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Achievements

Achievement: YOLOAchievement: QuickdrawAchievement: Pull Sharkx2Achievement: Pair Extraordinaire

Achievements

Achievement: YOLOAchievement: QuickdrawAchievement: Pull Sharkx2Achievement: Pair Extraordinaire

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jfdev001/README.md

Jared Frazier

Software engineer with 2 years of experience in high performance computing (HPC) environments, working on large-scale simulation software such as the ICON climate/weather model. Experienced in performance optimization, automation, and DevOps

Current interests

  • High performance computing + DevOps in these environments
  • Machine learning + climate modelling
  • Finite element/volume methods
  • Computational fluid dynamics
  • Compiler development

Free and Open-Source Software (FOSS) Contributions

FTorch | 10+ merged pull-requests to one of the most popular production-grade Fortran/PyTorch interoperability libraries

  • Designed and deployed GitHub Actions CI/CD pipelines for Intel oneAPI and GCC toolchains, expanding multi-compiler support and improving cross-platform build reliability (PRs).
  • Implemented automatic pkg-config file generation, simplifying library integration into legacy build systems (PR).
  • Enabled static library builds, allowing deployment in operational models where dynamic linking is restricted (PR).
  • Diagnosed and resolved subtle compilation issues, improving test-suite stability and build reproducibility (PRs).
  • Provided ongoing maintenance and community support (all PRs, all issues).

Other Open-Source Contributions | 10+ merged pull-requests and issues to scientific computing projects in C, Fortran, and Julia

  • Ferrite.jl: Improved developer documentation and resolved broken links, enhancing library usability (PRs, issues).
  • PETSc: Corrected API documentation and tutorial examples for the world's most widely used parallel numerical software library (PRs).
  • fftpack: Refactored CMake-based build system to remove unused configuration logic (PR).
  • pFUnit: Identified and reported dependency edge-case failures affecting downstream HPC projects (issues).
  • SpeedyWeather.jl: Identified 5 reproducibility issues in documented examples, improving scientific correctness (issues).

Pinned Loading

  1. algebraic-multigrid algebraic-multigrid Public

    Cross platform algebraic multigrid implementation using C++, Eigen3, and Catch2. For autodidactic purposes.

    C++ 3 1

  2. hello-sparse-blas hello-sparse-blas Public

    Boilerplate Modern CMake project with Fortran and Intel MKL SpBLAS. Optional unit testing and arbitrary dependency fftpack included for illustrative purposes.

    CMake 3

  3. icon-model-machine-learning-backbone icon-model-machine-learning-backbone Public

    Configuration boilerplate for using PyTorch ML models in ICON.

    Fortran 1

  4. PlasmaCellDiff PlasmaCellDiff Public

    Julia implementation of "Quantitative modeling of the terminal differentiation of B cells and mechanisms of lymphomagenesis" by Martinez 2012 (https://doi.org/10.1073/pnas.1113019109)

    Julia

  5. parallel-nbody parallel-nbody Public

    C MPI + OpenMP implementation of n-body simulation for the Parallel Programming Practical (PPP) course at Vrije Universiteit.

    C

  6. mlp-from-scratch mlp-from-scratch Public

    Implementation and extensive report on the multilayer perceptron to elucidate fundamental concepts in deep learning.

    Python