You can customize and target the DL HDL Toolbox generated code for any FPGA/ASIC/SoC hardware including Xilinx/AMD devices.
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 or SoC (with HDL Coder™ and Simulink®).
Deep Learning HDL Toolbox Supported Hardware
Support for third-party hardware such as Intel® and Xilinx® FPGA boards
https://www.mathworks.com/help/deep-learning-hdl/supported-hardware.html?s_tid=CRUX_lftnav
Deep Learning Processor Customization and IP Generation
Configure, build, and generate custom bitstreams and processor IP cores, estimate and benchmark custom deep learning processor performance
Deep Learning HDL Toolbox™ provides functions to configure, build, and generate custom bitstreams and a custom processor IP. Obtain performance and resource utilization of a pretrained series network on the custom processor. Optimize the custom processor by using the estimation results.
