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^®).

Tutorials

• Supported Networks, Layers and Boards
  

  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
  

  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.

• Check Host Computer Connection to FPGA Boards
  

  Troubleshoot computer-to-FPGA board connection.

• Deep Learning on FPGA Solution and Workflows
  

  The figure illustrates the MATLAB^® solution for implementing deep learning on FPGA.

Featured Examples

Get Started with Deep Learning FPGA Deployment on Intel Arria 10 SoC

Create, compile, and deploy a dlhdl.Workflow object that has a handwritten character detection series network object by using the Deep Learning HDL Toolbox™ Support Package for Intel FPGA and SoC. Use MATLAB® to retrieve the prediction results from the target device.

Open Live Script

Get Started with Deep Learning FPGA Deployment on Xilinx ZCU102 SoC

Create, compile, and deploy a dlhdl.Workflow object that has a handwritten character detection series network as the network object by using the Deep Learning HDL Toolbox™ Support Package for Xilinx FPGA and SoC. Use MATLAB® to retrieve the prediction results from the target device.

Open Live Script

Profile Network for Performance Improvement

Improve the performance of the deployed deep learning network, by identifying bottle neck layers from the profiler results.

Open Live Script

Accelerate Prototyping Workflow for Large Networks by using Ethernet

Deploy a deep learning network and obtain prediction results using the Ethernet connection to your target device. You can significantly speed up the deployment and prediction times for large deep learning networks by using Ethernet versus JTAG. This example shows the workflow on a ZCU102 SoC board. The example also works on the other boards supported by Deep Learning HDL Toolbox. See Deep Learning HDL Toolbox Supported Hardware.

Open Live Script