How AI is changing the game for high-performance SoC designs

By Andy Nightingale, Arteris 
EDN | March 5, 2025

The need for intelligent interconnect solutions has become critical as the scale, complexity, and customizability of today’s systems-on-chip (SoC) continue to increase. Traditional network-on-chip (NoC) technologies have played a vital role in addressing connectivity and data movement challenges, but the growing intricacy of designs necessitates a more advanced approach. Especially, when high-end SoC designs are surpassing the human ability to create NoCs without smart assistance.

The key drivers for this demand can be summarized as follows:

• Application-specific requirements: Many industries and applications, such as automotive, Internet of Things (IoT), consumer electronics, artificial intelligence (AI), and machine learning (ML), require highly specialized hardware tailored to unique workloads, such as real-time processing, low latency, or energy efficiency. Off-the-shelf chips often fall short of providing the precise blend of performance, power, and cost-efficiency these applications need.
• Cost and performance optimization: Custom SoCs allow companies to integrate multiple functions into a single chip, reducing system complexity, power consumption, and overall costs. With advanced process nodes, custom SoCs can achieve higher levels of performance tailored to the application, offering a competitive edge.
• Miniaturization and integration: Devices in areas like wearables, medical implants, and IoT sensors demand miniaturized solutions. Custom SoCs consolidate functionality onto a single chip, reducing size and weight.
• Data-centric and AI workloads: AI and ML require processing architectures optimized for parallel computation and real-time inferencing. Custom SoCs can incorporate specialized processing units, like neural network accelerators or high-bandwidth memory interfaces, to handle these demanding tasks.

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