Efficient Large Scale DLRM Implementation on Heterogeneous Memory Systems-Reference-Cited by-同舟云学术

Efficient Large Scale DLRM Implementation on Heterogeneous Memory Systems

Published:2023 Issue: Volume: Page:42-61
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
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Author:

Hildebrand Mark^ORCID,Lowe-Power Jason^ORCID,Akella Venkatesh^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-32041-5_3

Reference22 articles.

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2. Ardestani, E.K., et al.: Supporting massive DLRM inference through software defined memory. CoRR abs/2110.11489 (2021). https://arxiv.org/abs/2110.11489

3. Dhulipala, L., et al.: Sage: parallel semi-asymmetric graph algorithms for NVRAMs. Proc. VLDB Endow. 13(9), 1598–1613 (2020). https://doi.org/10.14778/3397230.3397251

4. Eisenman, A., et al.: Reducing DRAM footprint with NVM in Facebook. In: Proceedings of the Thirteenth EuroSys Conference, EuroSys 2018, Porto, Portugal, 23–26 April 2018, pp. 42:1–42:13 (2018). https://doi.org/10.1145/3190508.3190524

5. Eisenman, A., et al.: Bandana: using non-volatile memory for storing deep learning models. CoRR abs/1811.05922 (2018). http://arxiv.org/abs/1811.05922

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