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deploy

Class: dlhdl.Workflow
Package: dlhdl

Deploy the specified neural network to the target FPGA board

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Syntax

deploy(workflowObject)

Description

example

deploy(workflowObject) programs the specified target board with the bitstream and deploys the deep learning network on it.

Input Arguments

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Instance of workflow object, specified as an dlhld.Workflow object.

Examples

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Deploy VGG-19 to the Intel® Arria® 10 SoC development kit that has single data types.

The deploy function starts programming the FPGA device, displays progress messages, and the time it takes to deploy the network.

  1. snet = vgg19;
hTarget = dlhdl.Target('Intel');
hW = dlhdl.Workflow('Network', snet, 'Bitstream', 'arria10soc_single','Target',hTarget);
hW.deploy

  2. ### Programming FPGA bitstream using JTAG ...
### Programming FPGA bitstream has completed successfully.

tableOut =
          offset_name          offset_address     allocated_space 
    _______________________    ______________    _________________

    "InputDataOffset"           "0x00000000"     "24.0 MB"        
    "OutputResultOffset"        "0x01800000"     "4.0 MB"         
    "SystemBufferOffset"        "0x01c00000"     "52.0 MB"        
    "InstructionDataOffset"     "0x05000000"     "20.0 MB"        
    "ConvWeightDataOffset"      "0x06400000"     "276.0 MB"       
    "FCWeightDataOffset"        "0x17800000"     "472.0 MB"       
    "EndOffset"                 "0x35000000"     "Total: 848.0 MB"

### Loading weights to FC Processor.
### 4% finished, current time is 14-Jun-2020 18:31:07.
### 8% finished, current time is 14-Jun-2020 18:31:32.
### 12% finished, current time is 14-Jun-2020 18:31:58.
### 16% finished, current time is 14-Jun-2020 18:32:23.
### 20% finished, current time is 14-Jun-2020 18:32:48.
### 24% finished, current time is 14-Jun-2020 18:33:13.
### 28% finished, current time is 14-Jun-2020 18:33:39.
### 32% finished, current time is 14-Jun-2020 18:34:04.
### 36% finished, current time is 14-Jun-2020 18:34:30.
### 40% finished, current time is 14-Jun-2020 18:34:56.
### 44% finished, current time is 14-Jun-2020 18:35:21.
### 48% finished, current time is 14-Jun-2020 18:35:46.
### 52% finished, current time is 14-Jun-2020 18:36:11.
### 56% finished, current time is 14-Jun-2020 18:36:36.
### 60% finished, current time is 14-Jun-2020 18:37:02.
### 64% finished, current time is 14-Jun-2020 18:37:27.
### 68% finished, current time is 14-Jun-2020 18:37:52.
### 72% finished, current time is 14-Jun-2020 18:38:17.
### 76% finished, current time is 14-Jun-2020 18:38:43.
### 80% finished, current time is 14-Jun-2020 18:39:08.
### 84% finished, current time is 14-Jun-2020 18:39:33.
### 88% finished, current time is 14-Jun-2020 18:39:58.
### 92% finished, current time is 14-Jun-2020 18:40:23.
### 96% finished, current time is 14-Jun-2020 18:40:48.
### FC Weights loaded. Current time is 14-Jun-2020 18:41:06

  1. Create a file in your current working directory called getLogoNetwork.m. Enter these lines into the file:

    function net = getLogoNetwork
    data = getLogoData;
    net  = data.convnet;
end

function data = getLogoData
    if ~isfile('LogoNet.mat')
        url = 'https://www.mathworks.com/supportfiles/gpucoder/cnn_models/logo_detection/LogoNet.mat';
        websave('LogoNet.mat',url);
    end
    data = load('LogoNet.mat');
end

  2. Create an image datastore and split 70 percent of the images into a training data set and 30 percent of the images into a validation data set.

    curDir = pwd;
newDir = fullfile(matlabroot,'examples','deeplearning_shared','data','logos_dataset.zip');
copyfile(newDir,curDir);
unzip('logos_dataset.zip');
imds = imageDatastore('logos_dataset', ...
    'IncludeSubfolders',true, ...
    'LabelSource','foldernames');
[imdsTrain,imdsValidation] = splitEachLabel(imds,0.7,'randomized');

  3. Create a dlhdl.Workflow object which has quantized LogoNet as the network argument, zcu102_int8 as the bitstream, and hTarget as the target argument.

    To quantize the network, you need the products listed under FPGA in Quantization Workflow Prerequisites.

    % Save the pretrained SeriesNetwork object
snet = getLogoNetwork;

% Create a Target object and define the interface to the target board
hTarget = dlhdl.Target('Xilinx','Interface','Ethernet');

% Create a Quantized Network Object

dlquantObj = dlquantizer(snet,'ExecutionEnvironment','FPGA');
dlquantObj.calibrate(imdsTrain);

% Create a workflow object for the SeriesNetwork and using the FPFA bitstream 
hW = dlhdl.Workflow('Network', dlquantObj, 'Bitstream', 'zcu102_int8','Target',hTarget);

  4. Deploy the dlhdl.Workflow object to your target FPGA board by using the deploy method.

    % Deploy the workflow object
hW.deploy;

  5. When you call the deploy method, the method returns:

    ### Programming FPGA Bitstream using Ethernet...
Downloading target FPGA device configuration over Ethernet to SD card ...
# Copied /tmp/hdlcoder_rd to /mnt/hdlcoder_rd
# Copying Bitstream hdlcoder_system.bit to /mnt/hdlcoder_rd
# Set Bitstream to hdlcoder_rd/hdlcoder_system.bit
# Copying Devicetree devicetree_dlhdl.dtb to /mnt/hdlcoder_rd
# Set Devicetree to hdlcoder_rd/devicetree_dlhdl.dtb
# Set up boot for Reference Design: 'AXI-Stream DDR Memory Access : 3-AXIM'

Downloading target FPGA device configuration over Ethernet to SD card done. The system will now reboot for persistent changes to take effect.


System is rebooting . . . . . .
### Programming the FPGA bitstream has been completed successfully.
          offset_name          offset_address     allocated_space 
    _______________________    ______________    _________________

    "InputDataOffset"           "0x00000000"     "48.0 MB"        
    "OutputResultOffset"        "0x03000000"     "4.0 MB"         
    "SystemBufferOffset"        "0x03400000"     "60.0 MB"        
    "InstructionDataOffset"     "0x07000000"     "8.0 MB"         
    "ConvWeightDataOffset"      "0x07800000"     "8.0 MB"         
    "FCWeightDataOffset"        "0x08000000"     "12.0 MB"        
    "EndOffset"                 "0x08c00000"     "Total: 140.0 MB"

### Loading weights to FC Processor.
### FC Weights loaded. Current time is 12-Jun-2020 13:17:56

Version History

Introduced in R2020b

See Also

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