lattice/quda
Mar 2025 – Jul 2025
4 Months active
Languages Used
C++ShellYAML
Technical Skills
BLASCUDAHIPLinear AlgebraBuild SystemsCI/CD
Damon McDougall
PROFILE
Damon Mcdougall
Worked on the lattice/quda repository, focusing on GPU computing and high-performance linear algebra in C++ and CUDA. Over four months, delivered features and bug fixes that stabilized the HIP backend, improved ROCm and hipBLAS compatibility, and enhanced CI/CD workflows using CMake and GitHub Actions. Addressed precision and wavefront size inconsistencies, ensuring reliable host-device synchronization and correct reporting across architectures. Migrated ROCm build pipelines to cloud-based runners, reducing maintenance overhead and increasing reproducibility. The work demonstrated depth in low-level programming, performance optimization, and testing, resulting in more robust, maintainable code and improved runtime stability for complex scientific simulations.
Overall Statistics
Feature vs Bugs
33%Features
Repository Contributions
7Total
Bugs
4
Commits
7
Features
2
Lines of code
237
Activity Months4
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Work History
July 2025
1 Commits
Jul 1, 2025July 2025 monthly summary focusing on key accomplishments in the QUDA HIP backend. Delivered a targeted bug fix to ensure correct wavefront size reporting and stable host-device interaction, improving cross-architecture reliability and user confidence in the QUDA HIP backend.
1 Commits
Jul 1, 2025July 2025 monthly summary focusing on key accomplishments in the QUDA HIP backend. Delivered a targeted bug fix to ensure correct wavefront size reporting and stable host-device interaction, improving cross-architecture reliability and user confidence in the QUDA HIP backend.
July 2025
June 2025
4 Commits • 1 Features
Jun 1, 2025June 2025 monthly summary highlighting the main technical and business value delivered for lattice/quda. Focused on expanding ROCm/hipblas compatibility, stabilizing precision-related tests, and addressing ROCm regressions to improve overall runtime stability and reliability across stacks.
June 2025
4 Commits • 1 Features
Jun 1, 2025June 2025 monthly summary highlighting the main technical and business value delivered for lattice/quda. Focused on expanding ROCm/hipblas compatibility, stabilizing precision-related tests, and addressing ROCm regressions to improve overall runtime stability and reliability across stacks.
April 2025
1 Commits • 1 Features
Apr 1, 2025April 2025 monthly summary for lattice/quda: Delivered migration of ROCm build CI from a self-hosted ROCm environment to a Ubuntu-latest GitHub Actions runner, centralizing and stabilizing ROCm builds across CI. Removed legacy rocm-build-ci.yml and introduced rocm_githubactions_build.yml. Implemented ROCm component installation and CMake configuration on the GitHub Actions runner to enable consistent, reproducible builds in cloud environments. This work includes provisioning a non-self-hosted GitHub runner to improve scalability and reduce maintenance of dedicated CI infrastructure.
1 Commits • 1 Features
Apr 1, 2025April 2025 monthly summary for lattice/quda: Delivered migration of ROCm build CI from a self-hosted ROCm environment to a Ubuntu-latest GitHub Actions runner, centralizing and stabilizing ROCm builds across CI. Removed legacy rocm-build-ci.yml and introduced rocm_githubactions_build.yml. Implemented ROCm component installation and CMake configuration on the GitHub Actions runner to enable consistent, reproducible builds in cloud environments. This work includes provisioning a non-self-hosted GitHub runner to improve scalability and reduce maintenance of dedicated CI infrastructure.
April 2025
March 2025
1 Commits
Mar 1, 2025March 2025 performance-focused update for lattice/quda: focused on stabilizing the HIP backend numeric path by re-enabling double complex support in BatchInvertMatrix, addressing test failures, and improving reliability for complex-valued simulations.
March 2025
1 Commits
Mar 1, 2025March 2025 performance-focused update for lattice/quda: focused on stabilizing the HIP backend numeric path by re-enabling double complex support in BatchInvertMatrix, addressing test failures, and improving reliability for complex-valued simulations.
Activity
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Quality Metrics
Correctness90.0%
Maintainability85.8%
Architecture81.4%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
C++ShellYAML
Technical Skills
BLASBuild SystemsC++CI/CDCMakeCUDAGPU ComputingGitHub ActionsHIPHigh-Performance ComputingLinear AlgebraLow-Level ProgrammingPerformance OptimizationROCmTesting
Repositories Contributed To
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