AdvancedResearchComputing/examples
Jan 2026 – Jan 2026
1 Month active
Languages Used
BashJSONMarkdownPythonbashdatplaintext
Technical Skills
GPU ComputingGPU programmingLAMMPSMachine learningPyTorchSLURM job scheduling
Sarah Ghazanfari
PROFILE
Sarah Ghazanfari
Sarah Ghazanfari developed end-to-end, high-performance computing feature demonstrations for the AdvancedResearchComputing/examples repository, focusing on silicon MACE integration in LAMMPS and PFC simulation workflows. She designed reproducible, GPU-accelerated examples that leverage SLURM job scheduling and PyTorch for scalable model training and simulation. Her work included creating shell scripts and data files to streamline SLURM submissions and enable efficient molecular dynamics and phase field crystal simulations on GPU clusters. By emphasizing workflow reproducibility and collaboration readiness, Sarah established a robust foundation for researchers to execute materials simulations, improving research uptime and scalability across computational physics and scientific computing environments.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
9Total
Bugs
0
Commits
9
Features
2
Lines of code
1,031
Activity Months1
Your Network
21 peopleSame Organization
@falcon1.cm.falcon2
Work History
January 2026
9 Commits • 2 Features
Jan 1, 2026January 2026 (2026-01) monthly summary for AdvancedResearchComputing/examples. Focused on delivering end-to-end, HPC-ready feature demonstrations for silicon MACE in LAMMPS and for PFC workflows. No major bugs fixed this month; emphasis was on feature development, reproducible workflows, and enabling scalable GPU/HPC usage. Deliverables establish a solid foundation for researchers to run silicon-specific MACE simulations and PFC demos on GPU clusters with SLURM submission. Overall impact: Accelerated path from research ideas to execution through reusable, well-documented examples; improved reproducibility and scalability for materials simulations on HPC infrastructure.
9 Commits • 2 Features
Jan 1, 2026January 2026 (2026-01) monthly summary for AdvancedResearchComputing/examples. Focused on delivering end-to-end, HPC-ready feature demonstrations for silicon MACE in LAMMPS and for PFC workflows. No major bugs fixed this month; emphasis was on feature development, reproducible workflows, and enabling scalable GPU/HPC usage. Deliverables establish a solid foundation for researchers to run silicon-specific MACE simulations and PFC demos on GPU clusters with SLURM submission. Overall impact: Accelerated path from research ideas to execution through reusable, well-documented examples; improved reproducibility and scalability for materials simulations on HPC infrastructure.
January 2026
Activity
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Quality Metrics
Correctness97.8%
Maintainability91.2%
Architecture93.4%
Performance93.2%
AI Usage20.0%
Skills & Technologies
Programming Languages
BashJSONMarkdownPythonbashdatplaintext
Technical Skills
GPU ComputingGPU programmingLAMMPSMachine learningPyTorchSLURM job schedulingShell ScriptingSlurm scriptingcomputational physicsdata analysisdata modelingdata sciencehigh-performance computingmachine learningmodel training
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