CV
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Education
- B.S. in Huazhong University of Science and Technology, 2014
- M.S. in Arizona State University, 2015
- Ph.D. in Arizona State University, 2024
Work experience
- Summer intern, Lawrence Berkeley National Laboratory (May 2023)
- Wrote benchmark programs and characterized the performance of a new parallel discrete event simulation framework with a hybrid communication model.
- Conducted large-scale scalability tests of the simulator with up to 32,768 CPUs on the new HPC cluster (Perlmutter).
- Identified the performance bottlenecks of the under-performed corner cases and improved algorithms that facilitate the synchronization.
Skills
- Programming languages: C++, Python
- Molecular dynamics: LAMMPS, VMD
- Acceleration: MPI, Vectorization, threading (OpenMP), CUDA, OpenACC
- HPC environment: Slurm, Module, Docker
- Machine learning: Pytorch, CNN
- Programming tools: Git, GDB, gprof, NSight
Publications
- Liu, M., Ye, J., & Oswald, J. (2023). Coarse-grained molecular simulation of the role of curing rates on the structure and strength of polyurea. Computational Materials Science, 230, 112428.
- Bachan, J., Ye, J., Jiang, X., Nguyen, T., Natarajan, M., Bremer, M., & Chan, C. (2024, June). Devastator: A Scalable Parallel Discrete Event Simulation Framework for Modern C++. In Proceedings of the 38th ACM SIGSIM Conference on Principles of Advanced Discrete Simulation (pp. 35-46).
- Li, Y., Ye, J., Agrawal, V., & Oswald, J. (2024). Dependence of Thermally Activated Relaxation of Crystalline Stems on the Molecular Topology at Crystalline/Amorphous Interfaces in Polyethylene. Journal of Chemical Theory and Computation.
Teaching
