APPFL/APPFL
Jul 2025 – Jul 2025
1 Month active
Languages Used
Jupyter NotebookPython
Technical Skills
Distributed SystemsFederated LearningJupyter NotebooksMachine LearningPython
Zilinghan Li
PROFILE
Zilinghan Li
In July 2025, ZL migrated the NERSC notebook examples in the APPFL/APPFL repository from CPU to CUDA execution, enhancing performance and enabling more accurate benchmarking for high-performance computing workflows. Using Python and Jupyter Notebooks, ZL updated the server URI to a fixed IP address, ensuring consistent and reliable access to the notebooks. The work included aligning execution counts and timestamps to reflect the new CUDA-based runs, which improved reproducibility and traceability of results. This focused update addressed the needs of distributed systems and federated learning workflows, with all changes tracked in a dedicated commit to support auditability and transparency.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
827
Activity Months1
Your Network
16 peopleSame Organization
@login23.chn.perlmutter.nersc.gov2
Work History
July 2025
1 Commits • 1 Features
Jul 1, 2025July 2025: Delivered CUDA-enabled updates to NERSC notebook examples in APPFL/APPFL, switching execution from CPU to CUDA, updating the server URI to a fixed IP, and aligning execution counts and timestamps to reflect the new CUDA runs. These changes improve performance, reproducibility, and benchmarking accuracy for HPC workflows. The work is tracked in a commit that adds notebook running results on NERSC for auditability.
1 Commits • 1 Features
Jul 1, 2025July 2025: Delivered CUDA-enabled updates to NERSC notebook examples in APPFL/APPFL, switching execution from CPU to CUDA, updating the server URI to a fixed IP, and aligning execution counts and timestamps to reflect the new CUDA runs. These changes improve performance, reproducibility, and benchmarking accuracy for HPC workflows. The work is tracked in a commit that adds notebook running results on NERSC for auditability.
July 2025
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Jupyter NotebookPython
Technical Skills
Distributed SystemsFederated LearningJupyter NotebooksMachine LearningPython
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