaxation and the need of performing the disorder average. As a consequence, new algorithms, improved implementations, and…

Computational Physics · Physics 2020-05-20 Ravinder Kumar , Jonathan Gross , Wolfhard Janke , Martin Weigel

In this paper we present a topology optimization technique applicable to a broad range of flow design problems. We propose also a discrete adjoint formulation effective for a wide class of Lattice Boltzmann Methods (LBM). This adjoint…

Computational Engineering, Finance, and Science · Computer Science 2015-01-21 Łukasz Łaniewski-Wołłk , Jacek Rokicki

We present a multi-scale lattice Boltzmann scheme, which adaptively refines particles' velocity space. Different velocity sets, i.e., higher- and lower-order lattices, are consistently and efficiently coupled, allowing us to use the…

Fluid Dynamics · Physics 2021-06-16 N. G. Kallikounis , B. Dorschner , I. V. Karlin

Heterogeneous systems are becoming more common on High Performance Computing (HPC) systems. Even using tools like CUDA and OpenCL it is a non-trivial task to obtain optimal performance on the GPU. Approaches to simplifying this task include…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-01-11 Marek Blazewicz , Steven R. Brandt , Peter Diener , David M. Koppelman , Krzysztof Kurowski , Frank Löffler , Erik Schnetter , Jian Tao

Large language models have led to state-of-the-art accuracies across a range of tasks. However, training these models efficiently is challenging for two reasons: a) GPU memory capacity is limited, making it impossible to fit large models on…