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cs.DC2026
ShardTensor: Domain Parallelism for Scientific Machine Learning
Corey Adams, Peter Harrington, Akshay Subramaniam +4
Scientific Machine Learning (SciML) faces unique challenges for extreme-resolution data, with mitigations that often fail to scale or degrade the accuracy of trained models. While…
cs.DC2019
Scaling Distributed Training of Flood-Filling Networks on HPC Infrastructure for Brain Mapping
Wushi Dong, Murat Keceli, Rafael Vescovi +9
Mapping all the neurons in the brain requires automatic reconstruction of entire cells from volume electron microscopy data. The flood-filling network (FFN) architecture has demons…