GPU Processing in R: Is it worth it?
It would be difficult for an R user not to have heard of GPU processing. In 2006, about seven years after it invented the GPU, Nvidia released the first incarnation of CUDA, the architecture that allowed scientists, engineers, and statisticians to use high-end graphics processors as pure floating-point number-crunchers. Today, Nvidia’s CUDA platform, specific for […]
Are Programming Languages Secure?
The informative and instructive posts on this blog about programming in the R Programming Language, and a colleague’s recent suggestion that I use F# for a particular task, got me thinking about the current proliferation of programming languages. As a working college student, I designed and implemented a couple of programming languages and modified […]
Better Performance for R Functions with Vectorization
One of the best things about R is that so many talented people have contributed a multitude of valuable packages. In fact there are so many, that for most tasks you don’t have to do any programming at all. However, there are always going to be problems that require custom treatment and that will demand […]
A Problem with R
The value of R lies in the enormous quantity of code contributed by analysts and academic researchers over many years, providing a packaged solution not only for common analytical techniques but also the esoteric and the obscure. The problem with R, and one that concerns many analysts dealing with large data volumes, is that […]
Charts are Bad — Less UI, More UX
In my work as a decision science oriented software developer, I often explain to my clients that what they really want is a big green button that, when pressed, gives them the answer to the question they are currently wrestling with—a Magic 8-Ball that dispenses specific, data-driven advice. The challenge is, how close I can […]