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RIPCORD @ WPI

Public repo for the RIPCORD project

DNN Model Execution Caching

About

DNN models, especially popular CNN models, are often run from within GPU memory. This memory is a limited quantity, especially when compared to the number of models being served. The RIPCORD project focuses on improving DNN serving through better GPU memory management, intelligent model selection and request routing.

Publications

Project Personnel

Ph.D. Students

Principle Investigators

Acknowledgements

This research is supported in part by the National Science Foundation under Grant No. 1755659 and No. 1815619.