This work is about implementing the Support Points Algorithm(SP) given here: https://arxiv.org/abs/1609.01811 The authors claim to have better respresentation of a distribution through this algorithms while being almost as intensive as the standard MC or QMC algorithms. The results are presented over Normal and Expoenential Distribution(simple cases) and the plots show how well the samples cover the distribution over the space. This approach Could be very interesting where sampling is expensive; also in GPs, a GP is just one sample over a multivariate normal distribution. This algorithm gives a better chance of picking up a good sample over MC.