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Enabling High-Throughput Parallel I/O in Particle-in-Cell Monte Carlo Simulations with openPMD and Darshan I/O Monitoring

Autor: Williams, Jeremy J., Medeiros, Daniel, Costea, Stefan, Tskhakaya, David, Poeschel, Franz, Widera, René, Huebl, Axel, Klasky, Scott, Podhorszki, Norbert, Kos, Leon, Podolnik, Ales, Hromadka, Jakub, Narwal, Tapish, Steiniger, Klaus, Bussmann, Michael, Laure, Erwin, Markidis, Stefano

Large-scale HPC simulations of plasma dynamics in fusion devices require efficient parallel I/O to avoid slowing down the simulation and to enable the post-processing of critical information. Such complex simulations lacking parallel I/O capabilities

Externí odkaz: http://arxiv.org/abs/2408.02869

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Understanding the Impact of openPMD on BIT1, a Particle-in-Cell Monte Carlo Code, through Instrumentation, Monitoring, and In-Situ Analysis

Autor: Williams, Jeremy J., Costea, Stefan, Malony, Allen D., Tskhakaya, David, Kos, Leon, Podolnik, Ales, Hromadka, Jakub, Huck, Kevin, Laure, Erwin, Markidis, Stefano

Particle-in-Cell Monte Carlo simulations on large-scale systems play a fundamental role in understanding the complexities of plasma dynamics in fusion devices. Efficient handling and analysis of vast datasets are essential for advancing these simulat

Externí odkaz: http://arxiv.org/abs/2406.19058

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Transitioning from file-based HPC workflows to streaming data pipelines with openPMD and ADIOS2

Autor: Poeschel, Franz, E, Juncheng, Godoy, William F., Podhorszki, Norbert, Klasky, Scott, Eisenhauer, Greg, Davis, Philip E., Wan, Lipeng, Gainaru, Ana, Gu, Junmin, Koller, Fabian, Widera, René, Bussmann, Michael, Huebl, Axel

This paper aims to create a transition path from file-based IO to streaming-based workflows for scientific applications in an HPC environment. By using the openPMP-api, traditional workflows limited by filesystem bottlenecks can be overcome and flexi

Externí odkaz: http://arxiv.org/abs/2107.06108

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C++ & Python API for Scientific I/O with openPMD

Autor: Hübl, A., Pöschel, F., Koller, F., Gu, J.

openPMD is an open metadata format for open data workflows in open science. This library provides a common high-level API for openPMD writing and reading. It provides a common interface to I/O libraries and file formats such as HDF5 and ADIOS. Where

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______4577::bcde53a8e5bb3439dfcec00e56471b1c
https://www.hzdr.de/publications/Publ-27579-1

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openPMD – F.A.I.R Scientific I/O at the Exascale

Autor: Pöschel, F., Hübl, A.

Publikováno v: 8. Annual MT Meeting, 26.-27.09.2022, Hamburg, Deutschland
EuroNNAc Special Topics Workshop, 18.-24.09.2022, La Biodola Bay, Isola d'Elba, Italien

This talk presents openPMD, an open and F.A.I.R. standard for particle-mesh data, and its impact in heterogeneous scientific workflows. Particle accelerator codes need to span various time and length scales, leading to data processing pipelines consi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::584755bb800daf9da3c0a42baff235f0
https://www.hzdr.de/publications/Publ-35580-3

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openPMD - A Scientific, Community Meta-Data Standard

Autor: Huebl, Axel, Poeschel, Franz

The open standard for particle-mesh data (openPMD) is a FAIR community standard. openPMD meta-data adds scientific self-description in a machine-actionable format to data sets, which allows sharing data processing frameworks, chaining data through si

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7d5d698eb6eec3f6cafe9e9ac12c4a65

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Transitioning from file-based HPC workflows to streaming data pipelines with openPMD and ADIOS2

Autor: Franz Poeschel, Juncheng E, William F. Godoy, Norbert Podhorszki, Scott Klasky, Greg Eisenhauer, Philip E. Davis, Lipeng Wan, Ana Gainaru, Junmin Gu, Fabian Koller, René Widera, Michael Bussmann, Axel Huebl

Publikováno v: Smoky Mountains Computational Sciences & Engineering Conference (SMC2021), 18.-20.10.2021, Oak Ridge, USACommunications in Computer and Information Science, Volume 1512 CCIS, 99-118
Driving Scientific and Engineering Discoveries Through the Integration of Experiment, Big Data, and Modeling and Simulation ISBN: 9783030964979

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0153efcc9e9ddaedcfe59dc51ab45d84
http://arxiv.org/abs/2107.06108

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openPMD - An Open Standard for Particle-Mesh Data Files

Autor: Huebl, Axel, Lehe, Rémi, Vay, Jean-Luc, Grote, David P., Sbalzarini, Ivo F., Kuschel, Stephan, Sagan, David, Pérez, Frédéric, Koller, Fabian, Bussmann, Michael

Publikováno v: EUCALL (SIMEX) Annual Meeting, 30.05.-01.06.2018, Prague, Czech Republic
SIMEX Developer Workshop, 16.04.2018, Hamburg, Deutschland
18th Advanced Accelerator Concepts Workshop, 12.-17.08.2018, Breckenridge (CO), United States of America

Data fuels and substantiates scientific discoveries. Advanced particle accelerator research is no different and has an inherent need for high-rate, high-resolution data. But in recent years, generating and handling the sheer amount data that is drivi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::51f171dac79a94ef1786dd8209205dc1
https://www.hzdr.de/publications/Publ-27962-2

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openPMD Example Data Sets from PIConGPU 0.2.0

Autor: Hübl, A.

Publikováno v: Publication date: 2018-09-19 Open accessDOI: 10.14278/rodare.56Versions: 10.14278/rodare.57License: CC-BY-4.0

Quite outdated data but used in openPMD-api unit tests. HDF5 data contains particle patches, ADIOS1 data does not. Uploading it here for reference, as a download point and for test reproducibility.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______4577::10b69542935b71dc1b224ead015e23d3
https://www.hzdr.de/publications/Publ-27948-1

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