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Related papers: Porting WarpX to GPU-accelerated platforms

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The electrical and electronic engineering has used parallel programming to solve its large scale complex problems for performance reasons. However, as parallel programming requires a non-trivial distribution of tasks and data, developers…

Distributed, Parallel, and Cluster Computing · Computer Science 2011-07-05 Antonio Wendell De Oliveira Rodrigues , Frédéric Guyomarc'H , Jean-Luc Dekeyser , Yvonnick Le Menach

Modern GPUs increasingly rely on specialized hardware units and asynchronous coordination mechanisms, so performance depends on orchestrating data movement, tensor-core computation, and synchronization rather than exposing more thread-level…

With recent developments in parallel supercomputing architecture, many core, multi-core, and GPU processors are now commonplace, resulting in more levels of parallelism, memory hierarchy, and programming complexity. It has been necessary to…

High Energy Physics - Lattice · Physics 2017-12-04 Ruizi Li , Carleton DeTar , Steven Gottlieb , Doug Toussaint

The upcoming exascale computing systems Frontier and Aurora will draw much of their computing power from GPU accelerators. The hardware for these systems will be provided by AMD and Intel, respectively, each supporting their own GPU…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-05-18 Felix Wittwer , Nicholas K. Sauter , Derek Mendez , Billy K. Poon , Aaron S. Brewster , James M. Holton , Michael E. Wall , William E. Hart , Deborah J. Bard , Johannes P. Blaschke

Aurora is Argonne National Laboratory's pioneering Exascale supercomputer, designed to accelerate scientific discovery with cutting-edge architectural innovations. Key new technologies include the Intel(TM) Xeon(TM) Data Center GPU Max…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-12-09 William E. Allcock , Benjamin S. Allen , James Anchell , Victor Anisimov , Thomas Applencourt , Abhishek Bagusetty , Ramesh Balakrishnan , Riccardo Balin , Solomon Bekele , Colleen Bertoni , Cyrus Blackworth , Renzo Bustamante , Kevin Canada , John Carrier , Christopher Chan-nui , Lance C. Cheney , Taylor Childers , Paul Coffman , Susan Coghlan , Tanima Dey , Michael D'Mello , Ashok Emani , Murali Emani , Kyle G. Felker , Sam Foreman , Olivier Franza , Longfei Gao , Marta García , María Garzarán , Balazs Gerofi , Yasaman Ghadar , Subrata Goswami , Neha Gupta , Kevin Harms , Väinö Hatanpää , Brian Holland , Carissa Holohan , Brian Homerding , Khalid Hossain , Xue Hu , Louise Huot , Huda Ibeid , Joseph A. Insley , Sai Jayanthi , Hong Jiang , Wei Jiang , Xiao-Yong Jin , Jeongnim Kim , Christopher Knight , Panagiotis Kourdis , Kalyan Kumaran , JaeHyuk Kwack , Janghaeng Lee , Ti Leggett , Ben Lenard , Chris Lewis , Nevin Liber , Johann Lombardi , Raymond M. Loy , Ye Luo , Bethany Lusch , Nilakantan Mahadevan , Beth Markey , Victor A. Mateevitsi , Gordon McPheeters , Ryan Milner , Jerome Mitchell , Vitali A. Morozov , Servesh Muralidharan , Tom Musta , Mrigendra Nagar , Vikram Narayana , Marieme Ngom , Anthony-Trung Nguyen , Nathan Nichols , Aditya Nishtala , James C. Osborn , Michael E. Papka , Scott Parker , Saumil S. Patel , Julia Piotrowska , Adrian C. Pope , Sucheta Raghunanda , Esteban Rangel , Paul M. Rich , Katherine M. Riley , Silvio Rizzi , Kris Rowe , Varuni Sastry , Adam Scovel , Filippo Simini , Haritha Siddabathuni Som , Patrick Steinbrecher , Rick Stevens , Xinmin Tian , Peter Upton , Thomas Uram , Archit K. Vasan , Álvaro Vázquez-Mayagoitia , Kaushik Velusamy , Brice Videau , Venkatram Vishwanath , Brian Whitney , Timothy J. Williams , Michael Woodacre , Sam Zeltner , Chuanjun Zhang , Gengbin Zheng , Huihuo Zheng

Parallel data processing has become indispensable for processing applications involving huge data sets. This brings into focus the Graphics Processing Units (GPUs) which emphasize on many-core computing. With the advent of General Purpose…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-05-22 Poorna Banerjee , Amit Dave

In this paper, we introduce a software-defined framework that enables the parallel utilization of all the programmable processing resources available in heterogeneous system-on-chip (SoC) including FPGA-based hardware accelerators and…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-02-12 Jose Nunez-Yanez , Mohammad Hosseinabady , Moslem Amiri , Andrés Rodríguez , Rafael Asenjo , Angeles Navarro , Rubén Gran-Tejero , Darío Suárez-Gracia

As an increasing number of leadership-class systems embrace GPU accelerators in the race towards exascale, efficient communication of GPU data is becoming one of the most critical components of high-performance computing. For developers of…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-03-23 Jaemin Choi , Zane Fink , Sam White , Nitin Bhat , David F. Richards , Laxmikant V. Kale

High Performance Computing (HPC) platforms allow scientists to model computationally intensive algorithms. HPC clusters increasingly use General-Purpose Graphics Processing Units (GPGPUs) as accelerators; FPGAs provide an attractive…

Hardware Architecture · Computer Science 2015-04-20 Syed Waqar Nabi , Saji N. Hameed , Wim Vanderbauwhede

Elegant is an accelerator physics and particle-beam dynamics code widely used for modeling and design of a variety of high-energy particle accelerators and accelerator-based systems. In this paper we discuss a recently developed version of…

Computational Physics · Physics 2018-11-22 J. R. King , I. V. Pogorelov , K. M. Amyx , M. Borland , R. Soliday

Manycore System-on-Chip include an increasing amount of processing elements and have become an important research topic for improvements of both hardware and software. While research can be conducted using system simulators, prototyping…

Hardware Architecture · Computer Science 2013-04-19 Stefan Wallentowitz , Philipp Wagner , Michael Tempelmeier , Thomas Wild , Andreas Herkersdorf

This paper presents a computationally efficient implementation of a Hamming code decoder on a graphics processing unit (GPU) to support real-time software-defined radio (SDR), which is a software alternative for realizing wireless…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-12-23 Shohidul Islam , Cheol-Hong Kim , Jong-Myon Kim

The LHC experiments are designed to detect large amount of physics events produced with a very high rate. Considering the future upgrades, the data acquisition rate will become even higher and new computing paradigms must be adopted for…

General purpose computing on graphic processing units (GPU) is a potential method of speeding up scientific computation with low cost and high energy efficiency. We experimented with the particle physics simulation toolkit Geant4 used at…

Computational Physics · Physics 2012-09-25 Otto Seiskari , Jukka Kommeri , Tapio Niemi

In the wake of the intense effort made for the experimental CILEX project, numerical simulation cam- paigns have been carried out in order to finalize the design of the facility and to identify optimal laser and plasma parameters. These…

Computational Physics · Physics 2016-04-20 Arnaud Beck , Jacob Trier Frederiksen , Julien Dérouillat

Vortex, a newly proposed open-source GPGPU platform based on the RISC-V ISA, offers a valid alternative for GPGPU research over the broadly-used modeling platforms based on commercial GPUs. Similarly to the push originating from the RISC-V…

Hardware Architecture · Computer Science 2025-12-02 Giuseppe M. Sarda , Nimish Shah , Abubakr Nada , Debjyoti Bhattacharjee , Marian Verhelst

The use of multicore optical fibers is now recognized as one of the most promising methods to implement the space-division multiplexing techniques required to overcome the impending capacity limit of conventional single-mode optical fibers.…

Over the past few years, there has been an increased interest in including FPGAs in data centers and high-performance computing clusters along with GPUs and other accelerators. As a result, it has become increasingly important to have a…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-09-14 Mostafa Eghbali Zarch , Reece Neff , Michela Becchi

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

Heterogeneity is the prevalent trend in the rapidly evolving high-performance computing (HPC) landscape in both hardware and application software. The diversity in hardware platforms, currently comprising various accelerators and a future…

Numerical Analysis · Mathematics 2025-07-15 Youngjun Lee , Klaus Weide , Wesley Kwiecinski , Jared O'Neal , Johann Rudi , Anshu Dubey