FPGA AI Suite: SoC Design Example User Guide

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ID 768979
Date 3/28/2025
Public
Document Table of Contents
Document Table of Contents x
1. Publication Deprecation Notice 2. About the SoC Design Example 3. FPGA AI Suite SoC Design Example Quick Start Tutorial 4. FPGA AI Suite SoC Design Example Run Process 5. FPGA AI Suite SoC Design Example Build Process 6. FPGA AI Suite SoC Design Example Quartus® Prime System Architecture 7. FPGA AI Suite Soc Design Example Software Components 8. Streaming-to-Memory (S2M) Streaming Demonstration A. FPGA AI Suite SoC Design Example User Guide Archives B. FPGA AI Suite SoC Design Example User Guide Document Revision History
1. Publication Deprecation Notice x
1.1. FPGA AI Suite SoC Design Example User Guide
2. About the SoC Design Example x
2.1. FPGA AI Suite SoC Design Example Prerequisites
2.1. FPGA AI Suite SoC Design Example Prerequisites x
2.1.1. Agilex™ 7 FPGA I-Series Transceiver-SoC Development Kit Hardware Requirements
3. 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 SoC FPGA Development Kits for the FPGA AI Suite SoC Design Example 3.6. Adding Compiled Graphs (AOT files) to the SD Card 3.7. Verifying FPGA Device Drivers 3.8. 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 SoC FPGA Development Kits for the FPGA AI Suite SoC Design Example x
3.5.1. Preparing the Agilex™ 7 FPGA I-Series Transceiver-SoC Development Kit 3.5.2. Preparing the Arria® 10 SX SoC FPGA Development Kit (DK-SOC-10AS066S) 3.5.3. Configuring the SoC FPGA Development Kit UART Connection 3.5.4. Determining the SoC FPGA Development Kit IP Address
3.5.1. Preparing the Agilex™ 7 FPGA I-Series Transceiver-SoC Development Kit x
3.5.1.1. Confirming Agilex™ 7 FPGA I-Series Transceiver-SoC Development Kit Board Set Up 3.5.1.2. Programming the Agilex™ 7FPGA Device with the JTAG Indirect Configuration (.jic) File 3.5.1.3. Connecting the Agilex™ 7 FPGA I-Series Transceiver-SoC Development Kit to the Host Development System
3.5.2. Preparing the Arria® 10 SX SoC FPGA Development Kit (DK-SOC-10AS066S) x
3.5.2.1. Confirming Arria® 10 SX SoC FPGA Development Kit (DK-SOC-10AS066S) Board Settings 3.5.2.2. Connecting the Arria® 10 SX SoC FPGA Development Kit (DK-SOC-10AS066S) to the Host Development System
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
3.8. Running the Demonstration Applications x
3.8.1. Running the M2M Mode Demonstration Application 3.8.2. Running the S2M Mode Demonstration Application 3.8.3. Troubleshooting the Demonstration Applications
4. FPGA AI Suite SoC Design Example Run Process x
4.1. Exporting Trained Graphs from Source Frameworks 4.2. Compiling Exported Graphs Through the FPGA AI Suite
5. FPGA AI Suite SoC Design Example Build Process x
5.1. Building the Quartus® Prime Project 5.2. Building the Bootable SD Card Image (.wic)
5.1. Building the Quartus® Prime Project x
5.1.1. Quartus® Prime Build Flow 5.1.2. Build Script Options 5.1.3. Build Directory
5.1.1. 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. FPGA AI Suite SoC Design Example Quartus® Prime System Architecture x
6.1. 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 FPGA AI Suite 6.3.2. Nios® V Subsystem 6.3.3. Streaming System Operation 6.3.4. Resolving Input Rate Mismatches Between the 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. FPGA AI Suite Soc Design Example Software Components x
7.1. Yocto Build and Runtime Linux Environment 7.2. 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_%.bbappend 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_%.bbappend 7.1.6. Yocto Recipe: recipes-support/devmem2/devmem2_2.0.bb 7.1.7. 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. Publication Deprecation Notice
2. About the SoC Design Example
3. FPGA AI Suite SoC Design Example Quick Start Tutorial
4. FPGA AI Suite SoC Design Example Run Process
5. FPGA AI Suite SoC Design Example Build Process
6. FPGA AI Suite SoC Design Example Quartus® Prime System Architecture
7. FPGA AI Suite Soc Design Example Software Components
8. Streaming-to-Memory (S2M) Streaming Demonstration
A. FPGA AI Suite SoC Design Example User Guide Archives
B. FPGA AI Suite SoC Design Example User Guide Document Revision History

6. FPGA AI Suite SoC Design Example Quartus® Prime System Architecture

The FPGA AI Suite SoC design examples provide two variants for demonstrating the FPGA AI Suite operation.

All designs are Platform Designer based systems.

There is a single top-level Verilog RTL file for instantiating the Platform Designer system.

These two variants demonstrate FPGA AI Suite operations in the two most common usage scenarios. These scenarios are as follows:

  • Memory to Memory (M2M): In this variant, the following steps occur:
    1. The Arm* processor host presents input data buffers to the FPGA AI Suite that are stored in a system memory.
    2. The FPGA AI Suite IP performs an inference on these buffers.
    3. The host system collects the inference results.
    This variant demonstrates the simplest use-case of the FPGA AI Suite.
  • Streaming to Memory (S2M): This variant offers a superset of the M2M functionality. The S2M variant demonstrates sending streaming input source data into the FPGA AI Suite IP and then collecting the results. An Avalon® streaming input captures live input data, stores the data into system memory, and then automatically triggers FPGA AI Suite IP inference operations.

    You can use this variant as a starting point for larger designs that stream input data to the FPGA AI Suite IP with minimal host intervention.


Section Content
FPGA AI Suite SoC Design Example Inference Sequence Overview
Memory-to-Memory (M2M) Variant Design
Streaming-to-Memory (S2M) Variant Design
Top Level
The SoC Design Example Platform Designer System
Fabric EMIF Design Component
PLL Configuration

Level Two Title