VCS3: Revolutionizing AI Inference on the Edge

The VCS3 single-board computer is an ultra-compact yet powerful processing solution designed to deliver exceptional performance in a micro-sized package. Built around the AMD Zynq UltraScale+ MPSoC, this board integrates ARM CPUs and FPGA fabric, enabling powerful computing capabilities in a footprint as small as 30mm x 50mm. With its impressive hardware capabilities, the VCS3 is an ideal platform for AI inference on the edge, offering low-latency performance that surpasses traditional GPU solutions in compact embedded applications.

Compact Powerhouse for AI at the Edge

The VCS3’s compact size makes it perfect for integration into devices where space is limited but computational power is essential. This makes the VCS3 especially well-suited for autonomous systems, industrial automation, precision robotics, and advanced imaging solutions.

With four MIPI camera interfaces, the VCS3 excels in vision-based AI systems. It connects seamlessly to MIPI sensors, enabling direct image acquisition for real-time processing. This makes it an ideal platform for edge AI inference in surveillance, smart traffic management, or automated inspection systems.

Xilinx AI Toolset Support

The VCS3 is backed by the powerful Xilinx AI toolset, allowing developers to seamlessly convert AI models for deployment on the VCS3. Leveraging the AMD Xilinx ecosystem, developers can utilize tools such as:

• Vitis AI: A comprehensive development platform simplifying model deployment on FPGA-accelerated platforms like the VCS3.
• Vivado Design Suite: Provides a complete FPGA design environment for developing customized hardware acceleration solutions.
• PetaLinux: A tailored embedded Linux distribution that allows developers to build efficient Linux systems for the VCS3’s ARM cores.
• Bare Metal Development Tools: Enables fast, lightweight system designs without an operating system, delivering maximum performance for time-critical applications.

By using these tools, developers can convert AI models created in frameworks like TensorFlow, PyTorch, or ONNX to run efficiently on the VCS3’s FPGA logic. This ensures that edge inference workloads are executed with low and predictable latency, a crucial requirement for real-time decision-making applications.

Why FPGA-Based AI Inference?

FPGA-based inference, like that on the VCS3, offers significant advantages over traditional GPU-based systems:

• Deterministic Latency: FPGA logic paths deliver predictable response times, which is essential for mission-critical AI tasks.
• Power Efficiency: The VCS3 consumes significantly less power than comparable GPU systems while maintaining high performance.
• Flexible Hardware Acceleration: Developers can tailor the FPGA fabric to their specific AI model’s structure, maximizing throughput and efficiency.

VCS3 Development Kit

To support development efforts, the VCS3 Development Kit (VCS3-DK) provides all the essential components to get started quickly. The kit includes:

• VCS3 Module
• AC/DC Power Supply (12V)
• PicoATX PSU for regulated voltage output
• ATX Breakout Board with multiple voltage options (3.3V, 5V, 12V, adjustable voltage)
• 3D Printed Desktop Holder with Integrated Cooling Fan
• Lynsyn Lite Power Measurement and JTAG Interface Module
• 9-Way and 5-Way Expansion Cables for GPIO, CAN Bus, and UART
• Main Power and UART-0 Cable
• JTAG Cable for FPGA Programming and Debugging
• UART to USB Dongle for PC Communication

Getting Started with VCS3 Development

The VCS3 is designed for fast and efficient development, with resources and guides available to streamline the process.

1. Hardware Setup: Connect the power supply, fan unit, UART cables, and JTAG interface according to the provided instructions.
2. Software Setup: Install Vivado and Vitis AI for FPGA programming and model deployment. For JTAG communication and power measurement, the Lynsyn Lite software is simple to install on both Windows and Linux.
3. AI Model Deployment: Using the Xilinx AI toolset, developers can convert trained AI models for optimal execution on the VCS3 platform.
4. Power Measurement and Optimization: With Lynsyn Lite, developers can accurately monitor power consumption to ensure optimal efficiency and performance.

Applications of the VCS3

The powerful combination of FPGA acceleration, ARM CPUs, and MIPI connectivity enables the VCS3 to excel in applications such as:

• Autonomous Vehicles for real-time sensor fusion and AI decision-making.
• Industrial Automation for precision control and intelligent machine vision.
• Medical Imaging Systems where efficient image processing is critical.
• Surveillance and Security with AI-driven anomaly detection and recognition.

Final Thoughts

The VCS3 offers a compelling solution for developers looking to build AI-driven systems at the edge. By combining powerful FPGA processing, seamless MIPI sensor integration, and the robust Xilinx AI toolset, the VCS3 empowers developers to achieve real-time inference with low power consumption and predictable latency. With its compact form factor and powerful development kit, the VCS3 is poised to transform edge computing applications.