This and fully integrated minimal runtime environment is built around the powerful combination of TensorFlow, an open-source machine learning library, Keras, an open-source neural network library, Jupyter Notebook, a browser-based interactive programming, mathematics, and data science environment, and the versatile Python programming language.
Designed with optimization for NVidia GPU in mind, this stack is tailored to leverage the full potential of GPU acceleration. It includes key components like CUDA, a parallel computing platform and API model, and cuDNN, a GPU-accelerated library of primitives specifically crafted for deep neural networks. Furthermore, the stack comes equipped with NVidia drivers and a Development preset, providing a comprehensive suite of program development and building tools, including a C compiler and make utility.
This integrated environment is ideal for data scientists and machine learning practitioners looking to harness the power of NVidia GPU for their computational tasks. Whether you’re working on complex neural network models, deep learning projects, or other GPU-intensive machine learning tasks, this stack provides a seamless and optimized platform to accelerate your work.