AI Development Potential with the Agilex™ 5 System on Module

Artificial Intelligence (AI) is revolutionizing various industries by providing transformative solutions that significantly enhance efficiency, accuracy, and the ability to make informed decisions. In this landscape, the concept of Edge AI—processing AI algorithms on devices located at the edge of a network—has emerged as a game-changing approach. It allows for real-time data processing, reduced latency, improved data privacy, and autonomy in decision-making, especially critical in sectors like healthcare, robotics, and industrial automation.

iWave, a pioneering force in embedded systems engineering, is at the forefront of this revolution, offering embedded platforms designed to push the boundaries of AI at the edge. These platforms are specifically tailored for applications requiring high-performance computing and sophisticated AI/ML capabilities, such as media processing, robotics, and visual computing.

Introducing iW-RainboW-G58M: The Next Generation of AI-Infused FPGAs

In a significant advancement for the embedded systems market, iWave is thrilled to introduce the iW-RainboW-G58M System on Module (SoM) (Figure 1), powered by the Intel Agilex™ 5 FPGA. This is the first FPGA to feature AI capabilities integrated directly into its fabric, marking a new era in FPGA technology. The iW-RainboW-G58M is meticulously engineered for applications demanding high-performance, low-latency processing, and custom logic implementation with embedded AI/ML support, making it an ideal choice for industries such as medical imaging, robotics, and industrial automation.

Figure 1: The iWave iW-RainboW-G58M SoM, powered by the Intel Agilex 5 FPGA which is the first FPGA to feature directly integrated AI capabilities. (Image source: iWave)

The iW-RainboW-G58M SoM is compact, measuring just 60 mm x 70 mm, yet it is packed with powerful features. It supports the Intel Agilex™ 5 FPGA and SoC E-Series family in the B32A package, available in two distinct device variants to cater to a range of application needs:

• Group A: A5E 065A/052A/043A/028A/013A SoC FPGA – These variants offer higher performance and are suitable for applications requiring more complex processing capabilities.
• Group B: A5E 065B/052B/043B/028B/013B/008B SoC FPGA – These variants provide cost-effective solutions for less demanding tasks, ensuring flexibility in design and implementation.

The combination of these options allows developers to select the most appropriate FPGA variant for their specific application, balancing performance, power consumption, and cost.

Harnessing the full potential of Intel Agilex™ 5 FPGAs for Edge AI

Intel’s Agilex™ 5 FPGAs and SoCs represent a significant leap forward in FPGA technology, especially in the context of AI and machine learning applications at the edge. The Agilex™ 5 series builds on Intel’s legacy of AI-optimized FPGAs, introducing the industry’s first AI tensor block in a mid-range FPGA. This block is specifically designed to accelerate AI workloads, making these FPGAs a perfect fit for edge AI applications where real-time processing and decision-making are critical.

A key feature of the Agilex™ 5 FPGA is its asymmetric applications processor system, which includes dual Arm Cortex-A76 cores and dual Cortex-A55 cores. This configuration allows the FPGA to deliver exceptional processing power while optimizing power efficiency, a crucial factor in edge computing environments where power consumption must be minimized without compromising performance.

The Agilex™ 5 FPGA also includes enhanced Digital Signal Processing (DSP) capabilities, integrated with an AI tensor block. This combination allows the FPGA to handle complex AI tasks such as deep learning inference, image processing, and predictive analytics with greater efficiency and accuracy. Moreover, the FPGA’s advanced connectivity features, including high-speed GTS transceivers that support data rates up to 28.1 Gbps, PCI Express* (PCIe*) 4.0 × 8, and outputs for DisplayPort and HDMI, make it a versatile solution for a wide range of applications.

Comprehensive AI/ML software ecosystem: accelerating development

The iW-RainboW-G58M SoM is complemented by a comprehensive software ecosystem that significantly accelerates AI and machine learning development. Central to this ecosystem is the support for popular AI frameworks such as TensorFlow and PyTorch, ensuring that developers can leverage these familiar platforms to create sophisticated AI models without steep learning curves.

A critical component of this ecosystem is the OpenVINO toolkit. This open-source toolkit is designed to optimize deep learning models for inference on a variety of hardware architectures, including CPUs, GPUs, and FPGAs. By using the OpenVINO toolkit, developers can ensure that their AI models are not only optimized for performance but are also highly portable across different hardware platforms, allowing for greater flexibility in deployment.

Additionally, the Intel FPGA AI Suite plays a pivotal role in simplifying the development process. This suite is designed with ease of use in mind, enabling FPGA designers, machine learning engineers, and software developers to create AI platforms that are optimized for FPGA architectures. By integrating with industry-standard tools such as TensorFlow, PyTorch, and the OpenVINO toolkit, the Intel FPGA AI Suite allows developers to speed up the development process while maintaining a high degree of reliability and performance in their AI solutions.

The suite also integrates seamlessly with the Intel Quartus Prime FPGA design software, a powerful tool that supports the design, analysis, and optimization of FPGA-based systems. This integration ensures that developers have access to a robust and proven workflow, reducing time to market and enhancing the overall reliability of their AI applications.

Cloud AI vs. Edge AI: a comparative analysis

As AI continues to evolve, the distinction between Cloud AI and Edge AI becomes increasingly important. Cloud AI, which relies on the vast computational resources of remote data centers, offers high scalability and the ability to process large volumes of data. However, this approach often comes with higher latency and potential security concerns due to the need for data transmission over the internet.

On the other hand, Edge AI offers significant advantages in scenarios where real-time processing, low latency, and enhanced data privacy are critical. By processing data locally on the device, Edge AI eliminates the need for constant communication with the cloud, reducing latency and improving the responsiveness of AI systems. This is particularly important in applications such as autonomous vehicles, industrial automation, and healthcare, where delays in decision-making can have serious consequences.

Moreover, Edge AI contributes to data privacy by keeping sensitive information on the local device, reducing the risk of data breaches associated with cloud-based processing. The hybrid approach, where edge devices perform initial data processing before transmitting it to the cloud for more complex analysis, is becoming increasingly popular. This method combines the strengths of both Edge AI and Cloud AI, allowing for efficient resource utilization, enhanced security, and improved system performance.

Ensuring longevity and comprehensive support: iWave’s commitment to customers

One of iWave’s key commitments is to ensure the long-term availability of its products. The company’s product longevity program guarantees that its System on Modules (SoMs) are available for extended periods, often exceeding 10 years. This is especially important for industries like medical devices, aerospace, and industrial automation, where product lifecycles are typically long and consistent component availability is critical.

In addition to longevity, iWave provides extensive technical support throughout the product development process. This support includes ODM (Original Design Manufacturer) services, such as carrier card design, thermal simulation, and system-level design, allowing customers to focus on their core competencies while iWave handles the complex aspects of hardware design and integration.

iWave’s commitment to customer success is further demonstrated by the provision of comprehensive evaluation kits for its SoMs. These kits come with complete user documentation, software drivers, and a board support package, enabling customers to rapidly evaluate and prototype their designs. By offering these resources, iWave helps customers reduce development time and bring their products to market faster.

Summary

iWave’s iW-RainboW-G58M SoM, with the Intel Agilex 5 FPGA that features integrated AI capabilities, is carefully engineered for high-performance, low-latency processing, and custom logic implementation with embedded AI/ML support applications. This makes it a good choice for industries such as medical imaging, robotics, and industrial automation.