The text discusses various tools for monitoring Graphics Processing Units (GPUs) in deep learning applications, including NVIDIA's `nvidia-smi`, `gpustat`, `nvtop`, and `nvitop`. These tools provide a range of features such as real-time monitoring, customizable output, and interactive interfaces. Some tools also offer Python APIs for integrating with popular machine learning frameworks like PyTorch and Keras. Additionally, the text mentions other options such as Jupyter Lab plugins and GPU profiling tools like PyTorch Profiler and NVIDIA's Visual Profiler. The goal of these tools is to help users optimize their GPUs for better performance and efficiency in deep learning applications.