You are of course aware that Xilinx has its own flavour of ML stuff that can be pushed onto its FPGA’s. I believe it is mostly geared towards inference, but have you considered checking the plausibility of your ‘as good as a 3090’ estimate against the published performance numbers of the first party solutions?
You are of course aware that Xilinx has its own flavour of ML stuff that can be pushed onto its FPGA’s. I believe it is mostly geared towards inference, but have you considered checking the plausibility of your ‘as good as a 3090’ estimate against the published performance numbers of the first party solutions?
I did not write this post. Just thought it was interesting/relevant for LessWrong.