AdvancedResearchComputing/examples
Jun 2025 – Jun 2026
13 Months active
Languages Used
BashShellCC++InputMarkdownPythonGo
Technical Skills
Code OrganizationDocumentationHPCQuantum ChemistryShell ScriptingSystem Administration
nbraunsc
PROFILE
Nbraunsc
Over thirteen months, contributed to AdvancedResearchComputing/examples by developing and refining 37 features that streamline high-performance computing workflows for scientific research. Focused on reproducibility and maintainability, the work included building ready-to-run simulation templates, scalable SLURM job scripts, and containerized environments for tools like Amber, VASP, and LAMMPS. Leveraged Python, Bash, and C/C++ to automate deployment, optimize resource allocation, and support both CPU and GPU workloads. Enhanced onboarding and documentation to reduce setup time and errors, while archiving legacy examples for clarity. The approach emphasized modular code organization and robust configuration management, enabling efficient, reproducible research on HPC clusters.
Overall Statistics
Feature vs Bugs
90%Features
Repository Contributions
59Total
Bugs
4
Commits
59
Features
37
Lines of code
1,510,354
Activity Months13
Your Network
68 peopleShared Repositories
20
Adeyemi AinaMember
Matthew BrownMember
ckuhlmanMember
Saikat DeyMember
Saikat DeyMember
Eslam Ali Hassan HusseinMember
Eslam Ali Hassan HusseinMember
Ayat MohammedMember
sarah-ghazanfariMember
Work History
June 2026
1 Commits • 1 Features
Jun 1, 2026June 2026 focused on enabling scalable HPC workloads by delivering ready-to-run templates and configurations for common HPC stacks. The repository readiness improvements aim to accelerate experimentation, benchmarking, and reproducibility for high-performance simulations.
1 Commits • 1 Features
Jun 1, 2026June 2026 focused on enabling scalable HPC workloads by delivering ready-to-run templates and configurations for common HPC stacks. The repository readiness improvements aim to accelerate experimentation, benchmarking, and reproducibility for high-performance simulations.
June 2026
May 2026
3 Commits • 2 Features
May 1, 2026Concise monthly summary for May 2026 focusing on key accomplishments, business value, and technical execution for AdvancedResearchComputing/examples.
May 2026
3 Commits • 2 Features
May 1, 2026Concise monthly summary for May 2026 focusing on key accomplishments, business value, and technical execution for AdvancedResearchComputing/examples.
April 2026
2 Commits • 2 Features
Apr 1, 2026April 2026 monthly summary focusing on delivering tangible HPC capabilities and stabilizing the software stack. Key features delivered include a GPU-Accelerated Linear System Solver Example (NVIDIA cuDSS) with a complete build and job submission workflow, and a VASP module version upgrade in SLURM scripts to boost performance and compatibility. Major bugs fixed: none reported this month. Overall impact: enables faster prototyping and execution of GPU-accelerated workflows for sparse linear systems, improves job throughput and stability in the HPC environment, and increases reproducibility through updated tooling and documentation. Technologies/skills demonstrated: NVIDIA cuDSS, GPU acceleration, SLURM scripting, Makefiles, Bash scripting, and Linux module management. This aligns with business value by accelerating solution times, reducing friction for GPU-enabled experiments, and ensuring up-to-date software stacks for production workloads.
2 Commits • 2 Features
Apr 1, 2026April 2026 monthly summary focusing on delivering tangible HPC capabilities and stabilizing the software stack. Key features delivered include a GPU-Accelerated Linear System Solver Example (NVIDIA cuDSS) with a complete build and job submission workflow, and a VASP module version upgrade in SLURM scripts to boost performance and compatibility. Major bugs fixed: none reported this month. Overall impact: enables faster prototyping and execution of GPU-accelerated workflows for sparse linear systems, improves job throughput and stability in the HPC environment, and increases reproducibility through updated tooling and documentation. Technologies/skills demonstrated: NVIDIA cuDSS, GPU acceleration, SLURM scripting, Makefiles, Bash scripting, and Linux module management. This aligns with business value by accelerating solution times, reducing friction for GPU-enabled experiments, and ensuring up-to-date software stacks for production workloads.
April 2026
March 2026
7 Commits • 3 Features
Mar 1, 2026March 2026 monthly summary for AdvancedResearchComputing/examples: Delivered GPU-accelerated simulation workflows and a cluster-ready MD toolkit, improving reproducibility, resource utilization, and interactive job capabilities. Consolidated GPU assets, enhanced ML-IAP/LAMMPS integration, and added GPU-based VASP support with clearer execution messaging. Achieved notable code quality improvements via typo fixes and message clarifications, and refreshed repository hygiene with a personal account adjustment to align with project conventions. Overall, these efforts accelerated setup and execution of molecular dynamics and materials simulations on ARC clusters while sharpening documentation and maintainability.
March 2026
7 Commits • 3 Features
Mar 1, 2026March 2026 monthly summary for AdvancedResearchComputing/examples: Delivered GPU-accelerated simulation workflows and a cluster-ready MD toolkit, improving reproducibility, resource utilization, and interactive job capabilities. Consolidated GPU assets, enhanced ML-IAP/LAMMPS integration, and added GPU-based VASP support with clearer execution messaging. Achieved notable code quality improvements via typo fixes and message clarifications, and refreshed repository hygiene with a personal account adjustment to align with project conventions. Overall, these efforts accelerated setup and execution of molecular dynamics and materials simulations on ARC clusters while sharpening documentation and maintainability.
February 2026
3 Commits • 3 Features
Feb 1, 2026February 2026 — AdvancedResearchComputing/examples: Delivered three HPC workflow improvements to enhance usability, onboarding, and resource reliability. Key features include a Dimer VTST example for VASP with MD inputs, GPU cluster configuration, and execution scripts; a Julia command-line example to demonstrate CLI usage and output writing; and an updated SLURM compute environment using Miniforge3 with revised memory allocations for modern HPC environments. Major bugs fixed: none reported this month. Overall impact: accelerates VTST workflows for computational chemistry and materials science, reduces onboarding time for new users, and improves resource reliability and efficiency on GPU-enabled clusters. Technologies/skills demonstrated: Python scripting for HPC workflows, Julia CLI development, SLURM job scripting, and environment modernization with Miniforge3.
3 Commits • 3 Features
Feb 1, 2026February 2026 — AdvancedResearchComputing/examples: Delivered three HPC workflow improvements to enhance usability, onboarding, and resource reliability. Key features include a Dimer VTST example for VASP with MD inputs, GPU cluster configuration, and execution scripts; a Julia command-line example to demonstrate CLI usage and output writing; and an updated SLURM compute environment using Miniforge3 with revised memory allocations for modern HPC environments. Major bugs fixed: none reported this month. Overall impact: accelerates VTST workflows for computational chemistry and materials science, reduces onboarding time for new users, and improves resource reliability and efficiency on GPU-enabled clusters. Technologies/skills demonstrated: Python scripting for HPC workflows, Julia CLI development, SLURM job scripting, and environment modernization with Miniforge3.
February 2026
January 2026
2 Commits • 1 Features
Jan 1, 20262026-01 Monthly Summary: Delivered ORCA workflow enhancements in the AdvancedResearchComputing/examples repo, focusing on example usage and parallel execution. No major bugs reported for this period. Impact includes enabling researchers to run ORCA simulations on Slurm in parallel, improving throughput and scalability, along with maintainable and discoverable workflow examples.
January 2026
2 Commits • 1 Features
Jan 1, 20262026-01 Monthly Summary: Delivered ORCA workflow enhancements in the AdvancedResearchComputing/examples repo, focusing on example usage and parallel execution. No major bugs reported for this period. Impact includes enabling researchers to run ORCA simulations on Slurm in parallel, improving throughput and scalability, along with maintainable and discoverable workflow examples.
December 2025
3 Commits • 2 Features
Dec 1, 2025December 2025 performance summary for AdvancedResearchComputing/examples focused on delivering robust workflow enhancements and SLURM-ready submission improvements, with a clear emphasis on business value, reliability, and maintainability of HPC pipelines.
3 Commits • 2 Features
Dec 1, 2025December 2025 performance summary for AdvancedResearchComputing/examples focused on delivering robust workflow enhancements and SLURM-ready submission improvements, with a clear emphasis on business value, reliability, and maintainability of HPC pipelines.
December 2025
November 2025
1 Commits • 1 Features
Nov 1, 2025Month: 2025-11 — Delivered a streamlined Quantum ESPRESSO CPU workflow in AdvancedResearchComputing/examples by adding a simplified CPU version example, new input files, and updated SLURM job submission scripts. Legacy examples were archived to reduce confusion and create a clearer, repeatable structure for running simulations, improving reproducibility, onboarding, and execution efficiency in HPC environments. The work delivers tangible business value by accelerating research workflows and enabling scalable use of shared HPC resources.
November 2025
1 Commits • 1 Features
Nov 1, 2025Month: 2025-11 — Delivered a streamlined Quantum ESPRESSO CPU workflow in AdvancedResearchComputing/examples by adding a simplified CPU version example, new input files, and updated SLURM job submission scripts. Legacy examples were archived to reduce confusion and create a clearer, repeatable structure for running simulations, improving reproducibility, onboarding, and execution efficiency in HPC environments. The work delivers tangible business value by accelerating research workflows and enabling scalable use of shared HPC resources.
October 2025
2 Commits • 1 Features
Oct 1, 2025Concise monthly summary for 2025-10: Delivered Wolfram Mathematica SLURM HPC demonstration and optimization in AdvancedResearchComputing/examples. Implemented a demonstration script to run Mathematica on an HPC environment and a SLURM batch script to execute it, with resource configuration to optimize CPU usage per task. Notable commits: d7d7d3fb614ab422cbf94dd9177194b6b55b189a (added example for wolfram-mathematica, readme to be added) and 42afbf019b68faf5a0bff7b2de62d742364c7fb2 (edited batch SLURM script). No major bugs fixed this month. Impact: enables scalable, reproducible Mathematica workflows on HPC, improving experimentation throughput and resource utilization. Technologies/skills demonstrated: HPC orchestration, SLURM, batch scripting, resource optimization, version control, and Mathematica integration.
2 Commits • 1 Features
Oct 1, 2025Concise monthly summary for 2025-10: Delivered Wolfram Mathematica SLURM HPC demonstration and optimization in AdvancedResearchComputing/examples. Implemented a demonstration script to run Mathematica on an HPC environment and a SLURM batch script to execute it, with resource configuration to optimize CPU usage per task. Notable commits: d7d7d3fb614ab422cbf94dd9177194b6b55b189a (added example for wolfram-mathematica, readme to be added) and 42afbf019b68faf5a0bff7b2de62d742364c7fb2 (edited batch SLURM script). No major bugs fixed this month. Impact: enables scalable, reproducible Mathematica workflows on HPC, improving experimentation throughput and resource utilization. Technologies/skills demonstrated: HPC orchestration, SLURM, batch scripting, resource optimization, version control, and Mathematica integration.
October 2025
September 2025
8 Commits • 5 Features
Sep 1, 2025September 2025 monthly summary for AdvancedResearchComputing/examples: Delivered a suite of GPU-accelerated HPC experiments, scalable execution scripts, and documentation improvements that improve reproducibility, onboarding, and research throughput. The month focused on adding GPU-enabled workflows, expanding the FDMNES and PyTorch/R example sets, and cleaning up the repository to reduce noise while enhancing accessibility for ARC cluster users. Key business value and outcomes: - Faster time-to-research: GPU-enabled examples and standardized SLURM scripts shorten setup time for high-performance simulations and ML workloads. - Reproducibility and clarity: Updated READMEs and SLURM configurations provide clear CPU/GPU usage guidance and run-file hygiene across projects. - Scalable HPC readiness: New input configurations and SLURM scripts support TiO2, V2O3, LAPW, multiple scattering, and TDDFT in FDMNES; PyTorch and R examples now include portable, scalable scripts. - Operational cleanliness: Removed large generated outputs to reduce clutter and improve repository navigation and CI sanity. Technologies/skills demonstrated: - GPU-accelerated workflows and CUDA-aware Linux scripting - SLURM workload management and job scripting - PyTorch (CPU/GPU) and CIFAR-10 workflows; R with SLURM-friendly runs - Documentation craftsmanship and HPC usage guidance
September 2025
8 Commits • 5 Features
Sep 1, 2025September 2025 monthly summary for AdvancedResearchComputing/examples: Delivered a suite of GPU-accelerated HPC experiments, scalable execution scripts, and documentation improvements that improve reproducibility, onboarding, and research throughput. The month focused on adding GPU-enabled workflows, expanding the FDMNES and PyTorch/R example sets, and cleaning up the repository to reduce noise while enhancing accessibility for ARC cluster users. Key business value and outcomes: - Faster time-to-research: GPU-enabled examples and standardized SLURM scripts shorten setup time for high-performance simulations and ML workloads. - Reproducibility and clarity: Updated READMEs and SLURM configurations provide clear CPU/GPU usage guidance and run-file hygiene across projects. - Scalable HPC readiness: New input configurations and SLURM scripts support TiO2, V2O3, LAPW, multiple scattering, and TDDFT in FDMNES; PyTorch and R examples now include portable, scalable scripts. - Operational cleanliness: Removed large generated outputs to reduce clutter and improve repository navigation and CI sanity. Technologies/skills demonstrated: - GPU-accelerated workflows and CUDA-aware Linux scripting - SLURM workload management and job scripting - PyTorch (CPU/GPU) and CIFAR-10 workflows; R with SLURM-friendly runs - Documentation craftsmanship and HPC usage guidance
August 2025
11 Commits • 7 Features
Aug 1, 2025August 2025 – AdvancedResearchComputing/examples: Delivered cross‑repo HPC workflow improvements focused on containerized MPI workflows, no‑MPI usability, and cluster‑level documentation hygiene. Implemented CP2K internal MPI in Apptainer, introduced a no‑MPI Dalton workflow, enhanced ParaView and Gaussian 16 readiness with updated SLURM and documentation, added vLLM deployment guidance, and standardized cluster‑wide documentation/scripts for consistent usage on ARC infrastructure. A targeted SLURM account fix for ParaView improved resource allocation accuracy. These changes reduce setup time, improve reproducibility, and enable scalable, containerized workloads on ARC clusters.
11 Commits • 7 Features
Aug 1, 2025August 2025 – AdvancedResearchComputing/examples: Delivered cross‑repo HPC workflow improvements focused on containerized MPI workflows, no‑MPI usability, and cluster‑level documentation hygiene. Implemented CP2K internal MPI in Apptainer, introduced a no‑MPI Dalton workflow, enhanced ParaView and Gaussian 16 readiness with updated SLURM and documentation, added vLLM deployment guidance, and standardized cluster‑wide documentation/scripts for consistent usage on ARC infrastructure. A targeted SLURM account fix for ParaView improved resource allocation accuracy. These changes reduce setup time, improve reproducibility, and enable scalable, containerized workloads on ARC clusters.
August 2025
July 2025
13 Commits • 7 Features
Jul 1, 2025July 2025 monthly summary for AdvancedResearchComputing/examples focused on delivering scalable deployment capabilities, improved documentation, onboarding, and repository hygiene across multiple HPC-oriented examples. The work emphasizes business value by enabling reproducible, cluster-agnostic execution and streamlined user onboarding, while achieving concrete technical milestones across TensorFlow, cuQuantum, SU2/WRF, STREAM, OpenMM, and CP2K workflows.
July 2025
13 Commits • 7 Features
Jul 1, 2025July 2025 monthly summary for AdvancedResearchComputing/examples focused on delivering scalable deployment capabilities, improved documentation, onboarding, and repository hygiene across multiple HPC-oriented examples. The work emphasizes business value by enabling reproducible, cluster-agnostic execution and streamlined user onboarding, while achieving concrete technical milestones across TensorFlow, cuQuantum, SU2/WRF, STREAM, OpenMM, and CP2K workflows.
June 2025
3 Commits • 2 Features
Jun 1, 2025June 2025 monthly summary for AdvancedResearchComputing/examples. Focused on enhancing reproducibility and maintainability of OpenMolcas and related examples by improving SLURM workflow integration, consolidating run instructions, and organizing example directories. Deliverables include a streamlined SLURM submission workflow, clearer documentation, and consistent naming, along with archival of outdated components to reduce confusion for new users. These changes reduce setup time, minimize deployment errors, and lay groundwork for future automation and scalability.
3 Commits • 2 Features
Jun 1, 2025June 2025 monthly summary for AdvancedResearchComputing/examples. Focused on enhancing reproducibility and maintainability of OpenMolcas and related examples by improving SLURM workflow integration, consolidating run instructions, and organizing example directories. Deliverables include a streamlined SLURM submission workflow, clearer documentation, and consistent naming, along with archival of outdated components to reduce confusion for new users. These changes reduce setup time, minimize deployment errors, and lay groundwork for future automation and scalability.
June 2025
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Quality Metrics
Correctness92.2%
Maintainability89.6%
Architecture89.2%
Performance85.0%
AI Usage21.0%
Skills & Technologies
Programming Languages
BashCC++CUDAFortranGoInputInput File FormatJuliaLAMMPS
Technical Skills
ANSYSAmber simulationBashBenchmarkingCC/C++ developmentCFDCP2KCode OrganizationComputational PhysicsConfiguration ManagementContainerizationDeep LearningDocumentationGPU Computing
Repositories Contributed To
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