activity
20182025
most citedRelax: Composable Abstractions for End-to-End Dynamic Machine Learning

12 citations · 29 across the 5 of their papers we have counts for

collaborators

5 papers

cs.DC2025★ 4 cited

FlashInfer: Efficient and Customizable Attention Engine for LLM Inference Serving

Zihao Ye, Lequn Chen, Ruihang Lai +8

Transformers, driven by attention mechanisms, form the foundation of large language models (LLMs). As these models scale up, efficient GPU attention kernels become essential for hi…

cs.LG2023★ 12 cited

Relax: Composable Abstractions for End-to-End Dynamic Machine Learning

Ruihang Lai, Junru Shao, Siyuan Feng +16

Dynamic shape computations have become critical in modern machine learning workloads, especially in emerging large language models. The success of these models has driven the deman…

cs.LG2022★ 3 cited

TensorIR: An Abstraction for Automatic Tensorized Program Optimization

Siyuan Feng, Bohan Hou, Hongyi Jin +8

Deploying deep learning models on various devices has become an important topic. The wave of hardware specialization brings a diverse set of acceleration primitives for multi-dimen…

cs.LG2022★ 10 cited

Tensor Program Optimization with Probabilistic Programs

Junru Shao, Xiyou Zhou, Siyuan Feng +7

Automatic optimization for tensor programs becomes increasingly important as we deploy deep learning in various environments, and efficient optimization relies on a rich search spa…

cs.CV2018

Recurrent Residual Module for Fast Inference in Videos

Bowen Pan, Wuwei Lin, Xiaolin Fang +3

Deep convolutional neural networks (CNNs) have made impressive progress in many video recognition tasks such as video pose estimation and video object detection. However, CNN infer…