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1. FPGA AI Suite PCIe-based Design Example User Guide
2. About the PCIe* -based Design Example
3. Getting Started with the FPGA AI Suite PCIe* -based Design Example
4. Building the FPGA AI Suite Runtime
5. Running the Design Example Demonstration Applications
6. Design Example Components
7. Design Example System Architecture for the Agilex™ 7 FPGA
A. FPGA AI Suite PCIe-based Design Example User Guide Archives
B. FPGA AI Suite PCIe-based Design Example User Guide Document Revision History
5.1. Exporting Trained Graphs from Source Frameworks
5.2. Compiling Exported Graphs Through the FPGA AI Suite
5.3. Compiling the PCIe* -based Example Design
5.4. Programming the FPGA Device ( Agilex™ 7)
5.5. Performing Accelerated Inference with the dla_benchmark Application
5.6. Running the Ported OpenVINO™ Demonstration Applications
7.1. System Overview
The system consists of the following components connected to a host system via a PCIe* interface as shown in the following figure.
- A board with the FPGA device
- On-board DDR memory
The FPGA image consists of the FPGA AI Suite IP and an additional logic that connects it to a PCIe* interface and DDR. The host can read and write to the DDR memory through the PCIe* port. In addition, the host can communicate and control the FPGA AI Suite instances through the PCIe* connection which is also connected the direct memory access (DMA) CSR port of FPGA AI Suite instances.
The FPGA AI Suite IP accelerates neural network inference on batches of images. The process of executing a batch follows these steps:
- The host writes a batch of images, weights, and configuration data to DDR where weights can be reused between batches.
- The host writes to the FPGA AI Suite CSR to start execution.
- FPGA AI Suite computes the results of the batch and stores them in DDR.
- Once the computation is complete, FPGA AI Suite raises an interrupt to the host.
- The host reads back the results from DDR.
Figure 2. FPGA AI Suite Example Design System Overview