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Deep Learning HDL Processing System

Simulate deep learning processor IP core interface

Since R2023b

    Libraries:

    Description

    The Deep Learning HDL Processing System block simulates the deep learning processor IP core and models, simulates, and validates the hand-shaking logic between the pre- and post-processing systems and the deep learning processor IP core. The block icon changes depending on the RunTimeControl property setting of the dlhdl.ProcessorConfig object. To access the block at the MATLAB® command line, enter:

    open_system('dlhdllib')

    RunTimeControl SettingBlock Icon
    RegisterRegister Ports
    PortPort Inputs

    Examples

    Limitations

    • Batch processing mode for the deep learning processor IP core is not supported for simulation.

    • The data type of the dlhdl.ProcessorConfig data type must be set to single. The int8 data type is not supported.

    • The top-level properties of the dlhdl.ProcessorConfig object must all be set to "Port" or "Register". A mix of port and register parameter settings is not supported.

    • Multiple input networks are not supported.

    Ports

    Input

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    Input write data control bus, specified as a bus. The bus control signals are of type BusAXIWriteCtrlM2S and includes these signals:

    Signal NameData Type
    wr_addruint32 scalar
    wr_lenuint32 scalar
    wr_validBoolean scalar

    Data Types: BusAXIWriteCtrlM2S

    Input data, specified as a scalar or vector.

    Data Types: uint32

    Input data read control bus, specified as a bus. The bus control signals are of type BusAXIReadCtrlM2S and includes these signals:

    Signal NameData Type
    rd_addruint32 scalar
    rd_lenuint32 scalar
    rd_avalidboolean scalar
    rd_dreadyboolean scalar

    Data Types: BusAXIReadCtrlM2S

    Input DDR memory write data control bus, specified as a bus. The bus control signals are of type BusAXIWriteCtrlM2S and includes these signals:

    Signal NameData Type
    wr_addruint32 scalar
    wr_lenuint32 scalar
    wr_validBoolean scalar

    Data Types: BusAXIWriteCtrlm2S

    Input DDR memory data specified as a scalar or vector.

    Data Types: ufix128

    Input DDR memory read data control bus, specified as a bus. The bus data type is BusAXIReadCtrlM2S and includes these signals:

    Signal NameData Type
    rd_addruint32 scalar
    rd_lenuint32 scalar
    rd_avalidboolean scalar
    rd_dreadyboolean scalar

    Data Types: BusAXIReadCtrlM2S

    Data processing start signal, specified as a boolean.

    Dependencies

    To enable this port, set the RunTimeControl property of the dlhdl.ProcessorConfig object to "port".

    Data Types: Boolean

    Number of input data frames, specified as a int32 scalar.

    Dependencies

    To enable this port, set the RunTimeControl property of the dlhdl.ProcessorConfig object to "port".

    Data Types: int32

    Data streaming stop signal, specified as a boolean.

    Dependencies

    To enable this port, set the RunTimeControl property of the dlhdl.ProcessorConfig object to "port".

    Data Types: Boolean

    Next input frame ready signal, specified as a boolean.

    Dependencies

    To enable this port, set the RunTimeControl property of the dlhdl.ProcessorConfig object to "port".

    Data Types: Boolean

    Current output data read complete signal, specified as a boolean.

    Dependencies

    To enable this port, set the RunTimeControl property of the dlhdl.ProcessorConfig object to "port".

    Data Types: Boolean

    Output

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    Output data write control bus, returned as a bus. The bus control signals are of type BusAXIWriteCtrlS2M and includes these signals:

    Signal NameData Type
    wr_readyboolean scalar
    wr_completeboolean scalar

    Data Types: BusAXIWriteCtrlS2M

    Output data returned as a scalar or vector.

    Data Types: uint32

    Output data read control bus, returned as a bus. The bus control signals are of type BusAXIReadCtrlS2M and includes these signals:

    Signal NameData Type
    rd_areadyboolean scalar
    rd_dvalidboolean scalar

    Data Types: BusAXIReadCtrlS2M

    Output DDR memory data write control bus, returned as a bus. The bus control signals are of type BusAXIWriteCtrlS2M and includes these signals:

    Signal NameData Type
    wr_readyboolean scalar
    wr_completeboolean scalar

    Data Types: BusAXIWriteCtrlS2M

    Output DDR memory data returned as a scalar or vector.

    Data Types: ufix128

    Output DDR memory data read control bus, returned as a bus. The bus control signals are of type BusAXIReadCtrlS2M and includes these signals:

    Signal NameData Type
    rd_areadyboolean scalar
    rd_dvalidboolean scalar

    Data Types: BusAXIReadCtrlS2M

    Input data memory address signal returned, as a uint32 scalar.

    Dependencies

    To enable this port, set the RunTimeControl property of the dlhdl.ProcessorConfig object to "port".

    Data Types: uint32

    Size of next input data frame, returned as a uint32 scalar. The input data frame size is measured in bytes.

    Dependencies

    To enable this port, set the RunTimeControl property of the dlhdl.ProcessorConfig object to "port".

    Data Types: uint32

    Input data valid signal, returned as a boolean.

    Dependencies

    To enable this port, set the RunTimeControl property of the dlhdl.ProcessorConfig object to "port".

    Data Types: Boolean

    Processed output data memory address signal, returned as a uint32 scalar.

    Dependencies

    To enable this port, set the RunTimeControl property of the dlhdl.ProcessorConfig object to "port".

    Data Types: uint32

    Size of next output data frame signal, returned as a uint32 scalar. Use this signal when the OutputValid signal is on.

    Dependencies

    To enable this port, set the RunTimeControl property of the dlhdl.ProcessorConfig object to "port".

    Data Types: uint32

    Output data valid signal, returned as a boolean scalar.

    Dependencies

    To enable this port, set the RunTimeControl property of the dlhdl.ProcessorConfig object to "port".

    Data Types: Boolean

    Data processing complete signal, returned as a boolean scalar.

    Dependencies

    To enable this port, set the RunTimeControl property of the dlhdl.ProcessorConfig object to "port".

    Data Types: Boolean

    Parameters

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    Name of network object, specified as one of these options:

    • Network from MATLAB function — Provide the name of the MATLAB function that returns a network object.

    • Network from MAT-file — Provide the path to the MAT-file that stores the network object.

    Name of the MATLAB function that returns a network object.

    Dependencies

    To enable this parameter, set Network to Network from MATLAB function.

    Path to MAT-file that contains the network object.

    Dependencies

    To enable this parameter, set Network to Network from MAT-file.

    Name of network activation layer to simulate. The default activation layer is the last layer of the network object specified by the Network parameter.

    Maximum input frame number limit to calculate DDR memory access allocation.

    Processor Configuration Properties

    Import an existing dlhdl.ProcessorConfig object. if you specify a function name, it must be a MATLAB function. For example, this MATLAB function returns a dlhdl.ProcessorConfig object called hPCinMATLAB.

    function hPCinMATLAB = hPCinMATLAB()
    hPC = dlhdl.ProcessorConfig;
    hPC.RunTimeControl = "port";
    hPCinMATLAB = hPC;
    end

    After you add the MATLAB function name or dlhdl.ProcessorConfig object, click Apply to import the processor configuration or MATLAB configuration into the block.

    Export a dlhdl.ProcessorConfig object. The default object name is hPCInSimulink.

    Convolution Module

    Enable or disable convolution module generation. Use this parameter to control generation of the convolution module as a part of the deep learning processor configuration.

    Dependencies

    To edit this parameter, enable Export Processor Configuration to MATLAB Workspace.

    Enable or disable LRN block generation. Use this parameter to control generation of the LRN block as a part of the convolution module of the deep learning processor configuration.

    Dependencies

    To edit this parameter, enable Export Processor Configuration to MATLAB Workspace.

    Enable or disable segmentation block generation. Use this parameter to control generation of the segmentation block as a part of the convolution module of the deep learning processor configuration.

    Dependencies

    To edit this parameter, enable Export Processor Configuration to MATLAB Workspace.

    Number of parallel convolution processor kernel threads.

    This parameter is the number of parallel 3-by-3 convolution kernel threads that are a part of the conv module in the dlhdl.ProcessorConfig object.

    Dependencies

    To edit this parameter, enable Export Processor Configuration to MATLAB Workspace.

    This parameter is read-only.

    Input memory cache BRAM size. This parameter is a 3-D matrix that represents the maximum input image size permitted by the BRAM of the conv module in the dlhdl.ProcessorConfig object.

    Dependencies

    To edit this parameter, enable Export Processor Configuration to MATLAB Workspace.

    Output memory cache BRAM size.

    This parameter is a 3-D matrix that represents the maximum output image size permitted by the BRAM of the conv module in the dlhdl.ProcessorConfig object.

    Dependencies

    To edit this parameter, enable Export Processor Configuration to MATLAB Workspace.

    Maximum input and output feature size.

    This parameter is a positive integer that represents the maximum input and output feature size as a part of the conv module in the dlhdl.ProcessorConfig object.

    Dependencies

    To edit this parameter, enable Export Processor Configuration to MATLAB Workspace.

    FC Module

    Enable or disable fully connected module generation. Use this parameter to control generation of the fully connected module as a part of the deep learning processor configuration.

    Dependencies

    To edit this parameter, enable Export Processor Configuration to MATLAB Workspace.

    Enable or disable Softmax block generation. Use this parameter to control generation of the Softmax block as a part of the fully connected module of the deep learning processor configuration. When you clear this parameter, the Softmax layer is still implemented in software.

    Dependencies

    To edit this parameter, enable Export Processor Configuration to MATLAB Workspace.

    Number of parallel fully connected (FC) MAC threads. This parameter is the number of parallel FC MAC threads that are a part of the fc module in the dlhdl.ProcessorConfig object.

    Dependencies

    To edit this parameter, enable Export Processor Configuration to MATLAB Workspace.

    Input memory cache BRAM size. This parameter is an unsigned integer that represents the input cache memory size permitted by the BRAM of the fc module in the dlhdl.ProcessorConfig object.

    Dependencies

    To edit this parameter, enable Export Processor Configuration to MATLAB Workspace.

    Output memory cache BRAM size. This parameter is an unsigned integer that represents the output cache memory size permitted by the BRAM of the fc module in the dlhdl.ProcessorConfig object.

    Dependencies

    To edit this parameter, enable Export Processor Configuration to MATLAB Workspace.

    Custom Module

    Enable or disable custom module generation. Use this parameter to control generation of the adder module as a part of the deep learning processor configuration.

    Dependencies

    To edit this parameter, enable Export Processor Configuration to MATLAB Workspace.

    Enable or disable addition layer generation. Use this parameter to control generation of the addition layer as a part of the custom module of the deep learning processor configuration.

    Dependencies

    To edit this parameter, enable Export Processor Configuration to MATLAB Workspace.

    Enable or disable multiplication layer generation. Use this parameter to control generation of the multiplication layer as a part of the custom module of the deep learning processor configuration.

    Dependencies

    To edit this parameter, enable Export Processor Configuration to MATLAB Workspace.

    Enable or disable 2-D resize layer generation. Use this parameter to control generation of the 2-D resize layer as a part of the custom module of the deep learning processor configuration.

    Dependencies

    To edit this parameter, enable Export Processor Configuration to MATLAB Workspace.

    Enable or disable sigmoid layer generation. Use this parameter to control generation of the sigmoid layer as a part of the custom module of the deep learning processor configuration.

    Dependencies

    To edit this parameter, enable Export Processor Configuration to MATLAB Workspace.

    Enable or disable tanh layer generation. Use this parameter to control generation of the tanh layer as a part of the custom module of the deep learning processor configuration.

    Dependencies

    To edit this parameter, enable Export Processor Configuration to MATLAB Workspace.

    Enable or disable mish layer generation. Use this parameter to control generation of the mish layer as a part of the custom module of the deep learning processor configuration.

    Dependencies

    To edit this parameter, enable Export Processor Configuration to MATLAB Workspace.

    Enable or disable swish layer generation. Use this parameter to control generation of the swish layer as a part of the custom module of the deep learning processor configuration.

    Dependencies

    To edit this parameter, enable Export Processor Configuration to MATLAB Workspace.

    Input memory cache BRAM size. This parameter is an unsigned integer that represents the input cache memory size permitted by the BRAM of the custom module in the dlhdl.ProcessorConfig object.

    Dependencies

    To edit this parameter, enable Export Processor Configuration to MATLAB Workspace.

    Output memory cache BRAM size. This parameter is an unsigned integer that represents the input cache memory size permitted by the BRAM of the custom module in the dlhdl.ProcessorConfig object.

    Dependencies

    To edit this parameter, enable Export Processor Configuration to MATLAB Workspace.

    Processor Top Level

    This parameter is read-only.

    Select the interface type for all deep learning processor IP core interface signals. Specify whether the run-time input signals, run-time feedback signals, input interface control input signals, and input interface control feedback signals are implemented as registers or ports.

    Dependencies

    To enable and edit this parameter, enable Export Processor Configuration to MATLAB Workspace.

    This parameter is read-only.

    Deep learning processor IP core mode setting. Specify whether the run-time input signals to the deep learning processor IP core are implemented as registers or ports.

    This parameter is read-only.

    Feedback signals from deep learning processor IP core control. Specify whether the run-time output signals from the deep learning processor IP core are implemented as registers or ports.

    This parameter is read-only.

    Deep learning processor IP core input interface control.

    This parameter is read-only.

    Deep learning processor IP core output interface control.

    This parameter is read-only.

    Deep learning processor IP core user interface control.

    Deep learning processor IP core module data type.

    Dependencies

    To edit this parameter, enable Export Processor Configuration to MATLAB Workspace.

    This parameter is read-only.

    Enable this option to export a structure containing address locations to the MATLAB workspace.

    Version History

    Introduced in R2023b