About Me "Nerver forget where you came from"
I am actively looking for a research internship in high-performance system design in Fall 2019!
My name is Kai Wu (吴凯). I am a Computer Science PhD student in EECS at University of California, Merced, where I am a member of Parallel Architecture, System, and Algorithm Lab (PASA)and advised by Dr. Dong Li. Before coming to UC Merced, I earned my master degree in Computer Science and Engineering from Michigan State University.
My research broadly falls into general areas of high-performance system and architecture design(large-scale parallel/distributed systems). More specifically, I am interested in memory/storage/cache systems.
My most recent research work is focusing on exploring the efficient approach of utilizing emerging non-volatile memory (NVM) in HPC, cloud and database systems.
- Parallel programming models and runtime
- Performance optimization and modeling
[SC'18] Kai Wu, Jie Ren and Dong Li. "Runtime Data Management on Non-Volatile Memory-based Heterogeneous Memory for Task-Parallel Programs". In 30th ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis, 2018.
[ICPP'18] Kai Wu, Wenqian Dong, Qiang Guan, Nathan Debardeleben and Dong Li. "Modeling Application Resilience in Large Scale Parallel Execution". In 47th International Conference on Parallel Processing.
[MCHPC'18] Jie Ren, Kai Wu and Dong Li. "Understanding Application Recomputability without Crash Consistency in Non-Volatile Memory". In Workshop on Memory Centric High Performance Computing held in conjunction with SC’18.
[SC'17] Kai Wu, Yingchao Huang and Dong Li. "Unimem: Runtime Data Management in Non-Volatile Memory-based Heterogeneous Main Memory". In 29th ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis, 2017.
[SC'17] Kai Wu, Qiang Guan, Nathan DeBardeleben and Dong Li. "Characterization and Comparison of Application Resilience for Serial and Parallel Codes". Poster in 29th ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis, 2017.
[Cluster'17] Shuo Yang, Kai Wu, Yifan Qiao, Dong Li and Jidong Zhai. "Algorithm-Directed Persistent Memory for High Performance Computing". In 19th IEEE Cluster Conference.
[NAS'17] Wei Liu, Kai Wu, Jialin Liu, Feng Chen and Dong Li. "Performance Evaluation and Modeling of HPC I/O on Non-Volatile Memory". In 12th International Conference on Networking, Architecture, and Storage, 2017.
Kai Wu, Yingchao Huang and Dong Li. "High Performance Data Persistence in Non-Volatile Memory for Resilient High Performance Computing" (In submission)
[TR] Kai Wu, Qiang Guan, Frank Ober, Shari Hamlin, and Dong Li. Early Evaluation of Intel Optane Non-Volatile Memory with HPC I/O Workloads. Technical Report, PASA Lab, UC Merced.
Research Intern / Lawrence Livermore National Laboratory(LLNL)
Mentor: Maya B Gokhale
May 2018 - Aug 2018
Research Intern / Los Alamos National Laboratory(LANL)
Mentor: Nathan DeBardeleben, Qiang Guan
May 2017 - Aug 2017
Graduate Student Researcher / UC Merced
Advisor: Dong Li
Aug 2016 - Current
External reviewers: SC'18, IPDPS'17, CLUSTER'17, HPCC'17, NAS'17, etc.
Student Volunteer: SC'18, SC'16.
Student Travel Award: SC'18, OSDI'18, ASPLOS'18, NVMW'18, CLUSTER'17, NVMW'17, SC'16
Graduate Travel Fellowship, University of California, Merced, 2018
Bobcat Graduate Research Fellowship, University of California, Merced 2017
China National Scholarship 2013
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