NVIDIA has officially introduced the Global Performance Tuner, a new feature integrated into the latest release of NVIDIA TensorRT 11.1. This tool is designed to address the complexities of optimizing deep learning models by providing automated, accuracy-aware performance tuning.
By leveraging the Global Performance Tuner, developers can perform end-to-end performance optimization within the TensorRT environment. The system functions by dynamically customizing various optimizations tailored to specific models, a process intended to streamline the deployment of high-performance AI applications.
This development follows the challenges associated with scheduling, which remains a critical stage in deep learning workflows. By automating the tuning process, the feature aims to simplify the optimization path for developers working with diverse AI models, moving beyond traditional, single-build route limitations. Further technical context on the challenges addressed by this tool can be found in the first part of NVIDIA’s technical series on the subject.
Source: NVIDIA
Original article: https://developer.nvidia.com/blog/scaling-nvidia-tensorrt-performance-optimization-beyond-a-single-build-route-with-the-global-performance-tuner-part-2/
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