Avatars Grow Legs: Generating Smooth Human Motion from Sparse Tracking Inputs with Diffusion Model
Yuming Du, Robin Kips, Albert Pumarola, Sebastian Starke, Ali Thabet, Artsiom Sanakoyeu
IEEE Conference on Cloud Computing (CLOUD)
Serverless computing (SC) in an attractive win-win paradigm for cloud providers and customers, simultaneously providing greater flexibility and control over resource utilization for cloud providers while reducing costs through pay-per-use model and no capacity management for customers. While SC has been shown effective for event-triggered web applications, the use of deep learning (DL) applications on SC is limited due to latency-sensitive DL applications and stateless SC. In this paper, we focus on two key problems impacting deployment of distributed inference (DI) models on SC: resource allocation and cold start latency. To address the two problems, we propose a hybrid scheduler for identifying the optimal server resource allocation policy. The hybrid scheduler identifies container allocation based on candidate allocations from greedy strategy as well as deep reinforcement learning based allocation model.
Yuming Du, Robin Kips, Albert Pumarola, Sebastian Starke, Ali Thabet, Artsiom Sanakoyeu
Lisa Rivalin, Andrew Grier, Tobias Tiecke, Chi Zhou, Doris Gao, Prakriti Choudhury, John Fabian
Shreshth Tuli, Kinga Bojarczuk, Natalija Gucevska, Mark Harman, Xiao-Yu Wang, Graham Wright