Intel® FPGA AI Suite: Getting Started Guide

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ID 768970
Date 4/05/2023
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Document Table of Contents
Document Table of Contents x
1. Intel® FPGA AI Suite Getting Started Guide 2. About the Intel® FPGA AI Suite 3. Installing the Intel® FPGA AI Suite 4. Installing the Intel® FPGA AI Suite PCIe-Based Design Example Prerequisites 5. Installing the Intel FPGA AI Suite Compiler and IP Generation Tools 6. Intel® FPGA AI Suite Quick Start Tutorial A. Installation Notes for Other Operating Systems B. Intel® FPGA AI Suite Getting Started Guide Archives C. Intel® FPGA AI Suite Getting Started Guide Document Revision History
3. Installing the Intel® FPGA AI Suite x
3.1. Intel® FPGA AI Suite Directory Structure
4. Installing the Intel® FPGA AI Suite PCIe-Based Design Example Prerequisites x
4.1. PCIe-based Design Example Hardware Prerequisites 4.2. PCIe-based Design Example Operating System Prerequisites 4.3. PCIe-based Design Example Software Prerequisites
4.3. PCIe-based Design Example Software Prerequisites x
4.3.1. Additional Software Prerequisites for the PCIe-based Design Example for Intel Agilex® 7 Devices 4.3.2. Additional Software Prerequisites for the PCIe-Based Design Example for Intel® Arria® 10 Devices
5. Installing the Intel FPGA AI Suite Compiler and IP Generation Tools x
5.1. Supported FPGA Families 5.2. Operating System Prerequisites 5.3. Software Prerequisites 5.4. Installing the Intel® FPGA AI Suite Using System Package Management Tools 5.5. Installing the Intel® FPGA AI Suite Into an Alternative Location
5.3. Software Prerequisites x
5.3.1. OpenVINO™ Toolkit 5.3.2. Intel® Quartus® Prime Pro Edition Software
6. Intel® FPGA AI Suite Quick Start Tutorial x
6.1. Creating a Working Directory 6.2. Preparing OpenVINO™ Model Zoo and Model Optimizer 6.3. Preparing a Model 6.4. Running the Graph Compiler 6.5. Preparing an Image Set 6.6. Programming the FPGA Device 6.7. Performing Inference on the PCIe-Based Example Design 6.8. Building an FPGA Bitstream for the PCIe Example Design 6.9. Building the Example FPGA Bitstreams 6.10. Preparing a ResNet50 v1 Model 6.11. Performing Inference on the Inflated 3D (I3D) Graph 6.12. Performing Inference on YOLOv3 and Calculating Accuracy Metrics
6.12. Performing Inference on YOLOv3 and Calculating Accuracy Metrics x
6.12.1. Preparing a YOLOv3 Model 6.12.2. Preparing a COCO Validation Dataset and Annotations 6.12.3. Inference on YOLOv3 and Calculating Accuracy Scores
A. Installation Notes for Other Operating Systems x
A.1. CentOS* 7 Installation Notes
1. Intel® FPGA AI Suite Getting Started Guide
2. About the Intel® FPGA AI Suite
3. Installing the Intel® FPGA AI Suite
4. Installing the Intel® FPGA AI Suite PCIe-Based Design Example Prerequisites
5. Installing the Intel FPGA AI Suite Compiler and IP Generation Tools
6. Intel® FPGA AI Suite Quick Start Tutorial
A. Installation Notes for Other Operating Systems
B. Intel® FPGA AI Suite Getting Started Guide Archives
C. Intel® FPGA AI Suite Getting Started Guide Document Revision History

6.4. Running the Graph Compiler

The Intel® FPGA AI Suite compiler (dla_compiler tool) can estimate the performance of a graph and IP architecture combination. The tool can also produce a compiled network that the runtime uses in AOT (ahead-of-time) mode to control inference on the IP.

The following commands generate an AOT file for Intel® Arria® 10 devices: 
cd $COREDLA_WORK/demo/models/public/resnet-50-tf/FP32
dla_compiler \
	--march $COREDLA_ROOT/example_architectures/A10_Performance.arch \
	--network-file ./resnet-50-tf.xml \
	--foutput-format=open_vino_hetero \
	--o $COREDLA_WORK/demo/RN50_Performance_b1.bin \
	--batch-size=1 \
	--fanalyze-performance
The following commands generate an AOT file for Intel Agilex® 7 devices: 
cd $COREDLA_WORK/demo/models/public/resnet-50-tf/FP32
dla_compiler \
	--march $COREDLA_ROOT/example_architectures/AGX7_Performance.arch \
	--network-file ./resnet-50-tf.xml \
	--foutput-format=open_vino_hetero \
	--o $COREDLA_WORK/demo/RN50_Performance_b1.bin \
	--batch-size=1 \
	--fanalyze-performance
These command specify the following input files:
  • The .arch file specifies the configuration of the IP architecture (configuration parameters such as large, small, and which activations to use).
  • The .xml file (along with the .bin) describes the network.
  • The .bin file stores certain parameters along with the model weights.
The Intel® FPGA AI Suite compiler uses these files to analyze the performance estimate.

The output file RN50_Performance_b1.bin is the compiled network and contains the instructions and graph weights necessary to control the Intel® FPGA AI Suite IP on the FPGA device. This output file is specific to the .arch file and the graph .xml file.

The compiler dot graph shows which layers run on the FPGA and which layers run on the CPU. Using the Graphviz package, the dot file format can be converted into an SVG graphics file named ResNet-50.svg that shows each layer. You can view SVG graphics in most web browsers. Use the following command to convert the dot graph file into an SVG file: 
dot -Tsvg hetero_subgraphs_resnet-50-tf.dot -o ResNet-50.svg
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