[FPGA Artix7 Basys3 Deep/ Machine learning]

Thank you for your comments. I'll check web pages you linked!

 

Personally, I was guessing the procedure.

-Using any D.L. framework, create a weight file that matches the real configuration (FPGA channel or I/O) 

-Rewrite it to C++ and put it on FPGA with Micro-blaze (soft CPU)

-Based on FPGA input: High/Low, FPGA provides High/Low following the weight file. 

But, if #of FPGA I/O is not sufficient, a couple/few of FPGA must be used. In that case, how is communication among them done....

 

Anyway, I have to investigate it. PYNQ is probably helpful to brush my knowledge up...

[FPGA Artix7 Basys3 Deep/ Machine learning]

Are there any introductive hands-on web pages or articles on Deep/Machine learning on FPGA Artix7 (not ZYNQ or PYNQ) ?? I'm doing deep learning using Tnsorflow or KELAS, and now, I'm thinking of performing it on FPGA Artix7. But, I do not have any clues to start it. If someone knows useful information, could you tell me. 

Best regards.