Intel® FPGA AI Suite: SoC Design Example User Guide

Download PDF
ID 768979
Date 12/01/2023
Public

A newer version of this document is available. Customers should click here to go to the newest version.

Document Table of Contents
Document Table of Contents x
1. Intel® FPGA AI Suite SoC Design Example User Guide 2. About the SoC Design Example 3. Intel® FPGA AI Suite SoC Design Example Quick Start Tutorial 4. Intel® FPGA AI Suite SoC Design Example Run Process 5. Intel® FPGA AI Suite SoC Design Example Build Process 6. Intel® FPGA AI Suite SoC Design Example Intel® Quartus® Prime System Architecture 7. Intel® FPGA AI Suite Soc Design Example Software Components 8. Streaming-to-Memory (S2M) Streaming Demonstration A. Intel® FPGA AI Suite SoC Design Example User Guide Archives B. Intel® FPGA AI Suite SoC Design Example User Guide Document Revision History
2. About the SoC Design Example x
2.1. Intel® FPGA AI Suite SoC Design Example Prerequisites
3. Intel® FPGA AI Suite SoC Design Example Quick Start Tutorial x
3.1. Initial Setup 3.2. Initializing a Work Directory 3.3. (Optional) Create an SD Card Image (.wic) 3.4. Writing the SD Card Image (.wic) to an SD Card 3.5. Preparing the Intel® Arria® 10 SX SoC FPGA Development Kit for the Intel® FPGA AI Suite SoC Design Example 3.6. Adding Compiled Graphs (AOT files) to the SD Card 3.7. Running the Demonstration Applications
3.3. (Optional) Create an SD Card Image (.wic) x
3.3.1. Installing Prerequisite Software for Building an SD Card Image 3.3.2. Building the FPGA Bitstreams 3.3.3. Installing HPS Disk Image Build Prerequisites 3.3.4. (Optional) Downloading the ImageNet Categories 3.3.5. Building the SD Card Image
3.5. Preparing the Intel® Arria® 10 SX SoC FPGA Development Kit for the Intel® FPGA AI Suite SoC Design Example x
3.5.1. Confirming Intel® Arria® 10 SX SoC FPGA Development Kit Board Settings 3.5.2. Connect the Intel® Arria® 10 SX SoC FPGA Development Kit to the Host Development System 3.5.3. Configuring the Intel® Arria® 10 SX SoC FPGA Development Kit UART Connection 3.5.4. Determining the Intel® Arria® 10 SX SoC FPGA Development Kit IP Address
3.6. Adding Compiled Graphs (AOT files) to the SD Card x
3.6.1. Preparing OpenVINO™ Model Zoo 3.6.2. Preparing a Model 3.6.3. Compiling the Graphs 3.6.4. Copying the Compiled Graphs to the SD card
3.7. Running the Demonstration Applications x
3.7.1. Running the M2M Mode Demonstration Application 3.7.2. Running the S2M Mode Demonstration Application 3.7.3. Troubleshooting the Demonstration Applications
4. Intel® FPGA AI Suite SoC Design Example Run Process x
4.1. Exporting Trained Graphs from Source Frameworks 4.2. Compiling Exported Graphs Through the Intel® FPGA AI Suite
5. Intel® FPGA AI Suite SoC Design Example Build Process x
5.1. Building the Intel® Quartus® Prime Project 5.2. Building the Bootable SD Card Image (.wic)
5.1. Building the Intel® Quartus® Prime Project x
5.1.1. Intel® Quartus® Prime Build Flow 5.1.2. Build Script Options 5.1.3. Build Directory
5.1.1. Intel® Quartus® Prime Build Flow x
5.1.1.1. Build Synchronization of FPGA with Software
5.1.3. Build Directory x
5.1.3.1. The create_project.bash Script 5.1.3.2. The generate_sof.bash Script 5.1.3.3. The generate_rbf.bash Script 5.1.3.4. The build_stream_controller.sh Script
6. Intel® FPGA AI Suite SoC Design Example Intel® Quartus® Prime System Architecture x
6.1. Intel® FPGA AI Suite SoC Design Example Inference Sequence Overview 6.2. Memory-to-Memory (M2M) Variant Design 6.3. Streaming-to-Memory (S2M) Variant Design 6.4. Top Level 6.5. The SoC Design Example Platform Designer System 6.6. Fabric EMIF Design Component 6.7. PLL Configuration
6.2. Memory-to-Memory (M2M) Variant Design x
6.2.1. The mSGDMA Intel FPGA IP 6.2.2. RAM considerations
6.3. Streaming-to-Memory (S2M) Variant Design x
6.3.1. Streaming Enablement for Intel® FPGA AI Suite 6.3.2. Nios® V Subsystem 6.3.3. Streaming System Operation 6.3.4. Resolving Input Rate Mismatches Between the Intel® FPGA AI Suite IP and the Streaming Input 6.3.5. The Layout Transform IP as an Application-Specific Block
6.3.3. Streaming System Operation x
6.3.3.1. Streaming System Buffer Management 6.3.3.2. Streaming System Inference Job Management
6.3.5. The Layout Transform IP as an Application-Specific Block x
6.3.5.1. Layout Transform Considerations 6.3.5.2. Layout Transform IP Register Map 6.3.5.3. Layout Transform Configuration Options
6.4. Top Level x
6.4.1. Clock Domains
6.5. The SoC Design Example Platform Designer System x
6.5.1. The dla_0 Platform Designer Layer (dla.qsys) 6.5.2. The hps_0 Platform Designer Layer (hps.qys)
7. Intel® FPGA AI Suite Soc Design Example Software Components x
7.1. Yocto Build and Runtime Linux Environment 7.2. Intel® FPGA AI Suite Runtime Plugin 7.3. Runtime Interaction with the MMD Layer 7.4. MMD Layer Hardware Interaction Library
7.1. Yocto Build and Runtime Linux Environment x
7.1.1. Yocto Recipe: recipes-core/images/coredla-image.bb 7.1.2. Yocto Recipe: recipes-bsp/u-boot/u-boot-socfpga_%.bbapend 7.1.3. Yocto Recipe: recipes-drivers/msgdma-userio/msgdma-userio.bb 7.1.4. Yocto Recipe: recipes-drivers/uio-devices/uio-devices.bb 7.1.5. Yocto Recipe: recipes-kernel/linux/linux-socfpga-lts_5.15.bbappend 7.1.6. Yocto Recipe: wic
7.4. MMD Layer Hardware Interaction Library x
7.4.1. MMD Layer Hardware Interaction Library Class mmd_device 7.4.2. MMD Layer Hardware Interaction Library Class uio_device 7.4.3. MMD Layer Hardware Interaction Library Class dma_device
8. Streaming-to-Memory (S2M) Streaming Demonstration x
8.1. Nios® Subsystem 8.2. Building the Stream Controller Module 8.3. Building the Streaming Demonstration Applications 8.4. Running the Streaming Demonstration
8.1. Nios® Subsystem x
8.1.1. Stream Controller Communication Protocol 8.1.2. Buffer Flow in Streaming Mode using Nios® V Software Scheduler
8.1.2. Buffer Flow in Streaming Mode using Nios® V Software Scheduler x
8.1.2.1. Review of M2M mode 8.1.2.2. External Streaming Mode Buffer Flow 8.1.2.3. Nios® V Stream Controller State Machine Buffer Flow
8.4. Running the Streaming Demonstration x
8.4.1. The streaming_inference_app Application 8.4.2. The image_streaming_app Application
1. Intel® FPGA AI Suite SoC Design Example User Guide
2. About the SoC Design Example
3. Intel® FPGA AI Suite SoC Design Example Quick Start Tutorial
4. Intel® FPGA AI Suite SoC Design Example Run Process
5. Intel® FPGA AI Suite SoC Design Example Build Process
6. Intel® FPGA AI Suite SoC Design Example Intel® Quartus® Prime System Architecture
7. Intel® FPGA AI Suite Soc Design Example Software Components
8. Streaming-to-Memory (S2M) Streaming Demonstration
A. Intel® FPGA AI Suite SoC Design Example User Guide Archives
B. Intel® FPGA AI Suite SoC Design Example User Guide Document Revision History

3.7.1. Running the M2M Mode Demonstration Application

The M2M dataflow model uses the dla_benchmark demonstration application. The S2M bitstream supports both the M2M dataflow model and the S2M dataflow model.

You must know the host name of the Intel® Arria® 10 SX SoC FPGA Development Kit. If you do not know the development kit host name, go back to Determining the Intel Arria 10 SX SoC FPGA Development Kit IP Address before continuing here.

To run inference on the Intel® Arria® 10 SX SoC FPGA Development Kit:
  1. Open an SSH connection to the Intel® Arria® 10 SX SoC FPGA Development Kit:
    1. Start a new terminal session
    2. Run the following command:
      build-host:$ ssh <devkit_hostname>

      Where <devkit_hostname> is the host name you determined in Determining the Intel Arria 10 SX SoC FPGA Development Kit IP Address.

      Continuing the example from Determining the Intel Arria 10 SX SoC FPGA Development Kit IP Address, the following command would open an SSH connection: 
      build-host:$ ssh arria10-62747948036a.local
  2. In the SSH terminal, run the following commands: 
    export compiled_model=~/resnet-50-tf/RN50_Performance_b1.bin
export imgdir=~/resnet-50-tf/sample_images
export archfile=~/resnet-50-tf/A10_Performance.arch
cd ~/app
export COREDLA_ROOT=/home/root/app
./dla_benchmark \
   -b=1 \
   -cm $compiled_model \
   -d=HETERO:FPGA,CPU \
   -i $imgdir \
   -niter=5 \
   -plugins_xml_file ./plugins.xml \
   -arch_file $archfile \
   -api=async \
   -groundtruth_loc $imgdir/TF_ground_truth.txt \
   -perf_est \
   -nireq=4 \
   -bgr
The dla_benchmark command generates output similar to the following example output for each step: 
[Step 11/12] Dumping statistics report
count:             8 iterations
system duration:   174.3530 ms
IP duration:       112.1184 ms
latency:           79.9449 ms
system throughput: 45.8839 FPS
number of hardware instances: 1
number of network instances: 1
IP throughput per instance: 71.3531 FPS
IP throughput per fmax per instance: 0.3568 FPS/MHz
IP clock frequency: 200.0000 MHz
[Step 12/12] Dumping the output values
[ INFO ] Dumping result of Graph_0 to result.txt and result_tensor_boundaries.txt
Level Two Title