Deep Learning HDL Toolbox™ provides functions and tools to prototype and implement deep learning networks on FPGAs and SoCs. It provides pre-built bitstreams for running a variety of deep learning networks on supported Xilinx® and Intel® FPGA and SoC devices. Profiling and estimation tools let you customize a deep learning network by exploring design, performance, and resource utilization tradeoffs.
Deep Learning HDL Toolbox enables you to customize the hardware implementation of your deep learning network and generate portable, synthesizable Verilog® and VHDL® code for deployment on any FPGA (with HDL Coder™ and Simulink®).
Pretrained deep learning networks and network layers for which code can be generated by Deep Learning HDL Toolbox.
Learn how to use deep learning HDL toolbox to identify objects on a live webcam with the AlexNet pretrained network which has been deployed to a FPGA or SoC board.
Troubleshoot computer-to-FPGA board connection.
The figure illustrates the MATLAB® solution for implementing deep learning on FPGA.