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Bandana: Using Non-volatile Memory for Storing Deep Learning Models

Typical large-scale recommender systems use deep learning models that are stored on a large amount of DRAM. These models often rely on embeddings, which consume most of the required memory. We present Bandana, a storage system that reduces the DRAM footprint of embeddings, by using Non-volatile Memory (NVM) as the primary storage medium, with a small amount of DRAM as cache.

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Cite this as

Assaf Eisenman, Maxim Naumov, Darryl Gardner, Misha Smelyanskiy, Sergey Pupyrev, Kim Hazelwood, Asaf Cidon, Sachin Katti (2025). Dataset: Bandana: Using Non-volatile Memory for Storing Deep Learning Models. https://doi.org/10.57702/wuu05chh

DOI retrieved: January 2, 2025

Additional Info

Field Value
Created January 2, 2025
Last update January 2, 2025
Defined In https://doi.org/10.48550/arXiv.1811.05922
Author Assaf Eisenman
More Authors
Maxim Naumov
Darryl Gardner
Misha Smelyanskiy
Sergey Pupyrev
Kim Hazelwood
Asaf Cidon
Sachin Katti
Homepage https://arxiv.org/abs/1805.07763