Understanding the Scalability of Molecular Simulation Using Empirical Performance Modeling-Reference-Cited by-同舟云学术

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Understanding the Scalability of Molecular Simulation Using Empirical Performance Modeling

Published:2019 Issue: Volume: Page:125-143
ISSN:0302-9743
Container-title:Programming and Performance Visualization Tools
language:
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Author:

Shudler Sergei^ORCID,Vrabec Jadran^ORCID,Wolf Felix^ORCID

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-17872-7_8

Reference28 articles.

1. BMBF project TaLPas - Task-based Load Balancing and Auto-tuning in Particle Simulations. https://wr.informatik.uni-hamburg.de/research/projects/talpas/start . Accessed 22 May 2018

2. Cube 4.x series. http://www.scalasca.org/software/cube-4.x/download.html . Accessed 22 May 2018

3. European Union’s Horizon 2020 project POP - Performance Optimisation and Productivity. https://pop-coe.eu . Accessed 25 June 2018

4. Extra-P – Automated Performance-modeling Tool. http://www.scalasca.org/software/extra-p . Accessed 22 May 2018

5. Folding@home. https://foldingathome.org/ . Accessed 04 July 2018

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Offsite Autotuning Approach;Lecture Notes in Computer Science;2020

2. Semantic Interoperability and Characterization of Data Provenance in Computational Molecular Engineering;Journal of Chemical & Engineering Data;2019-12-19

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