NVIDIA/TensorRT-LLM
Nov 2025 – Dec 2025
2 Months active
Languages Used
PythonCUDA
Technical Skills
NVIDIA TensorRTPyTorchdeep learningmachine learningCUDA programmingGPU optimization
Tri Dao
PROFILE
Tri Dao
During a three-month period, Dao Minh Tri contributed to deep learning infrastructure by building and stabilizing features in the NVIDIA/TensorRT-LLM and confident-ai/deepeval repositories. He added Glm4MoeForCausalLM model support to enable mixture-of-experts causal language modeling, and refactored CUDA kernel synchronization for dsv3, replacing inline assembly with CUDA API calls to improve maintainability and performance. In deepeval, he resolved a runtime error in the MMLU benchmark by correcting a dataset variable, enhancing evaluation reliability. His work demonstrated depth in CUDA programming, GPU optimization, and PyTorch, focusing on robust, production-ready solutions for large-scale machine learning inference pipelines.
Overall Statistics
Feature vs Bugs
67%Features
Repository Contributions
3Total
Bugs
1
Commits
3
Features
2
Lines of code
1,033
Activity Months3
Your Network
279 people
Work History
December 2025
1 Commits • 1 Features
Dec 1, 2025Monthly summary for 2025-12: Focused on stabilizing and accelerating the NVIDIA/TensorRT-LLM path for dsv3. Delivered CUDA kernel synchronization improvements and resolved a PDL-related MOE issue, enhancing performance, reliability, and maintainability of the inference pipeline by refactoring synchronization to use CUDA APIs instead of inline assembly.
1 Commits • 1 Features
Dec 1, 2025Monthly summary for 2025-12: Focused on stabilizing and accelerating the NVIDIA/TensorRT-LLM path for dsv3. Delivered CUDA kernel synchronization improvements and resolved a PDL-related MOE issue, enhancing performance, reliability, and maintainability of the inference pipeline by refactoring synchronization to use CUDA APIs instead of inline assembly.
December 2025
November 2025
1 Commits • 1 Features
Nov 1, 2025November 2025 monthly summary for NVIDIA/TensorRT-LLM. Key delivery: Glm4MoeForCausalLM Model Support, enabling causal language modeling with mixture-of-experts capabilities in the library. Implemented in commit fc088e642c08e0c2b3cc49e242703a19ebc31bc6, advancing the platform's model deployment options.
November 2025
1 Commits • 1 Features
Nov 1, 2025November 2025 monthly summary for NVIDIA/TensorRT-LLM. Key delivery: Glm4MoeForCausalLM Model Support, enabling causal language modeling with mixture-of-experts capabilities in the library. Implemented in commit fc088e642c08e0c2b3cc49e242703a19ebc31bc6, advancing the platform's model deployment options.
May 2025
1 Commits
May 1, 2025May 2025 monthly summary for confident-ai/deepeval: Delivered a targeted bug fix in the MMLU benchmark to ensure stable prompt generation and evaluation. Corrected a dataset variable name typo to prevent an undefined-variable runtime error, improving reliability of evaluation prompts and data integrity. The change is tracked in commit 7382043108f540a701359c38c32f53e433400d59, with impact on downstream benchmarking runs and CI stability.
1 Commits
May 1, 2025May 2025 monthly summary for confident-ai/deepeval: Delivered a targeted bug fix in the MMLU benchmark to ensure stable prompt generation and evaluation. Corrected a dataset variable name typo to prevent an undefined-variable runtime error, improving reliability of evaluation prompts and data integrity. The change is tracked in commit 7382043108f540a701359c38c32f53e433400d59, with impact on downstream benchmarking runs and CI stability.
May 2025
Activity
Loading activity data...
Quality Metrics
Correctness100.0%
Maintainability86.6%
Architecture93.4%
Performance93.4%
AI Usage33.4%
Skills & Technologies
Programming Languages
CUDAPython
Technical Skills
Bug FixCUDA programmingGPU optimizationNVIDIA TensorRTParallel computingPyTorchRefactoringdeep learningmachine learning
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline
confident-ai/deepeval
May 2025 – May 2025
1 Month active
Languages Used
Python
Technical Skills
Bug FixRefactoring