collaborators

5 papers

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…

cs.MS2020

Temporal Vectorization for Stencils

Liang Yuan, Hang Cao, Yunquan Zhang +3

Stencil computations represent a very common class of nested loops in scientific and engineering applications. Exploiting vector units in modern CPUs is crucial to achieving peak p…