dusty-nv/jetson-containers
Aug 2025 – Aug 2025
1 Month active
Languages Used
C++PythonShell
Technical Skills
Build SystemsCMakeCUDAContainerizationDeep LearningJetPack
David Ung
PROFILE
David Ung
Worked on the dusty-nv/jetson-containers repository to enable CUDA 13.0 support and JetPack compatibility for vLLM builds targeting SM110 hardware. Focused on aligning core dependencies such as CUDA, cuDNN, NCCL, and Triton with JetPack 7.x requirements, implementing targeted patches to ensure reliable builds across updated CUDA architectures. Utilized CMake, Python, and Shell scripting to update build systems and manage package configurations, consolidating changes for broader hardware support. The work delivered foundational updates that streamline future deep learning optimizations and system configuration, addressing compatibility challenges and positioning the stack for ongoing development in containerized, GPU-accelerated environments.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
3Total
Bugs
0
Commits
3
Features
1
Lines of code
412
Activity Months1
Your Network
35 peopleWork History
August 2025
3 Commits • 1 Features
Aug 1, 2025August 2025: Focused on enabling CUDA 13.0 support and JetPack compatibility for the dusty-nv/jetson-containers stack, with emphasis on enabling vLLM builds for SM110. Aligned core dependencies (CUDA/cuDNN/NCCL/Triton) with JetPack 7.x requirements and implemented targeted patches to ensure compatibility and build reliability. Delivered foundational changes that position the project for broader hardware support and future performance optimizations.
3 Commits • 1 Features
Aug 1, 2025August 2025: Focused on enabling CUDA 13.0 support and JetPack compatibility for the dusty-nv/jetson-containers stack, with emphasis on enabling vLLM builds for SM110. Aligned core dependencies (CUDA/cuDNN/NCCL/Triton) with JetPack 7.x requirements and implemented targeted patches to ensure compatibility and build reliability. Delivered foundational changes that position the project for broader hardware support and future performance optimizations.
August 2025
Activity
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Quality Metrics
Correctness86.6%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage40.0%
Skills & Technologies
Programming Languages
C++PythonShell
Technical Skills
Build SystemsCMakeCUDAContainerizationDeep LearningJetPackLLM OptimizationPackage ManagementShell ScriptingSystem Configuration
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