The article mention EAI's SIMSTAR, a real software reconfigurable analog computer from the 1980s. Here's a description of how that worked.[1] This was pretty good. They had a crosspoint of FET analog switches to pass signals around, so they managed to do this in solid state, without relays. They had a M68000 as a control machine to set up connections. It all worked well enough to allow a real time man-in-the-loop simulation of the F-16 control system.[2] Just barely. The USAF paper says that the biggest problem was keeping the SIMSTAR analog computers alive.
Analog FPGAs have been made, downsizing this sort of thing to chip size. But not recently. The problems seem to be 1) lack of a use case, and 2) noise.
Analog computing is all about noise minimization. This is Not Fun.
There's interest in this stuff for neural nets, which do a lot of clipping and may be less noise-sensitive.
One has to think in different terms in signal to utilize analog. Think collisions in waves that cohere. We can’t have an end goal in hardware dev unless we have an existing software that crudely maps to the goal. We use such imprecise ideas in hardware to compute, they’re arbitrary. Our computers are still at the toy stages. Neural nets are toy models. Think organ stage.
Not really. The amount of analog hardware on die is minimal - it's little more than a few multiplexers surrounding the standard sorts of analog peripherals you'd see on a microcontroller like ADCs/DACs/comparators.
Love this idea. One use case is actually music synthesis as digital tools like supercollider are not that aurally satisfying while making analog circuits is tedious. Software controlled analog is a nice in-between. BTW I mean use case as in "this is cool, I would like to use it" not "bzillion users and a pile of money" ofc haha.
The article mention EAI's SIMSTAR, a real software reconfigurable analog computer from the 1980s. Here's a description of how that worked.[1] This was pretty good. They had a crosspoint of FET analog switches to pass signals around, so they managed to do this in solid state, without relays. They had a M68000 as a control machine to set up connections. It all worked well enough to allow a real time man-in-the-loop simulation of the F-16 control system.[2] Just barely. The USAF paper says that the biggest problem was keeping the SIMSTAR analog computers alive.
Analog FPGAs have been made, downsizing this sort of thing to chip size. But not recently. The problems seem to be 1) lack of a use case, and 2) noise.
Analog computing is all about noise minimization. This is Not Fun.
There's interest in this stuff for neural nets, which do a lot of clipping and may be less noise-sensitive.
[1] https://www.analogmuseum.org/library/simstar_technology.pdf
[2] https://apps.dtic.mil/sti/tr/pdf/ADA189675.pdf
One has to think in different terms in signal to utilize analog. Think collisions in waves that cohere. We can’t have an end goal in hardware dev unless we have an existing software that crudely maps to the goal. We use such imprecise ideas in hardware to compute, they’re arbitrary. Our computers are still at the toy stages. Neural nets are toy models. Think organ stage.
Does https://en.wikipedia.org/wiki/Cypress_PSoC Count? I’ve kinda wanted to try one out but have 0 use case…
Not really. The amount of analog hardware on die is minimal - it's little more than a few multiplexers surrounding the standard sorts of analog peripherals you'd see on a microcontroller like ADCs/DACs/comparators.
Love this idea. One use case is actually music synthesis as digital tools like supercollider are not that aurally satisfying while making analog circuits is tedious. Software controlled analog is a nice in-between. BTW I mean use case as in "this is cool, I would like to use it" not "bzillion users and a pile of money" ofc haha.
See also: Eurorack, FPAAs, Jumperless, Zoxnoxious (https://www.youtube.com/watch?v=LsGcW3EjFYo)
Ullmann to the rescue. We’re indifferent to analog computers like Detroit was once with electric cars.
Ahhh, Vaxman still up to his usual shenannigans :-)
Imagine that, a self-organizing, self-learning software that builds its own hardware. Even dumb primates like us can build ‘em!