activity
20182025
collaborators

8 papers

cs.SE2025

Stencil-Lifting: Hierarchical Recursive Lifting System for Extracting Summary of Stencil Kernel in Legacy Codes

Mingyi Li, Junmin Xiao, Siyan Chen +5

We introduce Stencil-Lifting, a novel system for automatically converting stencil kernels written in low-level languages in legacy code into semantically equivalent Domain-Specific…

cs.CE2025

SparStencil: Retargeting Sparse Tensor Cores to Scientific Stencil Computations via Structured Sparsity Transformation

Qi Li, Kun Li, Haozhi Han +7

Sparse Tensor Cores offer exceptional performance gains for AI workloads by exploiting structured 2:4 sparsity. However, their potential remains untapped for core scientific worklo…

cs.LG2021

An Accurate and Efficient Large-scale Regression Method through Best Friend Clustering

Kun Li, Liang Yuan, Yunquan Zhang +1

As the data size in Machine Learning fields grows exponentially, it is inevitable to accelerate the computation by utilizing the ever-growing large number of available cores provid…

cs.DC2021

An Efficient Vectorization Scheme for Stencil Computation

Kun Li, Liang Yuan, Yunquan Zhang +3

Stencil computation is one of the most important kernels in various scientific and engineering applications. A variety of work has focused on vectorization and tiling techniques, a…

cs.DC2021

Reducing Redundancy in Data Organization and Arithmetic Calculation for Stencil Computations

Kun Li, Liang Yuan, Yunquan Zhang +3

Stencil computation is one of the most important kernels in various scientific and engineering applications. A variety of work has focused on vectorization techniques, aiming at ex…

eess.SY2021

AutoFlow: Hotspot-Aware, Dynamic Load Balancing for Distributed Stream Processing

Pengqi Lu, Liang Yuan, Yunquan Zhang +2

Stream applications are widely deployed on the cloud. While modern distributed streaming systems like Flink and Spark Streaming can schedule and execute them efficiently, streaming…