ALiEn – a GPU-accelerated artificial life simulation program

This was my first thought after looking at the project. Just finished the book.. wild!

I think you need to read the first few chapters of After Virtue to appreciate the concept behind creating things for people to enjoy directly; it's a form of art, essentially reducing the overgrown calculator known as a "computer" to a beautiful vase holding a flower arrangement.

Here is the link: https://archive.org/details/4.Macintyre/page/n17/mode/2up

This is a sort of test playground for marketing, brands, and so on since the programs occupy a no man's land between games, academic research, toys, entertainment, and programming.

It also satisfies the self-feeding dogfood condition: similar to games such as RoboWar, it is difficult to resist the temptation to experiment at the simulation level, a phenomenon that could be described as the MFTL effect.

http://www.catb.org/~esr/jargon/html/M/MFTL.html

I've written a lot of software against GPUs, albiet some years back. The main challenge was that many of the best libraries had CUDA support (or CuDNN support on top) but not support for other GPU lines' frameworks.

Getting CUDA to work well is hard. Not hard on your laptop, not hard on a particular machine but hard to work everywhere when you dont know the target environment beforehand -- there are different OSs, different OS versions, different versions of CUDA, different cards with different capabilities. But we did get it to work fairly widely across client machines.

The same effort needs to be put into getting things to work for other manufacturers, except a layer deeper since now you're not even standardized on CUDA. Many companies just dont make the investment. Our startup didn't, because we wouldn't find people who could make it work cost effectively.

What I really wish is that the other manufacturers would themselves test popular frameworks against a matrix of cards under different operating systems and versions. We see some of that, for example, with the effort of getting TensorFlow to run on Apple's m1 and metal. I just dont see a random startup (e.g., mine w/ 12 employees) being able to achieve this.

For example, if I know from the manufacturer that I could get TensorFlow X to work on GPU Y on {Centos N, Ubuntu 18/20}, I would gladly expand support to those GPUs. But sometimes you dont know if it is even possible and you spin your wheels for days or weeks -- and if the marketshare for the card is limited, the business justification for the effort is hard to make. The manufacturers can address this issue.

There is an old artificial life simulator (darwinbots http://wiki.darwinbots.com/w/Main_Page ) that is inspired by grobots-like programming games. Each organism is driven by its own code that can mutate randomly at each reproduction.

I've been trying to produce a web version of it. This is where I got so far (before more or less desisting):

http://darwinjs.herokuapp.com/

the difference between current AMD and Nvidia GPUs isn't even that large if viewed from price/performance ratio... Comparing cards at similar price has AMD having slightly less performance while having significantly more GDDR memory.

i still use an RTX3080 though, thankfully got one before the current craze started