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Related papers: Gyrokinetic Simulations on Many- and Multi-core Ar…

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The gyrokinetic particle-in-cell code PICLS is a full-f finite element tool to simulate turbulence in the tokamak scrape-off layer. During the previous year, the capability of PICLS was extended to encompass electromagnetic effects.…

This paper presents the Parallel Coupler for Multimodel Simulations (PCMS), a new GPU accelerated generalized coupling framework for coupling simulation codes on leadership class supercomputers. PCMS includes distributed control and field…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-10-22 Jacob S. Merson , Cameron W. Smith , Mark S. Shephard , Fuad Hasan , Abhiyan Paudel , Angel Castillo-Crooke , Joyal Mathew , Mohammad Elahi

We present OpenRBC, a coarse-grained molecular dynamics code, which is capable of performing an unprecedented in silico experiment --- simulating an entire mammal red blood cell lipid bilayer and cytoskeleton as modeled by 4 million…

Graphics processing units have been extensively used to accelerate classical molecular dynamics simulations. However, there is much less progress on the acceleration of force evaluations for many-body potentials compared to pairwise ones.…

Computational Physics · Physics 2017-06-27 Zheyong Fan , Wei Chen , Ville Vierimaa , Ari Harju

The linear properties of the geodesic acoustic modes (GAM) in tokamaks are investigated by means of the comparison of analytical theory and gyrokinetic numerical simulations. The dependence on the value of the safety factor,…

Heterogeneous many-cores are now an integral part of modern computing systems ranging from embedding systems to supercomputers. While heterogeneous many-core design offers the potential for energy-efficient high-performance, such potential…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-05-11 Jianbin Fang , Chun Huang , Tao Tang , Zheng Wang

Applications with low data reuse and frequent irregular memory accesses, such as graph or sparse linear algebra workloads, fail to scale well due to memory bottlenecks and poor core utilization. While prior work with prefetching,…

Hardware Architecture · Computer Science 2023-05-05 Marcelo Orenes-Vera , Esin Tureci , David Wentzlaff , Margaret Martonosi

In this work, we consider the reformulation of hierarchical ($\mathcal{H}$) matrix algorithms for many-core processors with a model implementation on graphics processing units (GPUs). $\mathcal{H}$ matrices approximate specific dense…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-09-04 Peter Zaspel

Task-based programming models have become very popular, as they offer an attractive solution to parallelize serial application code with task and data annotations. They usually depend on a runtime system that schedules the tasks to multiple…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-06-15 Spyros Lyberis , Polyvios Pratikakis , Iakovos Mavroidis , Dimitrios S. Nikolopoulos

The triangular mesh-based gyrokinetic scheme enables comprehensive axis-to-edge studies across the entire plasma volume. Our approach employs triangular finite elements with first-derivative continuity (C1), building on previous work to…

The overwhelmingly increasing amount of stored data has spurred researchers seeking different methods in order to optimally take advantage of it which mostly have faced a response time problem as a result of this enormous size of data. Most…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-02-18 H I Alzeini , Sh A Hameed , M H Habaebi

We implement and benchmark parallel I/O methods for the fully-manycore driven particle-in-cell code PIConGPU. Identifying throughput and overall I/O size as a major challenge for applications on today's and future HPC systems, we present a…

VPIC is a general purpose Particle-in-Cell simulation code for modeling plasma phenomena such as magnetic reconnection, fusion, solar weather, and laser-plasma interaction in three dimensions using large numbers of particles. VPIC's…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-06-16 Robert Bird , Nigel Tan , Scott V. Luedtke , Stephen Lien Harrell , Michela Taufer , Brian Albright

Analog in-memory computing (AIMC) cores offers significant performance and energy benefits for neural network inference with respect to digital logic (e.g., CPUs). AIMCs accelerate matrix-vector multiplications, which dominate these…

We propose a new hybrid topology optimization algorithm based on multigrid approach that combines the parallelization strategy of CPU using OpenMP and heavily multithreading capabilities of modern Graphics Processing Units (GPU). In…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-02-01 Arya Prakash Padhi , Souvik Chakraborty , Anupam Chakrabarti , Rajib Chowdhury

The properties of the boundary plasma in a tokamak are now recognized to play a key role in determining the achievable fusion power and the lifetimes of plasma-facing components. Accurate quantitative modeling and improved qualitative…

Plasma Physics · Physics 2017-08-25 E. L. Shi

With the advent of the gyrokinetic formalism, recent developments in low-noise nonlinear $\delta f$ methods, and enormous gains in computing power, large-scale gyrokinetic simulations have become an important tool for improved understanding…

Plasma Physics · Physics 2008-02-03 Jeremy Kepner , Scott Parker , Viktor Decyk

This paper presents a comprehensive comparison of three dominant parallel programming models in High Performance Computing (HPC): Message Passing Interface (MPI), Open Multi-Processing (OpenMP), and Compute Unified Device Architecture…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-06-19 Nizar ALHafez , Ahmad Kurdi

We present an MPI + OpenACC implementation of the kernel-independent barycentric Lagrange treecode (BLTC) for fast summation of particle interactions on GPUs. The distributed memory parallelization uses recursive coordinate bisection for…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-03-17 Nathan Vaughn , Leighton Wilson , Robert Krasny

Processing large-scale graph datasets is computationally intensive and time-consuming. Processor-centric CPU and GPU architectures, commonly used for graph applications, often face bottlenecks caused by extensive data movement between the…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-02-11 Marzieh Barkhordar , Alireza Tabatabaeian , Mohammad Sadrosadati , Christina Giannoula , Juan Gomez Luna , Izzat El Hajj , Onur Mutlu , Alaa R. Alameldeen