Short presentation on Jupyter Kernel for C++

1. C++ Jupyter Kernel
Kasturi Murthy, PhD

2. Introduction
●
C++ is a very powerful language but lacks intutive character
that programming languages like R and Python offer in the
backdrop of Jupyter Kernel
●
This a short presentation on my experiments with Jupyter
Kernel for C++ (Ubuntu 18.04) covering the following:
– Simple C++ example
– How to Invoke C++ help as and when required
– Xwidgets in conjuction with Observer function
– Invoking Armadillo Linear Algebra Libraries, Random Number Generation and
dimensionality reduction techniques like PCA
●
Set up your programming environment –
Follow Github Instructions

3. Introduction
●
C++ is a very powerful language but lacks intutive character
that programming languages like R and Python in the
backdrop of Jupyter Kernel
●
This a short presentation on my experiments with Jupyter
Kernel for C++ (Ubuntu 18.04) covering the following:
– Simple C++ example
– How to Invoke C++ help as and when required
– Xwidgets in conjuction with Observer function
– Invoking Armadillo Linear Algebra Libraries, Random Number Generation and PCA
●
Set up your programming environment –
Follow Github Instructions

4. C++ Program
● Now, you see on top right side the
[1] The usual C++ stuff
[2] Nothing new initializing a variable ‘x’
[3] What is in the variable ‘x’ - the intutiveness aspect

5. C++ Program
xwidgets

6. C++ Program
C++11 Lambda
Function!

7. Principal Component Analysis (PCA)
➔ Armadillo uses BLAS and LPACK for Matrix
Operations
➔ OpenBLAS used in this example is an
implementation of BLAS (Basic Linear
Algebra Subprograms)

8. Conclusions
● Looked at how to bring Jupyter Kernel Capability to C++
using Xeus-cling
● Looked at:
– Simple C++ example
– How to Invoke C++ help as and when required – inline with code
– Xwidgets in conjuction with Observer Pattern/function
– Invoking Armadillo Linear Algebra Libraries, Random Number Generation and PCA

9. Thanks!