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TensorFlow GPU with Jupyter Notebook

Take advantage of your GPU and perform powerful parallel computations.  Run GPU-powered Jupyter Notebooks securely in your browser with minimal configuration required for your deep learning projects.

Product Name

TensorFlow GPU with Jupyter Notebook

Product Version

2.0

HPE Ezmeral Container Platform Version

5.2

Overview

TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications. TensorFlow v2 has become easier to use than ever. It offers support for both standard CPU as well as GPU based deep learning. GPUs are mostly used for deep learning training due to their significant speed when compared to CPUs. GPU is preferred for training deep learning systems in a long run for very large datasets. 

Setting TensorFlow up, especially in order to take advantage of GPU acceleration remains something of a chore.  HPE Ezmeral Container Platform offers a pre-configured and fully integrated minimal runtime environment with TensorFlow, an open source software library for machine learning, Keras, an open source neural network library, Jupyter Notebook, a browser-based interactive notebook for programming, mathematics, and data science, and the Python programming language. This stack is optimized for running on GPU.  

Documentation Additional Resources

Explore the industry’s first enterprise-grade container platform for cloud-native and distributed non-cloud native applications, HPE Ezmeral Container Platform.    

Interested in learning more about the HPE Ezmeral Container Platform and TensorFlow? Please contact us to learn more. 

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