16 citations · 33 across the 5 of their papers we have counts for
5 papers
Scepsy: Serving Agentic Workflows Using Aggregate LLM Pipelines
Marcel Wagenländer, Otto White, Britannio Jarrett +9
Agentic workflows carry out complex tasks by orchestrating multiple large language models (LLMs) and tools. Serving them at a target throughput with low latency is hard because the…
Tenplex: Dynamic Parallelism for Deep Learning using Parallelizable Tensor Collections
Marcel Wagenländer, Guo Li, Bo Zhao +2
Deep learning (DL) jobs use multi-dimensional parallelism, i.e. combining data, model, and pipeline parallelism, to use large GPU clusters efficiently. Long-running jobs may experi…
Quiver: Supporting GPUs for Low-Latency, High-Throughput GNN Serving with Workload Awareness
Zeyuan Tan, Xiulong Yuan, Congjie He +7
Systems for serving inference requests on graph neural networks (GNN) must combine low latency with high throughout, but they face irregular computation due to skew in the number o…
Fast and Flexible Human Pose Estimation with HyperPose
Yixiao Guo, Jiawei Liu, Guo Li +2
Estimating human pose is an important yet challenging task in multimedia applications. Existing pose estimation libraries target reproducing standard pose estimation algorithms. Wh…
Efficient Reinforcement Learning Development with RLzoo
Zihan Ding, Tianyang Yu, Yanhua Huang +5
Many researchers and developers are exploring for adopting Deep Reinforcement Learning (DRL) techniques in their applications. They however often find such an adoption challenging.…