Description
Neural-network models can be optimized and executed for high-performance inference on NVIDIA GPUs. This is useful for developers deploying computer vision, language, recommendation, or other deep-learning workloads where latency and throughput matter.
The platform depends on NVIDIA drivers, CUDA compatibility, and model conversion choices. Users should validate accuracy, supported layers, GPU memory use, and deployment constraints before using optimized engines in production.