Decommissioned NVIDIA enterprise GPUs are one of the last remaining sources of idle VRAM. K80 with 24GB of GDDR5 sells for $60, P100-16GB for around $75 and V100-16GB for under $200. Shortcomings and all, it’s important to understand if we can utilize these widely available cards in the modern era. This project to benchmark tesla GPUs has been in the works for almost a year and over the winter I was able to spend many kilowatt hours heating up my studio with GPUs.
This post is one in a series about GANce
Close-readers, twitter-followers and corporeal-comrades will have already beheld the good news that Won Pound by Won Pound has been released! This is Won’s second album-length project (first of course being Post Space released in 2018), and graces listener’s ears courtesy of Minaret Records, a California jazz label.
The record is accompanied by an album-length music video synthesized with GANce, containing a completely unique video for each track. These 93960 frames have been the ultimate goal of this project since it’s inception, and serve as the best demonstration as to what GANce can do. Within the video (linked below), the video for ‘buzzz’ is a personal favorite, demonstrating the three core elements of a projection file blend:
This post is one in a series about GANce
As it stood, the three main features that would comprise the upcoming collaboration with Won Pound (slated for release mid-April) were:
As detailed in the previous post. The effect of these three features can be seen in this demo:
Knowing we had enough runway to add another large feature to the project, and feeling particularly inspired following a visit to Clifford Ross’ exhibit at the Portland Museum of Art, I began exploring the relationship between the projection source video and the output images synthesized by the network.
This post is one in a series about GANce
In collaboration with Won Pound for his forthcoming album release via minaret records I was recently commissioned to lead an expedition into latent space, encountering intelligences of my own haphazard creation.
A word of warning:
This and subsequent posts as well as the GitHub etc. should be considered toy projects. Development thus far has been results-oriented, with my git HEAD following the confusing and exciting. The goal was to make interesting artistic assets for Won’s release, with as little bandwidth as possible devoted to overthinking the engineering side. This is a fun role-reversal, typically the things that leave my studio look more like brushes than paintings. In publishing this work, the expected outcome is also inverted from my typical desire to share engineering techniques and methods; I hope my sharing the results shifts your perspective on the possible ways to bushwhack through latent space.
So, with that out of the way the following post is a summary of development progress thus far. Here’s a demo:
There are a few repositories associated with this work:
If you’re uninterested in the hardware/software configurations for image capture and GPU work, you should skip to Synthesizing Images.