How to connect a GPU to an FPGA?

Time: 2025-05-27 11:30:51View:

Connecting a GPU to an FPGA involves creating a high-speed communication link between the two. This is done to offload specific tasks (like pre/post-processing or streaming data) to the FPGA, while the GPU handles massively parallel computation (e.g., for AI, vision, or rendering tasks).

1. Common Connection Interfaces

You can connect a GPU to an FPGA through one of the following:

Interface	Speed	Notes
PCIe (most common)	Very high (Gbps per lane)	Both GPU and FPGA must support PCIe
AXI/AXI4 over SoC	Internal (FPGA+CPU SoCs)	Used on systems like Xilinx Zynq
NVLink	Ultra-fast	Proprietary (NVIDIA-specific, rare in FPGA setups)
Ethernet	Medium	Easier for distributed systems
USB/Serial	Slow	Useful for basic interfacing/testing only

2. Typical FPGA ↔ GPU Setup (via PCIe)

Hardware Requirements

FPGA board with PCIe support (e.g., Xilinx Kintex, Intel Stratix, etc.)
GPU installed in the same host system or attached via PCIe cable
Optionally: High-speed FMC board or interposer

High-level architecture:

less

[ Host CPU ]
     |
[ PCIe Root Complex ]
     |                 \
[ FPGA (PCIe EP)] ——— [ GPU (PCIe EP) ]

The host CPU acts as a coordinator.
FPGA and GPU are both PCIe endpoints.
FPGA can act as a DMA engine or pre/post-processor.

3. Steps to Connect via PCIe

Step 1: FPGA PCIe Core Configuration

Instantiate a PCIe IP core (e.g., Xilinx PCIe Gen3, Intel Avalon PCIe)
Configure it as an endpoint (EP) or bridge
Add DMA engines or AXI bridges if needed

Step 2: Develop a Driver or Use Host Software

Use a Linux driver to allow communication between the CPU, GPU, and FPGA
You can use OpenCL, CUDA, or custom PCIe drivers

Step 3: Data Exchange Flow

Example: FPGA pre-processes sensor data, sends it to the GPU:

FPGA receives raw data (e.g., from camera)
FPGA sends data to host memory via PCIe DMA
GPU accesses the same memory (shared buffer) using CUDA
GPU processes and outputs results

4. Software Tools

CUDA (for GPU)
Vivado / Quartus (for FPGA PCIe setup)
XDMA / QDMA drivers (Xilinx)
OpenCL for unified programming on both devices (some platforms)

Alternative: Direct FPGA ↔ GPU Memory Access

For high-performance computing systems:

Some Xilinx Alveo or Intel PAC FPGA cards support peer-to-peer (P2P) access between GPU and FPGA over PCIe
Requires GPU with BAR1 memory mapping and advanced PCIe support

Real-World Use Cases

Use Case	FPGA Role	GPU Role
AI inference	Pre-process (resize, quantize)	Run neural net
Vision	Stream/encode camera data	Run CNN model
Networking	Filter/route packets	Analyze packets (e.g. intrusion detection)

Summary

To connect a GPU to an FPGA:

Use a high-speed interface like PCIe.
Configure the FPGA with a PCIe IP core.
Set up a driver or software layer to manage data flow.
Handle memory sharing or DMA between the two.
Consider using frameworks like OpenCL if you want to target both with similar code.