cewit's newsletter ran a short piece on what i was doing with the university's supercomputing allocation: audio synthesis and modeling at a scale that does not fit on a desktop.

having that much compute changes which questions you can ask. a lot of audio engineering is choosing a filter design or a basis function on the strength of experience and then tuning it until it sounds right. with a cluster you can search the space instead, evaluating thousands of candidates against a real corpus to find out whether the conventional choice was ever the best one.

the same models apply outside music. forensic audio and medical imaging are both problems of pulling a signal out of noise when you have a decent prior for what the signal should look like.

read the full article, inside the february 2016 newsletter pdf.