Altera Agilex 3 FPGA: Performance Test in Edge AI Scenarios

Power Efficiency: Agilex 3 vs Xilinx Versal

Agilex 3 leverages 2nd-gen HyperFlex architecture and Intel 7nm process, reducing power consumption by 38% while boosting logic performance by 1.9× vs Cyclone V. In edge AI tasks (e.g., 1080p object detection):

Power: 2.1W (vs Versal’s 2.8W)

Latency: <5ms (vs 7ms)

AI Acceleration: Integrated AI Tensor blocks deliver 2.8 TOPS INT8, 40% higher energy efficiency than Versal’s programmable logic.

Robotics Case: Multi-Sensor Fusion

In a robotic arm control system:

Agilex 3’s dual Arm Cortex-A55 processes ROS 2 algorithms while FPGA handles CNN vision (YOLOv7) and force feedback in parallel.

Result: Sensor fusion latency reduced to 8.2ms (40% faster than competitors), enabling sub-0.1mm precision at 3.5W power.

Development Tools

Quartus Prime Pro 25.1: Supports one-click AI model deployment (TensorFlow/PyTorch → FPGA) and STP streaming debugger.

FPGA AI Suite: Optimizes models (30% size reduction) and includes pre-trained libraries.

Deployment: Use SOM modules with BGA610 packaging for high I/O density designs.

Conclusion

Agilex 3 redefines edge AI with unmatched power efficiency and real-time processing, backed by 15-year lifecycle support.