• P B G, Marion Lincy G R, Rishekeeshan A and Deekshitha . (2024). Accelerating Native Inference Model Performance in Edge Devices using TensorRT 2024 IEEE Recent Advances in Intelligent Computational Systems (RAICS). 10.1109/RAICS61201.2024.10690032. 979-8-3503-8168-9. (1-7).

    https://ieeexplore.ieee.org/document/10690032/

  • Zong Z, Lin L, Lin L, Wen L and Sun Y. (2023). <sc>STR</sc>: Hybrid Tensor Re-Generation to Break Memory Wall for DNN Training. IEEE Transactions on Parallel and Distributed Systems. 34:8. (2403-2418). Online publication date: 1-Aug-2023.

    https://doi.org/10.1109/TPDS.2023.3266110

  • Liao J, Li M, Yang H, Sun Q, Sun B, Hao J, Feng T, Yu F, Chen S, Tao Y, Zhang Z, Luan Z and Qian D. (2023). Exploiting Input Tensor Dynamics in Activation Checkpointing for Efficient Training on GPU 2023 IEEE International Parallel and Distributed Processing Symposium (IPDPS). 10.1109/IPDPS54959.2023.00025. 979-8-3503-3766-2. (156-166).

    https://ieeexplore.ieee.org/document/10177427/

  • Schuler M, Membarth R and Slusallek P. (2022). XEngine: Optimal Tensor Rematerialization for Neural Networks in Heterogeneous Environments. ACM Transactions on Architecture and Code Optimization. 20:1. (1-25). Online publication date: 31-Mar-2023.

    https://doi.org/10.1145/3568956

  • Lin M, Zhou K and Su P. DrGPUM: Guiding Memory Optimization for GPU-Accelerated Applications. Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 3. (164-178).

    https://doi.org/10.1145/3582016.3582044