TensorRT
TensorRT is NVIDIA's high-performance deep learning inference optimizer and runtime library. It optimizes neural network models to run efficiently on NVIDIA GPUs by performing layer fusion, precision calibration, and kernel auto-tuning. This allows AI applications to achieve maximum throughput and minimal latency during deployment.
AI companies need to deploy models in production with low latency and high throughput, especially for real-time applications like autonomous vehicles, recommendation systems, and large language model serving. TensorRT is the industry-standard solution for optimizing inference on NVIDIA hardware, making it essential for infrastructure engineers at companies using GPU clusters.
🎓 Courses
NVIDIA TensorRT: Accelerating Deep Learning Inference
by NVIDIA DLI
This official NVIDIA course provides hands-on labs for optimizing models with TensorRT across different frameworks and precision modes.
Deploying Deep Learning Models with TensorRT
by NVIDIA
This course teaches practical deployment workflows including model conversion, optimization, and benchmarking with TensorRT.
📖 Books
Accelerating AI with NVIDIA TensorRT: A Practical Guide to High-Performance Inference
Saurabh Shrivastava · 2024
This 2024 book provides comprehensive coverage of TensorRT 8.x features including LLM optimization, multi-GPU deployment, and Triton integration.
CUDA Programming and GPU Performance Optimization: With Applications to Deep Learning
Shane Cook · 2023
While not exclusively about TensorRT, this 2023 book provides essential background on GPU architecture and optimization principles that TensorRT leverages.
🛠️ Tutorials & Guides
TensorRT Official Documentation and Quick Start Guide
The official documentation is essential for learning API usage, best practices, and the latest features.
TensorRT Tutorials Repository
Official sample code covering everything from basic model conversion to advanced plugins and dynamic shapes.
Optimizing TensorFlow Models with TensorRT
Step-by-step guide for converting TensorFlow models to TensorRT with practical optimization tips.
Deploying PyTorch Models with TensorRT
Official PyTorch integration guide showing how to deploy PyTorch models using TensorRT for production.
TensorRT-LLM Tutorial: Deploying and Optimizing LLMs
Essential tutorial for learning how to optimize and deploy large language models using the latest TensorRT-LLM framework.
Learning resources last updated: April 14, 2026