3 ms·
Why the downvotes? My understanding ai is not a use for fpgas because models require a lot of ram (preferably fast ram) and fpga themselves don’t have a lot of
by le-mark 1y ago
Why the downvotes? My understanding ai is not a use for fpgas because models require a lot of ram (preferably fast ram) and fpga themselves don’t have a lot of it. An fpga will have pins you can attach fast ram, but then board layout and layering traces becomes very non trivial. Hence gfx cards (and a lot of them) are more suited.
- throwaway48476 1y agoFPGA will never be as fast as an ASIC. NV data center chips cant do graphics anymore, just compute.
- random_duck 1y agoFunny you say that, if you look at the git repo for the blog there are a bunch of asic screenshots currently being committed.
- HarHarVeryFunny 1y agoSure - not as fast or flexible, but relatively cheap and reprogrammable - good for experimentation, maybe for building a real-world proof-of-concept of a learning architecture ?
- imtringued 1y agoThis doesn't actually matter in practice, because either nobody produces your specific architecture in the first place, or the existing architectures are significantly more power inefficient. FPGAs run at reduced clock speeds, but then again, you'd have to run the GPU or CPU at the same clock speed to obtain the same energy efficiency.
- HarHarVeryFunny 1y agoFPGA certainly not ideal for an experimental AI architecture, but if data is just flowing thru it (sensory input in, motor control out) then I don't see RAM as an issue. Could be an interesting option for experimenting on a mobile robot.