NVIDIA/KAI-Scheduler
Aug 2025 – Aug 2025
1 Month active
Languages Used
Go
Technical Skills
Backend DevelopmentDebuggingKubernetesResource ManagementTesting
Hoa Ngo
PROFILE
Hoa Ngo
Ngo Hoa contributed to both the NVIDIA/KAI-Scheduler and microsoft/presidio repositories, focusing on backend development and machine learning workflows. In KAI-Scheduler, Ngo addressed GPU memory allocation accuracy by standardizing memory unit handling, ensuring the scheduler used MiB values from node labels to prevent over-allocation and improve cluster utilization. For microsoft/presidio, Ngo enabled GPU-accelerated model loading for GLiNER by wiring device-aware configuration into the model’s load path, allowing inference on the appropriate hardware. Working primarily with Python, Go, and Kubernetes, Ngo demonstrated strong debugging and resource management skills, delivering targeted improvements that enhanced reliability and maintainability in production environments.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
2Total
Bugs
1
Commits
2
Features
1
Lines of code
26
Activity Months2
Your Network
64 peopleWork History
December 2025
1 Commits • 1 Features
Dec 1, 2025December 2025 – Microsoft/Presidio: GPU-Accelerated Model Loading for GLiNER delivered by wiring map_location through the GLiNER.from_pretrained load path to enable device-aware GPU inference and remove CPU-only defaults, aligned with configuration and performance goals.
1 Commits • 1 Features
Dec 1, 2025December 2025 – Microsoft/Presidio: GPU-Accelerated Model Loading for GLiNER delivered by wiring map_location through the GLiNER.from_pretrained load path to enable device-aware GPU inference and remove CPU-only defaults, aligned with configuration and performance goals.
December 2025
August 2025
1 Commits
Aug 1, 20252025-08 Monthly Summary for NVIDIA/KAI-Scheduler: Focused on memory accounting accuracy and scheduling reliability. The key bug fix standardizes memory unit handling by using MiB from node labels to correct GPU memory calculations, preventing inflated usage and pods being scheduled beyond actual GPU capacity. This change improves cluster utilization, reduces scheduling errors, and strengthens resource accountability. Demonstrated strong debugging, Git discipline, and collaboration with the NVIDIA/KAI-Scheduler team to ensure correct unit handling and maintainable memory accounting code.
August 2025
1 Commits
Aug 1, 20252025-08 Monthly Summary for NVIDIA/KAI-Scheduler: Focused on memory accounting accuracy and scheduling reliability. The key bug fix standardizes memory unit handling by using MiB from node labels to correct GPU memory calculations, preventing inflated usage and pods being scheduled beyond actual GPU capacity. This change improves cluster utilization, reduces scheduling errors, and strengthens resource accountability. Demonstrated strong debugging, Git discipline, and collaboration with the NVIDIA/KAI-Scheduler team to ensure correct unit handling and maintainable memory accounting code.
Activity
Loading activity data...
Quality Metrics
Correctness100.0%
Maintainability100.0%
Architecture100.0%
Performance100.0%
AI Usage50.0%
Skills & Technologies
Programming Languages
GoPython
Technical Skills
Backend DevelopmentDebuggingKubernetesMachine LearningNLPPythonResource ManagementTesting
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline
microsoft/presidio
Dec 2025 – Dec 2025
1 Month active
Languages Used
Python
Technical Skills
Machine LearningNLPPython