Intel® FPGA AI Suite: PCIe-based Design Example User Guide

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ID 768977
Date 9/06/2023
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Document Table of Contents
Document Table of Contents x
1. Intel® FPGA AI Suite PCIe-based Design Example User Guide 2. About the PCIe* -based Design Example 3. Getting Started with the Intel® FPGA AI Suite PCIe* -based Design Example 4. Building the Intel® FPGA AI Suite Runtime 5. Running the Design Example Demonstration Applications 6. Design Example Components 7. Design Example System Architecture for the Intel PAC with Intel® Arria® 10 GX FPGA A. Intel® FPGA AI Suite PCIe-based Design Example User Guide Archives B. Intel® FPGA AI Suite PCIe-based Design Example User Guide Document Revision History
4. Building the Intel® FPGA AI Suite Runtime x
4.1. CMake Targets 4.2. Build Options
5. Running the Design Example Demonstration Applications x
5.1. Exporting Trained Graphs from Source Frameworks 5.2. Compiling Exported Graphs Through the Intel FPGA AI Suite 5.3. Compiling the PCIe* -based Example Design 5.4. Programming the FPGA Device ( Intel® Arria® 10) 5.5. Programming the FPGA Device ( Intel Agilex® 7) 5.6. Performing Accelerated Inference with the dla_benchmark Application 5.7. Running the Ported OpenVINO™ Demonstration Applications
5.6. Performing Accelerated Inference with the dla_benchmark Application x
5.6.1. Inference on Image Classification Graphs 5.6.2. Inference on Object Detection Graphs 5.6.3. Additional dla_benchmark Options
5.6.2. Inference on Object Detection Graphs x
5.6.2.1. The mAP and COCO AP Metrics 5.6.2.2. Specifying Ground Truth 5.6.2.3. Example of Inference on Object Detection Graphs
5.7. Running the Ported OpenVINO™ Demonstration Applications x
5.7.1. Example Running the Object Detection Demonstration Application
6. Design Example Components x
6.1. Build Script 6.2. Example Architecture Bitstream Files 6.3. Software Components 6.4. Software Interface to the BSP
6.1. Build Script x
6.1.1. Build Script Options 6.1.2. Script Flow
6.3. Software Components x
6.3.1. OpenVINO™ FPGA Runtime Plugin 6.3.2. Intel FPGA AI Suite Runtime 6.3.3. BSP Driver
7. Design Example System Architecture for the Intel PAC with Intel® Arria® 10 GX FPGA x
7.1. System Overview 7.2. Hardware
7.2. Hardware x
7.2.1. PLL Adjustment
1. Intel® FPGA AI Suite PCIe-based Design Example User Guide
2. About the PCIe* -based Design Example
3. Getting Started with the Intel® FPGA AI Suite PCIe* -based Design Example
4. Building the Intel® FPGA AI Suite Runtime
5. Running the Design Example Demonstration Applications
6. Design Example Components
7. Design Example System Architecture for the Intel PAC with Intel® Arria® 10 GX FPGA
A. Intel® FPGA AI Suite PCIe-based Design Example User Guide Archives
B. Intel® FPGA AI Suite PCIe-based Design Example User Guide Document Revision History

6.3.1. OpenVINO™ FPGA Runtime Plugin

The FPGA runtime plugin uses the OpenVINO™ Inference Engine Plugin API.

The OpenVINO™ Plugin architecture is described in the OpenVINO™ Developer Guide for Inference Engine Plugin Library.

The source files are located under runtime/plugin. The three main components of the runtime plugin are the Plugin class, the Executable Network class, and the Inference Request class. The primary responsibilities for each class are as follows:

Plugin class

  • Initializes the runtime plugin with an Intel® FPGA AI Suite Architecture File which you set as an OpenVINO™ configuration key (refer to Running the Ported OpenVINO Demonstration Applications).
  • Contains QueryNetwork function that analyzes network layers and returns a list of layers that the specified architecture supports. This function allows network execution to be distributed between FPGA and other devices and is enabled with the HETERO mode.
  • Creates an executable network instance in one of the following ways:
    • Just-in-time (JIT) flow: Compiles a network such that the compiled network is compatible with the hardware corresponding to the Intel FPGA AI Suite Architecture File, and then loads the compiled network onto the FPGA device.
    • Ahead-of-time (AOT) flow: Imports a precompiled network (exported by Intel FPGA AI Suite compiler) and loads it onto the FPGA device.

Executable Network Class

  • Represents an Intel FPGA AI Suite compiled network
  • Loads the compiled model and config data for the network onto the FPGA device that has already been programmed with an Intel FPGA AI Suite AFU/AF bitstream. For two instances of Intel FPGA AI Suite, the Executable Network class loads the network onto both instances, allowing them to perform parallel batch inference.
  • Stores input/output processing information.
  • Creates infer request instances for pipelining multiple batch execution.

Infer Request class

  • Runs a single batch inference serially.
  • Executes five stages in one inference job – input layout transformation on CPU, input transfer to DDR, Intel FPGA AI Suite FPGA execution, output transfer from DDR, output layout transformation on CPU.
  • In asynchronous mode, executes the stages on multiple threads that are shared across all inference request instances so that multiple batch jobs are pipelined, and the FPGA is always active.
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