Changes between Version 30 and Version 31 of Jupyter

Timestamp:

05/21/18 15:09:41 (6 years ago)

Author:

Jens Henrik Goebbert

Comment:

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Jupyter

@@ -15 +15 @@
 * **Big data integration** \\ Leverage big data tools, such as Apache Spark, from Python, R and Scala. Explore that same data with pandas, scikit-learn, ggplot2, !TensorFlow.
 
-* **Language of choice** \\ The Notebook has support for over 40 programming languages, including Python, Julia, R and Bash.
+* **Language of choice** \\ The Notebook has support for over 40 programming languages, including Python, C++ Julia, R and Bash.
 
 ==== !JupyterLab
@@ -72 +72 @@
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-=== How to use your own special software through in a Jupyter-Kernel
-In general the Jupyter Kernel live in the system environment, which is loaded for Jupyter itself.
-This might not suite your needs and you want to switch to a different software stage or want to load additional software modules. In that case you need to set up your own specialized Jupyter kernel. This can be done in a few steps:
+=== Jupyter Kernel - The Computational Engine
+A Jupyter kernel is a “computational engine” that executes the code contained in a Jupyter Notebook document.\\
+Various kernel have been provided by different groups.\\
+Here is a list of available kernels: https://github.com/jupyter/jupyter/wiki/Jupyter-kernels
+
+In general the Jupyter Kernel live in the system environment, which is loaded for Jupyter itself.\\
+On JURECA currently the following kernel are installed:
+* Python
+* C++ (14,17,1z)
+* Julia
+* Bash
+but you can create your own specialized Jupyter kernel if you like (and need).
+
+==== Create your own specialized Jupyter-Kernel
+The installed kernels might not suite your needs and you want to switch to a different software stage or want to load additional software modules. In that case you need to set up your own specialized Jupyter kernel. This can be done in a few steps:
+
+
 
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