Weixing Ji (计卫星)

About Weixing Ji (计卫星)

Weixing Ji (计卫星), With an exceptional h-index of 16 and a recent h-index of 11 (since 2020), a distinguished researcher at Beijing Institute of Technology, specializes in the field of Parallel Computing, Program Analysis.

His recent articles reflect a diverse array of research interests and contributions to the field:

JLeaks: A Featured Resource Leak Repository Collected From Hundreds of Open-Source Java Projects

A Systematic Literature Survey of Sparse Matrix-Vector Multiplication

Revisiting thread configuration of SpMV kernels on GPU: A machine learning based approach

Predicting optimal sparse general matrix-matrix multiplication algorithm on GPUs

An Automated Approach to Extracting Local Variables

ConvDarts: a fast and exact convolutional algorithm selector for deep learning frameworks

An Automatic Deployment Method for Hybrid Cloud Simulation Platform

A systematic survey of general sparse matrix-matrix multiplication

Weixing Ji (计卫星) Information

University

Position

Associate Professor School of Computer Science

Citations(all)

712

Citations(since 2020)

337

Cited By

466

hIndex(all)

16

hIndex(since 2020)

11

i10Index(all)

27

i10Index(since 2020)

11

Email

University Profile Page

Google Scholar

Weixing Ji (计卫星) Skills & Research Interests

Parallel Computing

Program Analysis

Top articles of Weixing Ji (计卫星)

JLeaks: A Featured Resource Leak Repository Collected From Hundreds of Open-Source Java Projects

2024/4/12

A Systematic Literature Survey of Sparse Matrix-Vector Multiplication

2024/4/9

Revisiting thread configuration of SpMV kernels on GPU: A machine learning based approach

Journal of Parallel and Distributed Computing

2024/3/1

Predicting optimal sparse general matrix-matrix multiplication algorithm on GPUs

The International Journal of High Performance Computing Applications

2024/2/5

An Automated Approach to Extracting Local Variables

2023/11/30

ConvDarts: a fast and exact convolutional algorithm selector for deep learning frameworks

CCF Transactions on High Performance Computing

2023/9/20

An Automatic Deployment Method for Hybrid Cloud Simulation Platform

2023/8/4

A systematic survey of general sparse matrix-matrix multiplication

2023/3/2

Do bugs lead to unnaturalness of source code?

2022/11/7

Dnnabacus: Toward accurate computational cost prediction for deep neural networks

arXiv preprint arXiv:2205.12095

2022/5/24

Taichi: A hybrid compression format for binary sparse matrix-vector multiplication on gpu

IEEE Transactions on Parallel and Distributed Systems

2022/4/26

Towards Optimal Fast Matrix Multiplication on CPU-GPU Platforms

2021/12/17

AMF-CSR: Adaptive Multi-Row Folding of CSR for SpMV on GPU

2021/12/14

操作系统内核并发错误检测研究进展

2021/1/22

Attentive boundary aware network for multi-scale skin lesion segmentation with adversarial training

Multimedia Tools and Applications

2020/10

MMSparse: 2D partitioning of sparse matrix based on mathematical morphology

Future Generation Computer Systems

2020/7/1

Cube-based incremental outlier detection for streaming computing

Information Sciences

2020/5/1

Fast piecewise polynomial fitting of time-series data for streaming computing

IEEE Access

2020/2/27

Pin-Tool Based Execution Backtracking

2020

Sparse matrix partitioning for optimizing SpMV on CPU-GPU heterogeneous platforms

The International Journal of High Performance Computing Applications

2020/1

See List of Professors in Weixing Ji (计卫星) University(Beijing Institute of Technology)

Co-Authors

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