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von Laszewski

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Articles by von Laszewski

[2512.11588] AI Benchmark Democratization and Carpentry

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By von Laszewski, Vijay Janapa
| arXiv
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
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[2511.12185] Combining Serverless and High-Performance Computing Paradigms to support ML Data-Intensive Applications

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By Arup Kumar, von Laszewski
| arXiv
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
Open in Who Shared View Duplicates (202) Issue with article?

[2511.05614] An MLCommons Scientific Benchmarks Ontology

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By von Laszewski
| arXiv
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
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[2507.22294] Towards Experiment Execution in Support of Community Benchmark Workflows for HPC

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By von Laszewski
| arXiv
arXiv:2507.22294 (cs) View PDF Subjects: Distributed, Parallel, and Cluster Computing (cs.DC) Cite as: arXiv:2507.22294 [cs.DC] (or arXiv:2507.22294v1 [cs.DC] for this version) https://doi.org/10.48550/arXiv.2507.22294 Submission history From: Gregor von Laszewski PhD [ view email] [v1] Wed, 30 Jul 2025 00:01:41 UTC (2,847 KB) Bibliographic Tools Bibliographic Explorer Toggle Bibliographic Explorer () Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps...
Open in Who Shared View Duplicates (186) Issue with article?

[2401.08636] MLCommons Cloud Masking Benchmark with Early Stopping

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By von Laszewski
| arXiv
[Submitted on 11 Dec 2023] Title:MLCommons Cloud Masking Benchmark with Early Stopping Download a PDF of the paper titled MLCommons Cloud Masking Benchmark with Early Stopping, by Varshitha Chennamsetti and Gregor von Laszewski and Ruochen Gu and Laiba Mehnaz and Juri Papay and Samuel Jackson and Jeyan Thiyagalingam and Sergey V. Samsonau and Geoffrey C.
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An Overview of MLCommons Cloud Mask Benchmark: Related Research and Data

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By von Laszewski, Ruochen Gu
| arXiv
arXiv:2312.04799 (cs) Download PDF HTML (experimental) Comments: Subjects: Distributed, Parallel, and Cluster Computing (cs.DC); Artificial Intelligence (cs.AI) Cite as: arXiv:2312.04799 [cs.DC] (or arXiv:2312.04799v1 [cs.DC] for this version) https://doi.org/10.48550/arXiv.2312.04799 Submission history From: Gregor von Laszewski PhD [ view email] [v1] Fri, 8 Dec 2023 02:25:26 UTC (7,097 KB) Bibliographic Tools Bibliographic Explorer Toggle Bibliographic Explorer () Litmaps Toggle Litmaps...
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[2307.01394] In-depth Analysis On Parallel Processing Patterns for High-Performance Dataframes

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By Arup Kumar, von Laszewski, Thejaka Amila
| arXiv
arXiv:2307.01394 (cs) Download a PDF of the paper titled In-depth Analysis On Parallel Processing Patterns for High-Performance Dataframes, by Niranda Perera and 9 other authors Download PDF Submission history From: Niranda Perera [ view email] [v1] Mon, 3 Jul 2023 23:11:03 UTC (4,224 KB) Bibliographic Tools Bibliographic Explorer Toggle Bibliographic Explorer () Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Links...
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