SteevoThis is the tech that has been missing from many unmanned systems, using multiple inputs such as inertia, GPS, sonar (material identification/density) radar (location and environment mapping), infrared and being able to combine them in real time for programmed logic and decision making, autonomous machines can use the wider parallel processing to determine exact location, map and determine where to go and where to avoid.

Lets say we wanted to map the oceans, how do you determine where you are when GPS doesn't work under water? Get a fixed location, use a combination of sensors to pick a few points to triangulate a location (same way we have a camera angle in games to determine distance to an item) then use them as reference points, and the ability to use a programmable board with things like varying filters based on expected feedback VS actual feedback is new, before we had hardware filters built in and they may have been able to work in perfectly clear water, but add in debris and it became inaccurate, or thermal convection causes scintillation and distortion, so being able to run a kalman filter on multiple systems and deterministically choose the highest accuracy one is new and a huge improvement.

ShredBirdAs far as GPUs go, this one is pretty tame on the transistor count. Will it really offer computational advantages over a modern FPGA? The adaptive filtering does seem like a huge advantage though, that is something software does have over something not easily reconfigured on-the-fly like an FPGA. I'm just curious about the overall computational throughput, though.

Caring1The whole point of a FPGA is the ability to reprogram via a GUI and software.

Caring1Straight over my head, and not afraid to admit it. :laugh:
Only experience I have is with mining using FPGA's, and the software was pre written but could be easily modified.