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Open access
Aug 2026
FLEDA: Forecasting-Based Data Partition Placement for Efficient Deep Learning Recommendation Model Training
FLEDA is a forecasting-based data partition placement framework that selectively places daily-level training data partitions onto SSDs under constrained storage capacity and consistently outperforms state-of-the-art multivariate time-series forecasting models and significantly improves SSDs' throughput coverage with lo...
Yuchen Yang, Teng Yin, Yang Guo et al.
· Proceedings of the 32nd ACM... · 0 citations