TrimCaching: Parameter-sharing AI Model Caching in Wireless Edge Networks

no code implementations • 7 May 2024 • Guanqiao Qu, Zheng Lin, Fangming Liu, Xianhao Chen, Kaibin Huang

To this end, we formulate a parameter-sharing model placement problem to maximize the cache hit ratio in multi-edge wireless networks by balancing the fundamental tradeoff between storage efficiency and service latency.

Opara: Exploiting Operator Parallelism for Expediting DNN Inference on GPUs

1 code implementation • 16 Dec 2023 • Aodong Chen, Fei Xu, Li Han, Yuan Dong, Li Chen, Zhi Zhou, Fangming Liu

GPUs have become the defacto hardware devices to accelerate Deep Neural Network (DNN) inference in deep learning(DL) frameworks.

Scheduling

On-edge Multi-task Transfer Learning: Model and Practice with Data-driven Task Allocation

no code implementations • 6 Jul 2021 • Zimu Zheng, Qiong Chen, Chuang Hu, Dan Wang, Fangming Liu

We then show that task allocation with task importance for MTL (TATIM) is a variant of the NP-complete Knapsack problem, where the complicated computation to solve this problem needs to be conducted repeatedly under varying contexts.

Computational Efficiency Transfer Learning