nvidia-holoscan/holohub
Feb 2025 – Mar 2026
3 Months active
Languages Used
C++CMakeCUDADockerfileShell
Technical Skills
C++CMakeCUDAComputer VisionDockerHoloscan SDK
Colin Tracey
PROFILE
Colin Tracey
Over a three-month period, contributed to the nvidia-holoscan/holohub repository by developing advanced GPU-accelerated computer vision and signal processing features. Delivered a real-time stereo vision application using C++, CUDA, and NVIDIA VPI, enabling robust disparity estimation and visualization within Holoscan workflows. Enhanced compatibility and performance by refactoring stereo processing for CUDA 13 and expanding Holoscan SDK support, ensuring reliable operation across multiple environments. Built an end-to-end radar signal processing pipeline leveraging PVA acceleration, introducing new operators and a demonstration app for radar-to-point-cloud workflows. Emphasized reproducibility and maintainability through Docker-based environments and comprehensive documentation for users and developers.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
3Total
Bugs
0
Commits
3
Features
3
Lines of code
5,039
Activity Months3
Your Network
1671 peopleSame Organization
@nvidia.com1629
Shared Repositories
42
Work History
March 2026
1 Commits • 1 Features
Mar 1, 2026March 2026: Delivered end-to-end PVA-accelerated radar signal processing capability within holohub, including new operators, a demonstration pipeline, and a reproducible development environment. Focused on enabling real-time radar-to-point-cloud processing on PVA-enabled platforms, with thorough documentation and an illustrative demo app. No major bug fixes reported in this period; primary value delivered through feature delivery and knowledge transfer.
1 Commits • 1 Features
Mar 1, 2026March 2026: Delivered end-to-end PVA-accelerated radar signal processing capability within holohub, including new operators, a demonstration pipeline, and a reproducible development environment. Focused on enabling real-time radar-to-point-cloud processing on PVA-enabled platforms, with thorough documentation and an illustrative demo app. No major bug fixes reported in this period; primary value delivered through feature delivery and knowledge transfer.
March 2026
February 2026
1 Commits • 1 Features
Feb 1, 2026February 2026 monthly summary for nvidia-holoscan/holohub: Focused on CUDA 13 readiness and Holoscan SDK compatibility for VPI stereo processing. Implemented NppStreamContext support and _Ctx APIs, refined the VPI stereo undistortion/rectification path, and expanded the Holoscan SDK test matrix with 3.11 while maintaining compatibility with 2.4.0/2.6.0. Local validation on x86-64 dGPU confirms stable GPU-accelerated stereo processing across CUDA 12 and 13.
February 2026
1 Commits • 1 Features
Feb 1, 2026February 2026 monthly summary for nvidia-holoscan/holohub: Focused on CUDA 13 readiness and Holoscan SDK compatibility for VPI stereo processing. Implemented NppStreamContext support and _Ctx APIs, refined the VPI stereo undistortion/rectification path, and expanded the Holoscan SDK test matrix with 3.11 while maintaining compatibility with 2.4.0/2.6.0. Local validation on x86-64 dGPU confirms stable GPU-accelerated stereo processing across CUDA 12 and 13.
February 2025
1 Commits • 1 Features
Feb 1, 2025February 2025: Delivered VPI Stereo Vision Application (vpi_stereo) within nvidia-holoscan/holohub, enabling real-time stereo disparity estimation using NVIDIA VPI, with input processing, rectification, disparity computation, optional hardware acceleration, and Holoviz-based visualization. Focused on robust integration, performance, and extensibility for depth-perception workflows.
1 Commits • 1 Features
Feb 1, 2025February 2025: Delivered VPI Stereo Vision Application (vpi_stereo) within nvidia-holoscan/holohub, enabling real-time stereo disparity estimation using NVIDIA VPI, with input processing, rectification, disparity computation, optional hardware acceleration, and Holoviz-based visualization. Focused on robust integration, performance, and extensibility for depth-perception workflows.
February 2025
Activity
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Quality Metrics
Correctness83.4%
Maintainability80.0%
Architecture83.4%
Performance80.0%
AI Usage46.6%
Skills & Technologies
Programming Languages
C++CMakeCUDADockerfileShell
Technical Skills
C++C++ DevelopmentCMakeCUDAComputer VisionDockerGPU ProgrammingHoloscanHoloscan SDKNVIDIA VPIPVASignal ProcessingStereo Vision
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline