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Cliffhanger: Scaling Performance Cliffs in Web Memory Caches.

, , , and . NSDI, page 379-392. USENIX Association, (2016)

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Bandana: Using Non-volatile Memory for Storing Deep Learning Models., , , , , , , and . CoRR, (2018)High-performance, Distributed Training of Large-scale Deep Learning Recommendation Models., , , , , , , , , and 41 other author(s). CoRR, (2021)Cliffhanger: Scaling Performance Cliffs in Web Memory Caches., , , and . NSDI, page 379-392. USENIX Association, (2016)Dynacache: Dynamic Cloud Caching., , , and . HotStorage, USENIX Association, (2015)Check-N-Run: A Checkpointing System for Training Recommendation Models., , , , , , , and . CoRR, (2020)Flashield: a Hybrid Key-value Cache that Controls Flash Write Amplification., , , , , , and . NSDI, page 65-78. USENIX Association, (2019)QuickUpdate: a Real-Time Personalization System for Large-Scale Recommendation Models., , , , , , , , , and . NSDI, page 731-744. USENIX Association, (2024)Flashield: a Key-value Cache that Minimizes Writes to Flash., , , , , , and . CoRR, (2017)Software-hardware co-design for fast and scalable training of deep learning recommendation models., , , , , , , , , and 43 other author(s). ISCA, page 993-1011. ACM, (2022)Check-N-Run: a Checkpointing System for Training Deep Learning Recommendation Models., , , , , , , and . NSDI, page 929-943. USENIX Association, (2022)