Accelerate Machine Learning with NXP i.MX 8M Plus and NPU-powered Gateworks Single Board Computers

Gateworks Venice single board computers (SBCs) include variations powered by the 恩智浦半导体 i.MX 8M Plus processor with a built-in Neural Processing Unit (NPU). This cutting-edge addition significantly enhances the machine learning capabilities of Gateworks SBCs, providing up to 2.25 TOPS (Tera Operations Per Second) of processing power for industrial IoT applications.

The NPU’s performance is a game-changer for tasks such as image classification. For instance, the NPU can complete image classification in just 3.2 milliseconds, a dramatic improvement over the 170.5 milliseconds required by a standard CPU. This 98% increase in speed enables the NPU to process 53 frames for every frame handled by the CPU, making it ideal for real-time data processing and analysis in demanding industrial environments.

Getting Started: NPU Setup and Integration

To leverage the power of the NPU, users should begin with the NXP Board Support Package (BSP) image, which includes essential libraries and kernel support for NPU interfacing.

The initial setup involves:

1. Downloading Images: Obtain the Gateworks Venice Rescue Image and the NXP BSP evaluation kit image.
2. Preparing the Device: Update the device trees (DTBs) as needed.
3. Flashing the Board: Flash the images onto the board’s eMMC.

For detailed instructions, refer to the Gateworks Support Wiki here.

Real-World Applications: Smart Factories and Predictive Maintenance

The NPU’s capabilities extend to a range of industrial applications. One practical example is image identification and classification. This is a critical function in many IoT applications such as quality control, surveillance, and automation. Additionally, integration with programs like TensorFlow Lite allows developers to run machine learning models directly on the hardware, optimizing both performance and efficiency.

In smart factories, the NPU can be employed for predictive maintenance by analyzing data from sensors and cameras in real-time. It monitors parameters like vibrations, temperature, and sound to detect early signs of equipment wear or failure. By training machine learning models to identify patterns associated with specific issues, such as bearing degradation or motor misalignment, the NPU enables proactive maintenance. This capability minimizes downtime and reduces energy consumption to extend the equipment’s lifespan. NPUs can drive cost savings and operational improvements in a smart factory environment.

Future-Proofing Industrial IoT: Advanced Automation and Anomaly Detection

The i.MX 8M Plus processor provides a robust platform for developing advanced automation and anomaly detection systems. Its real-time data processing capabilities ensure Gateworks SBCs remain versatile, reliable and ready to meet the demands of industrial IoT. The integration of the NPU with Gateworks SBCs supports sophisticated machine learning tasks, preparing users for a future where intelligent automation and real-time analysis are crucial for success.

Gateworks Single Board Computers with NXP’s i.MX 8M Plus & NPU

• Venice GW7100-20
• Venice GW7101-21
• Venice GW7200-21
• Venice GW7201-21
• Venice GW7300-20
• Venice GW7301-21
• Venice GW7400
• Venice GW7401
• Venice GW7500-21

The combination of the NXP i.MX 8M Plus processor and Gateworks Corporation SBCs offer a powerful foundation for industrial IoT applications. This advanced technology not only accelerates processing speeds but also supports advanced machine learning tasks, ensuring users are well-equipped for the evolving landscape of real-time data analysis and intelligent automation.

For detailed instructions, refer to the Gateworks Support Wiki here.