NVIDIA/CUDALibrarySamples
Nov 2024 – Jul 2025
4 Months active
Languages Used
C++CMakeCUDAMarkdownCMakeScript
Technical Skills
C++CMakeCUDACUDA ProgrammingExample Code MaintenanceGPU Computing
Angelika Schwarz
PROFILE
Angelika Schwarz
Over four months, Alexander Schwarz contributed to NVIDIA/CUDALibrarySamples by developing and refining GPU-accelerated linear algebra sample code. He implemented new examples for eigenvalue and eigenvector computations using cuDSS and cuSOLVER, including workflows for double complex matrices and alternatives to deprecated APIs. His work involved C++ and CUDA, with careful integration into CMake-based build systems and thorough documentation updates to support onboarding and reproducibility. Alexander also addressed correctness in sparse matrix conversions, fixing COO to CSR logic to prevent downstream errors. His contributions demonstrated depth in numerical methods and high-performance computing, enhancing both reliability and breadth of the sample repository.
Overall Statistics
Feature vs Bugs
60%Features
Repository Contributions
5Total
Bugs
2
Commits
5
Features
3
Lines of code
1,915
Activity Months4
Your Network
1388 people
Work History
July 2025
1 Commits • 1 Features
Jul 1, 2025Summary for 2025-07 (NVIDIA/CUDALibrarySamples): - Key features delivered: CuDSS-based eigenvalue counting example for double complex matrices; new driver in CMakeLists.txt; core logic implemented in csreigs2cuDSS_dcomplex.cpp; README updated to document differences between cusolverSp and cuDSS. - Major bugs fixed: None reported this month. - Overall impact and accomplishments: Expands numerical capabilities within the samples, provides a runnable cuDSS workflow for eigenvalue counting on double complex matrices, and improves developer guidance on backend choices, enabling easier performance comparisons. - Technologies/skills demonstrated: CUDA/cuDSS integration, CMake build customization, C++ core algorithm development, and technical documentation for cross-backend comparison (cusolverSp vs cuDSS).
1 Commits • 1 Features
Jul 1, 2025Summary for 2025-07 (NVIDIA/CUDALibrarySamples): - Key features delivered: CuDSS-based eigenvalue counting example for double complex matrices; new driver in CMakeLists.txt; core logic implemented in csreigs2cuDSS_dcomplex.cpp; README updated to document differences between cusolverSp and cuDSS. - Major bugs fixed: None reported this month. - Overall impact and accomplishments: Expands numerical capabilities within the samples, provides a runnable cuDSS workflow for eigenvalue counting on double complex matrices, and improves developer guidance on backend choices, enabling easier performance comparisons. - Technologies/skills demonstrated: CUDA/cuDSS integration, CMake build customization, C++ core algorithm development, and technical documentation for cross-backend comparison (cusolverSp vs cuDSS).
July 2025
May 2025
1 Commits • 1 Features
May 1, 2025Month: 2025-05. Delivered a cuDSS-backed eigenvalue/eigenvector computation example in NVIDIA/CUDALibrarySamples, illustrating an alternative workflow to the deprecated cusolverSpDcsreigvsi. The work includes build-system and documentation updates to enable easy adoption and migration.
May 2025
1 Commits • 1 Features
May 1, 2025Month: 2025-05. Delivered a cuDSS-backed eigenvalue/eigenvector computation example in NVIDIA/CUDALibrarySamples, illustrating an alternative workflow to the deprecated cusolverSpDcsreigvsi. The work includes build-system and documentation updates to enable easy adoption and migration.
March 2025
1 Commits
Mar 1, 2025March 2025 (2025-03) monthly summary for NVIDIA/CUDALibrarySamples focusing on correctness and stability of sparse matrix conversions in sample code. Key deliverable: a targeted bug fix in COO to CSR conversion that prevents incorrect updates of index/value arrays during consecutive elements, ensuring accurate CSR construction and avoiding data population errors in downstream demos. The fix is implemented in commit 5cead8a88aa9247e30dfe27c6f2eb3af2045c03d with the message 'Fix COO to CSR conversion'. Impact: higher reliability of sample workflows that depend on correct sparse matrix conversions and reduced risk of misleading results in tutorials. Technologies/skills demonstrated: C++, CUDA, debugging, Git version control, code review, and patches in sample codebases.
1 Commits
Mar 1, 2025March 2025 (2025-03) monthly summary for NVIDIA/CUDALibrarySamples focusing on correctness and stability of sparse matrix conversions in sample code. Key deliverable: a targeted bug fix in COO to CSR conversion that prevents incorrect updates of index/value arrays during consecutive elements, ensuring accurate CSR construction and avoiding data population errors in downstream demos. The fix is implemented in commit 5cead8a88aa9247e30dfe27c6f2eb3af2045c03d with the message 'Fix COO to CSR conversion'. Impact: higher reliability of sample workflows that depend on correct sparse matrix conversions and reduced risk of misleading results in tutorials. Technologies/skills demonstrated: C++, CUDA, debugging, Git version control, code review, and patches in sample codebases.
March 2025
November 2024
2 Commits • 1 Features
Nov 1, 2024Month 2024-11: NVIDIA/CUDALibrarySamples focused on reliability and broader cuSOLVER coverage in sample code. Delivered a bug fix for the Dorgqr example, added comprehensive Xgeev eigenvalue/eigenvector demonstrations across data types and precision, and updated build/docs to improve reproducibility and onboarding for users and contributors.
November 2024
2 Commits • 1 Features
Nov 1, 2024Month 2024-11: NVIDIA/CUDALibrarySamples focused on reliability and broader cuSOLVER coverage in sample code. Delivered a bug fix for the Dorgqr example, added comprehensive Xgeev eigenvalue/eigenvector demonstrations across data types and precision, and updated build/docs to improve reproducibility and onboarding for users and contributors.
Activity
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Quality Metrics
Correctness94.0%
Maintainability88.0%
Architecture92.0%
Performance86.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
C++CMakeCMakeScriptCUDAMarkdown
Technical Skills
Algorithm ImplementationC++CMakeCUDACUDA ProgrammingExample Code MaintenanceGPU ComputingHigh-Performance ComputingLinear AlgebraNumerical Linear AlgebraNumerical MethodscuDSScuSOLVERcuSPARSEcuSolver
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