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Peggy Tian

PROFILE

Peggy Tian

Peggy Tang worked on the NVIDIA/cuda-samples repository, focusing on resolving CUDA runtime constraint issues to improve kernel launch reliability and debug-mode stability. She addressed a bug by increasing the pending kernel launch limit in cdpAdvancedQuicksort.cu and enforcing a per-thread register usage cap in the conjugateGradientMultiBlockCG sample’s CMake configuration. Using C++ and CMake, Peggy applied performance tuning and debugging skills to align sample applications with GPU hardware constraints, reducing the risk of launch failures with larger workloads. Her targeted changes enhanced maintainability and future-proofing of the codebase, demonstrating depth in understanding both CUDA runtime behavior and sample configuration.

Overall Statistics

Feature vs Bugs

0%Features

Repository Contributions

2Total
Bugs
1
Commits
2
Features
0
Lines of code
4
Activity Months1

Work History

May 2025

2 Commits

May 1, 2025

Month: 2025-05 – NVIDIA/cuda-samples: Implemented CUDA runtime constraint fixes to improve kernel launch reliability and debug-mode stability. Specifically increased the pending kernel launch limit to 4096 in cdpAdvancedQuicksort.cu and enforced a 128 32-bit registers-per-SM limit in debug mode via CMakeLists.txt in the conjugateGradientMultiBlockCG sample. These changes address GPU runtime constraints, reduce risk of launch failures with larger workloads, and improve debugging stability across sample apps. Commits applied: 611008fa86ecec5e6b54f30a416b9850f7eb0571 (Bug 5236593) and 770e433a9ec260fe659036a43a5d2673b39ce45b (Bug 5056055).

Activity

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Quality Metrics

Correctness80.0%
Maintainability100.0%
Architecture80.0%
Performance70.0%
AI Usage20.0%

Skills & Technologies

Programming Languages

C++CMake

Technical Skills

CUDADebuggingPerformance Tuning

Repositories Contributed To

1 repo

Overview of all repositories you've contributed to across your timeline

NVIDIA/cuda-samples

May 2025 May 2025
1 Month active

Languages Used

C++CMake

Technical Skills

CUDADebuggingPerformance Tuning

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