Get Started with Deep Learning HDL Toolbox
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®).
- Supported Networks, Layers, Boards, and Tools
Pretrained deep learning networks and network layers for which code can be generated by Deep Learning HDL Toolbox.
- Try Deep Learning on FPGA with Only Five Additional Lines of MATLAB Code
Use Deep Learning HDL Toolbox to identify objects on a live webcam with the ResNet-18 pretrained network which has been deployed to a FPGA or SoC board.
- Configure Command-Line Session for Intel SoC Device (Deep Learning HDL Toolbox Support Package for Intel FPGA and SoC Devices)
Open a serial command-line session with Intel SoC device.
- Troubleshoot Xilinx Zynq Platform and Development Computer Connection (Deep Learning HDL Toolbox Support Package for Xilinx FPGA and SoC Devices)
To determine if the Xilinx Zynq® platform is properly configured, repeat the steps in TFTP/WFTPD Configuration Guide (Deep Learning HDL Toolbox Support Package for Xilinx FPGA and SoC Devices).
- Deep Learning on FPGA Solution
Rapidly prototype custom deep learning networks on FPGA by leveraging the deep learning on FPGA solution.