NVIDIA/CUDALibrarySamples
Nov 2024 – Aug 2025
2 Months active
Languages Used
CCUDA
Technical Skills
C programmingCUDAGPU ComputingLinear AlgebraLinear Algebra LibrariesNumerical Analysis
Marcin Rogowski
PROFILE
Marcin Rogowski
Worked on NVIDIA/CUDALibrarySamples to enhance the reliability and maintainability of cuSOLVERMp matrix operations. Focused on improving matrix generation by refactoring logic to ensure diagonal dominance, which increased numerical stability and correctness for downstream applications. Addressed a critical bug by correcting parameter usage across cuSOLVERMp functions, reducing the risk of incorrect computations. Later, modernized the cuSOLVERMp samples by migrating the communication backend from CAL to NCCL, adding FP32 emulation samples, and updating CMake configurations and documentation for the 0.7.0 release. Utilized C, CUDA, and CMake, emphasizing reproducible builds, improved test coverage, and a better developer experience.
Overall Statistics
Feature vs Bugs
67%Features
Repository Contributions
3Total
Bugs
1
Commits
3
Features
2
Lines of code
2,666
Activity Months2
Your Network
1676 peopleSame Organization
@nvidia.com1629
Work History
August 2025
1 Commits • 1 Features
Aug 1, 2025Month: 2025-08 — Delivered modernization work on NVIDIA/CUDALibrarySamples CuSOLVERMp samples, focusing on backend migration, test coverage, and documentation to align with 0.7.0 release. No major defects logged this period; emphasis was on feature delivery, build reproducibility, and developer experience.
1 Commits • 1 Features
Aug 1, 2025Month: 2025-08 — Delivered modernization work on NVIDIA/CUDALibrarySamples CuSOLVERMp samples, focusing on backend migration, test coverage, and documentation to align with 0.7.0 release. No major defects logged this period; emphasis was on feature delivery, build reproducibility, and developer experience.
August 2025
November 2024
2 Commits • 1 Features
Nov 1, 2024November 2024 monthly summary for NVIDIA/CUDALibrarySamples focusing on cuSOLVERMp reliability improvements. Key features delivered include a stability and diagonal dominance enhancement for matrix generation, while a critical bug fix addressed incorrect ja parameter usage across cuSOLVERMp functions. These changes increase numerical stability, correctness, and overall reliability of matrix operations, lowering bug surface and enabling more consistent results for downstream applications.
November 2024
2 Commits • 1 Features
Nov 1, 2024November 2024 monthly summary for NVIDIA/CUDALibrarySamples focusing on cuSOLVERMp reliability improvements. Key features delivered include a stability and diagonal dominance enhancement for matrix generation, while a critical bug fix addressed incorrect ja parameter usage across cuSOLVERMp functions. These changes increase numerical stability, correctness, and overall reliability of matrix operations, lowering bug surface and enabling more consistent results for downstream applications.
Activity
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Quality Metrics
Correctness90.0%
Maintainability86.6%
Architecture80.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
CCUDA
Technical Skills
C programmingC++CMakeCUDAGPU ComputingLinear AlgebraLinear Algebra LibrariesMPINCCLNumerical AnalysiscuSOLVERMp
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