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Improvements & Evaluations on the MLCommons CloudMask Benchmark
March 8, 2024, 5:42 a.m. | Varshitha Chennamsetti, Laiba Mehnaz, Dan Zhao, Banani Ghosh, Sergey V. Samsonau
cs.LG updates on arXiv.org arxiv.org
Abstract: In this paper, we report the performance benchmarking results of deep learning models on MLCommons' Science cloud-masking benchmark using a high-performance computing cluster at New York University (NYU): NYU Greene. MLCommons is a consortium that develops and maintains several scientific benchmarks that can benefit from developments in AI. We provide a description of the cloud-masking benchmark task, updated code, and the best model for this benchmark when using our selected hyperparameter settings. Our benchmarking results …
abstract arxiv benchmark benchmarking benchmarks benefit cloud cluster computing cs.dc cs.lg deep learning improvements masking mlcommons new york university nyu paper performance report results science type university
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