dlhdl.ProcessorConfig.estimateResources - Return estimated resources used by custom bitstream configuration - MATLAB (original) (raw)

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Class: dlhdl.ProcessorConfig
Namespace: dlhdl

Return estimated resources used by custom bitstream configuration

Since R2021a

Syntax

Description

estimateResources([processorConfigObject](#mw%5F19fd4c29-0c57-47d9-be24-bc8c148895ca%5Fsep%5Fmw%5F4aaceff3-0437-4357-96fe-ca0f4d3de873)) returns the estimated resources used by the custom bitstream configuration.

example

[resources](#mw%5F90293de6-7227-44e2-9a01-9fb50b6e58e0) = estimateResources([processorConfigObject](#mw%5F19fd4c29-0c57-47d9-be24-bc8c148895ca%5Fsep%5Fmw%5F4aaceff3-0437-4357-96fe-ca0f4d3de873)) returns a table containing the estimated resources used by the custom bitstream configuration.

[resources](#mw%5F90293de6-7227-44e2-9a01-9fb50b6e58e0) = estimateResources([processorConfigObject](#mw%5F19fd4c29-0c57-47d9-be24-bc8c148895ca%5Fsep%5Fmw%5F4aaceff3-0437-4357-96fe-ca0f4d3de873),[Name,Value](#namevaluepairarguments)) returns the estimated resources used by the custom bitstream configuration, with additional options specified by one or more name-value arguments.

Input Arguments

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Processor configuration, specified as adlhdl.ProcessorConfig object.

Name-Value Arguments

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Specify optional pairs of arguments asName1=Value1,...,NameN=ValueN, where Name is the argument name and Value is the corresponding value. Name-value arguments must appear after other arguments, but the order of the pairs does not matter.

Before R2021a, use commas to separate each name and value, and enclose Name in quotes.

Flag to enable the display of reference design resource utilization specified as alogical data type.

Example: 'IncludeReferenceDesign',true

Output Arguments

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Resources used by the custom bitstream configuration, returned as a table.

Examples

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1. Create a default custom processor configuration object. Use thedlhdl.ProcessorConfig class.
   hPC = dlhdl.ProcessorConfig;

2. To retrieve the resources used by the custom processor configuration, call theestimateResources method.

3. Calling estimateResources returns these results:

          Deep Learning Processor Estimator Resource Results  
                         DSPs          Block RAM*     LUTs(CLB/ALUT)  
                    -------------    -------------    -------------

Available 2520 912 274080
------------- ------------- -------------
DL_Processor 722( 29%) 508( 56%) 216119( 79%)

• Block RAM represents Block RAM tiles in Xilinx devices and Block RAM bits in Intel devices

Rapidly prototype the deployment of deep learning networks to your custom board by using the estimateResources function. Estimate the resource utilization of the deep learning processor configuration for your custom board. Optimize the integration of custom IP cores and reference design into your system by using the estimateResources function to estimate the resource utilization of your reference design. The synthesis tool that you use must be in the list of tools supported by the SynthesisTool property of the dlhdl.ProcessorConfig object. For a list of supported tools and device families, see SynthesisTool and SynthesisToolChipFamily.

In this example, estimate the resource utilization for your custom board that has the Kintex® Ultrascale+™ chip family. Also estimate the resource utilization of the reference design for the Xilinx® Zynq® Ultrascale+™ MPSoC ZCU102 board.

Estimate Resource Utilization for Kintex® Ultrascale™ Board

To estimate the resource utilization for your custom board that has a Kintex® Ultrascale™ chip family , use the estimateResource function of the dlhdl.ProcessorConfig object.

1. Add the dlhdl_device_registration.m file to the MATLAB® search path.
2. Create a dlhdl.ProcessorConfig object.
3. Update the SynthesisToolChipFamily and SynthesisToolDeviceName properties of the dlhdl.ProcessorConfig object.
4. Use the estimateResources function to retrieve the resource utilization for your custom board.

Deep Learning HDL Toolbox™ does not support lookup table (LUT) estimation for custom boards.

hPC = dlhdl.ProcessorConfig; hPC.SynthesisToolChipFamily = 'KintexU'; hPC.SynthesisToolDeviceName = 'xcku040-ffva1156-2-e'; hPC.estimateResources

Warning: Device family "KintexU" is not supported for LUT Estimation. Supported families are Zynq, Zynq UltraScale+ and Arria 10.

          Deep Learning Processor Estimator Resource Results

                         DSPs          Block RAM*     LUTs(CLB/ALUT)  
                    -------------    -------------    ------------- 

Available 1920 600 242400 ------------- ------------- ------------- DL_Processor 722( 38%) 508( 85%) 0( 0%)

• Block RAM represents Block RAM tiles in Xilinx devices and Block RAM bits in Intel devices

Estimate Resource Utilization for Custom Reference Design

Estimate the resource utilization for a reference design that you want to integrate into your system that has a Xilinx® Zynq® Ultrascale+™ MPSoC ZCU102 board. Use the estimateResource function with the IncludeReferenceDesign name-value argument. The estimateResources function uses the ResourcesUsed.LogicElements, ResourcesUsed.DSP, and ResourcesUsed.RAM information in the reference design plugin file to perform the resource estimation. To estimate resource utilization for your custom reference design, you must populate your reference design file with values for ResourcesUsed.LogicElements, ResourcesUsed.DSP, and ResourcesUsed.RAM. See ResourcesUsed. The reference design used in this code is located at $supportpackageinstallationfolder/Xilinx/boards/+DLZCU102/+matlab_libiio_3axi4_master_2019_1/plugin_rd.m.

hPC_referencedesign = dlhdl.ProcessorConfig; hPC_referencedesign.estimateResources('IncludeReferenceDesign',true)

          Deep Learning Processor Estimator Resource Results

                         DSPs          Block RAM*     LUTs(CLB/ALUT)  
                    -------------    -------------    ------------- 

Available 2520 912 274080 ------------- ------------- ------------- Total 725( 29%) 586( 65%) 251119( 92%) ReferenceDesign 3( 1%) 78( 9%) 35000( 13%) DL_Processor 722( 29%) 508( 56%) 216119( 79%)

• Block RAM represents Block RAM tiles in Xilinx devices and Block RAM bits in Intel devices

The estimateResources function returns the resource utilization for the reference design and for the deep learning processor configuration.

Supporting Files

Device Registration File

Use the dlhdl_device_registration.m file to register a custom device family. Estimate the resource utilization of the custom device by using the estimateResources function.

type dlhdl_device_registration.m

function hFPGADeviceFamily = dlhdl_device_registration % Register a new device family by providing the following details: % 1. Device Family Name % 2. Vendor(Intel/Xilinx) % 3. DSP Width % 4. RAM Width % 5. RAM Depth % 6. SplitDSP Width(Optional) - alternative DSP Width supported by the DSP macro % 7. SplitRAM Width(Optional) - alternative RAM Width supported by the RAM macro

hFPGADeviceFamily = { ... kintex_ultrascale();... }; end

function hFPGADeviceFamily = kintex_ultrascale() % Datasheets : % https://www.xilinx.com/support/documentation/user_guides/ug579-ultrascale-dsp.pdf % https://www.xilinx.com/support/documentation/user_guides/ug573-ultrascale-memory-resources.pdf hFPGADeviceFamily = hdlcoder.FPGADeviceInfo('Name', 'KintexU'); hFPGADeviceFamily.Vendor = 'Xilinx'; hFPGADeviceFamily.DSPWidth = [27, 18]; hFPGADeviceFamily.RAMWidth = 36; hFPGADeviceFamily.SplitRAMWidth = 18; hFPGADeviceFamily.RAMDepth = 1024; end

Version History

Introduced in R2021a