deepmodeling/abacus-develop
Sep 2025 – Sep 2025
1 Month active
Languages Used
C++CMakeCUDAHIPMarkdown
Technical Skills
Build System ConfigurationBuild SystemsC++C++ DevelopmentCMakeCUDA
Tianxiang Wang
PROFILE
Tianxiang Wang
Worked on deepmodeling/abacus-develop and cp2k/cp2k, focusing on GPU acceleration, profiling, and stability in scientific computing workflows. Delivered NVTX-based profiling and offloaded Davidson diagonalization to GPUs using C++ and CUDA, enabling detailed performance analysis and faster large-scale computations. Improved build system compatibility with CMake and addressed multi-GPU reliability by dynamically managing CUDA devices. In cp2k/cp2k, resolved a NaN issue in RPA-AXK energy calculations by initializing communication buffers, stabilizing CUDA regression tests and ensuring accurate results. Demonstrated expertise in debugging, performance optimization, and numerical methods, contributing to more robust, maintainable, and high-performance codebases across both repositories.
Overall Statistics
Feature vs Bugs
40%Features
Repository Contributions
5Total
Bugs
3
Commits
5
Features
2
Lines of code
1,125
Activity Months2
Your Network
84 peopleWork History
November 2025
1 Commits
Nov 1, 2025November 2025 monthly summary for the cp2k/cp2k repository focused on stabilizing CUDA regression tests and ensuring accurate energy calculations in RPA-AXK. A critical NaN issue was fixed by initializing communication buffers during energy calculations, improving test reliability and result accuracy across CUDA runs.
1 Commits
Nov 1, 2025November 2025 monthly summary for the cp2k/cp2k repository focused on stabilizing CUDA regression tests and ensuring accurate energy calculations in RPA-AXK. A critical NaN issue was fixed by initializing communication buffers during energy calculations, improving test reliability and result accuracy across CUDA runs.
November 2025
September 2025
4 Commits • 2 Features
Sep 1, 2025September 2025 monthly summary for deepmodeling/abacus-develop focusing on key deliverables, fixes, impact, and technical capability demonstrated. The team delivered profiling and GPU acceleration capabilities, stabilized the build across CUDA versions and build configurations, and ensured reliability in multi-GPU environments. This period's work enhances performance visibility, accelerates large-scale computations, and improves maintainability and robustness of the codebase.
September 2025
4 Commits • 2 Features
Sep 1, 2025September 2025 monthly summary for deepmodeling/abacus-develop focusing on key deliverables, fixes, impact, and technical capability demonstrated. The team delivered profiling and GPU acceleration capabilities, stabilized the build across CUDA versions and build configurations, and ensured reliability in multi-GPU environments. This period's work enhances performance visibility, accelerates large-scale computations, and improves maintainability and robustness of the codebase.
Activity
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Quality Metrics
Correctness92.0%
Maintainability88.0%
Architecture90.0%
Performance88.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
C++CMakeCUDAFortranHIPMarkdown
Technical Skills
Build System ConfigurationBuild SystemsC++C++ DevelopmentCMakeCUDACUDA programmingDebuggingDocumentationGPU ComputingHIPLinear AlgebraPerformance OptimizationPerformance ProfilingROCm
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline
cp2k/cp2k
Nov 2025 – Nov 2025
1 Month active
Languages Used
Fortran
Technical Skills
CUDA programmingnumerical methodsscientific computing