Enabling Efficient Large Recommendation Model Training with Near CXL Memory Processing

Liu, Haifeng; Zheng, Long; Huang, Yu; Zhou, Jingyi; Liu, Chaoqiang; Wang, Runze; Liao, Xiaofei; Jin, Hai; Xue, Jingling

doi:10.1109/isca59077.2024.00036

2024 ACM/IEEE 51st Annual International Symposium on Computer Architecture (ISCA) 2024

DOI: 10.1109/isca59077.2024.00036

|View full text |Cite

Enabling Efficient Large Recommendation Model Training with Near CXL Memory Processing

Haifeng Liu,

Long Zheng,

Yu Huang

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Other2

Relationship

Self Cite0

Independent2

Authors

Journals

Cited by 2 publications

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

A Unified Computational Storage and Memory Architecture in the CXL Era

Chen,

Wu,

2024

2024 International Conference on Networking, Architecture and Storage (NAS)

View full text Add to dashboard Cite

A Unified Computational Storage and Memory Architecture in the CXL Era

Chen,

Wu,

2024

2024 International Conference on Networking, Architecture and Storage (NAS)

View full text Add to dashboard Cite

Boosting Data Center Performance via Intelligently Managed Multi-backend Disaggregated Memory

Wang,

Yang,

et al. 2024

SC24: International Conference for High Performance Computing, Networking, Storage and Analysis

View full text Add to dashboard Cite

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Enabling Efficient Large Recommendation Model Training with Near CXL Memory Processing

Cited by 2 publications

References 44 publications

A Unified Computational Storage and Memory Architecture in the CXL Era

A Unified Computational Storage and Memory Architecture in the CXL Era

Boosting Data Center Performance via Intelligently Managed Multi-backend Disaggregated Memory

Contact Info

Product

Resources

About