Main Content

Prototype Deep Learning Networks on FPGA

Estimate performance of series networks. Profile and retrieve inference results from target devices using MATLAB®

Deep Learning HDL Toolbox™ provides classes to create objects to deploy series deep learning networks to target FPGA and SoC boards. Before deploying deep learning networks onto target FPGA and SoC boards, leverage the methods to estimate the performance and resource utilization of the custom deep learning network. After you deploy the deep learning network, use MATLAB to retrieve the network prediction results from the target FPGA board.


expand all

dlhdl.WorkflowConfigure deployment workflow for deep learning neural network
dlhdl.TargetConfigure interface to target board for workflow deployment
dlhdl.SimulatorCreate an object that retrieves intermediate layer results and validate deep learning network prediction accuracy


expand all

activations Retrieve intermediate layer results for deployed deep learning network
compile Compile workflow object
deploy Deploy the specified neural network to the target FPGA board
getBuildInfoRetrieve bitstream resource utilization
predictPredict responses by using deployed network
activations Retrieve intermediate layers results for dlhdl.Simulator object
predictRetrieve prediction results for dlhdl.Simulator object
validateConnectionValidate SSH connection and deployed bitstream
releaseRelease the connection to the target device