activity
20162024
most citedTuning for Software Analytics: is it Really Necessary?

218 citations · 232 across the 5 of their papers we have counts for

collaborators

5 papers

cs.DC2024

ESG: Pipeline-Conscious Efficient Scheduling of DNN Workflows on Serverless Platforms with Shareable GPUs

Xinning Hui, Yuanchao Xu, Zhishan Guo +1

Recent years have witnessed increasing interest in machine learning inferences on serverless computing for its auto-scaling and cost effective properties. Existing serverless compu…

cs.LG202411 cited

SmartMem: Layout Transformation Elimination and Adaptation for Efficient DNN Execution on Mobile

Wei Niu, Md Musfiqur Rahman Sanim, Zhihao Shu +5

This work is motivated by recent developments in Deep Neural Networks, particularly the Transformer architectures underlying applications such as ChatGPT, and the need for performi…

cs.DC2023

BitGNN: Unleashing the Performance Potential of Binary Graph Neural Networks on GPUs

Jou-An Chen, Hsin-Hsuan Sung, Xipeng Shen +2

Recent studies have shown that Binary Graph Neural Networks (GNNs) are promising for saving computations of GNNs through binarized tensors. Prior work, however, mainly focused on a…

cs.LG20223 cited

Survey: Exploiting Data Redundancy for Optimization of Deep Learning

Jou-An Chen, Wei Niu, Bin Ren +2

Data redundancy is ubiquitous in the inputs and intermediate results of Deep Neural Networks (DNN). It offers many significant opportunities for improving DNN performance and effic…

cs.SE2016218 cited

Tuning for Software Analytics: is it Really Necessary?

Wei Fu, Tim Menzies, Xipeng Shen

Context: Data miners have been widely used in software engineering to, say, generate defect predictors from static code measures. Such static code defect predictors perform well co…