Jianhua Gao's CV

Download my CV or 中文简历

Education

• B.S. in College of Mathematics, Taiyuan University of Technology, July 2017
• Ph.D in School of Computer Science & Technology, Beijing Institute of Technology, June 2023

Work experience

• 11/2021-08/2021: Research Intern
  • Alibaba Infrastructure, Beijing, China
  • Duties included: Investigate the existing mobile deep learning inference framework; Analyze their advantages and disadvantages; Implement a basic deep learning inference framework; Propose innovative improvement methods.
  • Supervisor: Pengcheng Li
• 09/2016-05/2017: Research Intern
  • Computer Network Information Center, Chinese Academy of Sciences, Beijing, China
  • Duties included: Investigate the typical process of image characters recognition using deep neural network; Given a handwritten Tibetan data set, use a DNN model for training and inference; Adjust the model and parameters to achieve the highest accuracy
  • Supervisor: Haiwu He

Skills

• Rich work experience in Linux System
• Programming skills: C/C++, Python, CUDA, and Linux Shell
• Parallel framework: MPI, OpenMP, OpenACC

Publications

A Systematic Survey of General Sparse Matrix-Matrix Multiplication

Jianhua Gao, Weixing Ji, Fangli Chang, Shiyu Han, Bingxin Wei, Zeming Liu, and Yizhuo Wang. (2023). "A Systematic Survey of General Sparse Matrix-Matrix Multiplication." ACM Computing Surveys. 55(12), 244:1-36.

Fast Piecewise Polynomial Fitting of Time-Series Data for Streaming Computing

Jianhua Gao, Weixing Ji, Lulu Zhang, Senhao Shao, Yizhuo Wang, Feng Shi. (2020). "Fast Piecewise Polynomial Fitting of Time-Series Data for Streaming Computing." IEEE Access. 8:43764-43775.

Cube-Based Incremental Outlier Detection for Streaming Computing

Jianhua Gao, Weixing Ji, Lulu Zhang, Anmin Li, Yizhuo Wang, Zongyu Zhang. (2020). "Cube-Based Incremental Outlier Detection for Streaming Computing." Information Sciences. 517:361-376.

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

Jianhua Gao, Weixing Ji, Senhao Shao, Yizhuo Wang, Feng Shi. (2021). "AMF-CSR: Adaptive Multi-Row Folding of CSR for SpMV on GPU." 2021 IEEE 27th International Conference on Parallel and Distributed Systems. 418-425.

Towards Optimal Fast Matrix Multiplication on CPU-GPU Platforms

Senhao Shao, Yizhuo Wang, Weixing Ji, Jianhua Gao. (2022). "Towards Optimal Fast Matrix Multiplication on CPU-GPU Platforms." International Conference on Parallel and Distributed Computing: Applications and Technologies (PDCAT). 223–236.

MMSparse: 2D Partitioning of Sparse Matrix Based on Mathematical Morphology

Zhaonian Tan, Weixing Ji, Jianhua Gao, Yizhuo Wang, Feng Shi. (2020). "MMSparse: 2D Partitioning of Sparse Matrix Based on Mathematical Morphology." Future Generation Computer Systems. 108:521-532.

TaiChi: A Hybrid Compression Format for Binary Sparse Matrix-Vector Multiplication on GPU

Jianhua Gao, Weixing Ji, Zhaonian Tan, Yizhuo Wang, Feng Shi. (2022). "TaiChi: A Hybrid Compression Format for Binary Sparse Matrix-Vector Multiplication on GPU." IEEE Transactions on Parallel and Distributed Systems. 33(12):3732-3745.

Awards & Honors

• Postgraduate period
  • 2018, First Prize in competition area, China Parallel Application Challenge on Domestic CPU, China Computer Federation
  • 2019/2021, Second-Class Academic Scholarship, Beijing Institute of Technology
  • 2020, China Century Group Scholarship, Beijing Institute of Technology
  • 2020, Outstanding Academic Scholarship, Beijing Institute of Technology
  • 2020, Outstanding Student, Beijing Institute of Technology
  • 2021, Second prize, 2021 CCF Computing Intelligence Contest, China Computer Federation
• Undergraduate period
  • 2014-2016, Professional Study Scholarships for three consecutive years, Taiyuan University of Technology
  • 2016, National Encouragement Scholarship, Ministry of Education of the People’s Republic of China
  • 2016, Prize of Excellence (17th/175), Asia Supercomputer Community

Voluntary work

• Volunteer of the 2015 ASC Student Supercomputer Challenge
• Volunteer of the 2022 ChinaSys Workshop