Math

This PDF is my Bachelor Thesis (german), the grade for the thesis is 1,3 (see this entry in wikipedia for a comparison of grades). I am pretty proud about it. Apart from diving into evolutionary algorithms, implementing these from scratch on CUDA C/C++ and applying those within the context of a specific problem domain (portfolio optimization) was a lot of fun.

It was a great opportunity to utilize the latest tech, C/C++ and CUDA ... I was able to achieve a speedup of 22 on a GPU (GTX560Ti) in comparison to one CPU core. I used Latex and the great TexMaker IDE for the text, DIA and Inkscape for drawings, etc.. Some calculations and plots were created with the R package and associated plugins. I used libeigen3 for vector-math on a single cpu core (on GPU I wrote those operations myself).

Now I am just waiting for my actual degree to arrive

That's UBER-fantastic.



After watching this you can probably easily figure out a way to parallelize this algo

And now you can measure quick sort in calories burnt.

Remember O(n log n) ? You better do...

I really like Alan Watt's book as a general introduction to the topic, anyway there's a huge error on page 7 (3rd edition) , where the basics of Matrix operations are described. Rotation around an arbitrary point in 2D space is done by translating to the origin (T1) , rotating (R) , then translating back (T2) . Since Watts' book uses column vectors (like GL, as opposed to row vectors / DirectX) thats basically T2 R T1 x for a given vector x. Well, Alan Watts' book shows T1 R T2 x

Still a good book.

I am right now studying linear and non-linear optimizations while attending a mandatory mathematics course @ Universität in Hagen. Functions from R^2 -> R can be easily visualized - guess that qualifies for a textbook example ... Consider this optimization problem





The visualization contained in the course textbook looks like this





This is a contour plot - but I don't think its helpful to just present this graph. The normal plot and the contour graph made things a lot easier for me - I fired up the XMaxima CAS, and plotted this graph and it's contour graph






From an educational and visual point of view I think it's obvious which one is easier to grasp for a student ...

The Eigen Project (LGPL, thank god) has a cool comparison of linear algebra packages on their homepage.

The first one compares older packages, this benchmark is from 2008. You can find it here

The interesting new one compares only the faster new libraries: Here it is.

Greetings