Ladder: Enabling Efficient Low-Precision Deep Learning Computing through Hardware-aware Tensor Transformation.
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Proceedings of the 18th USENIX Symposium on Operating Systems Design and Implementation, 2024
SDPipe: A Semi-Decentralized Framework for Heterogeneity-aware Pipeline-parallel Training.
Proc. VLDB Endow., 2023
Cocktailer: Analyzing and Optimizing Dynamic Control Flow in Deep Learning.
Proceedings of the 17th USENIX Symposium on Operating Systems Design and Implementation, 2023
Welder: Scheduling Deep Learning Memory Access via Tile-graph.
Proceedings of the 17th USENIX Symposium on Operating Systems Design and Implementation, 2023
HET-GMP: A Graph-based System Approach to Scaling Large Embedding Model Training.
Proceedings of the SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022
HET: Scaling out Huge Embedding Model Training via Cache-enabled Distributed Framework.
Proc. VLDB Endow., 2021