Network-on-Chip (NoC) Design Architectural Trade-offs

When Interconnect Shapes the System

Modern SoCs are no longer defined solely by their compute capabilities. Instead, they are shaped by the complexity of integrating diverse processing elements and ensuring efficient communication between them. The rise of heterogeneous architectures, combined with the increasing adoption of chiplet-based and multi-die systems, has significantly expanded the role of interconnect design.

As these systems scale, the interconnect is no longer a secondary consideration—it becomes a determining factor in overall system viability. Ensuring that data can be delivered efficiently, predictably, and at scale is now central to achieving performance and power targets.

This shift has been observed across multiple generations of SoC development, particularly among companies focused on on-chip connectivity, such as Arteris, where evolving system requirements have increasingly highlighted data movement as a system-level constraint ^[1].

Why NoC Complexity Has Increased

The growing importance of network-on-chip (NoC) design is closely tied to the demands of modern workloads, particularly in artificial intelligence (AI). AI systems require high bandwidth, low latency, and efficient data reuse across multiple compute units, placing significant pressure on interconnect infrastructure.

As AI workloads scale, SoCs integrate more heterogeneous IP blocks, including CPUs, GPUs, NPUs, and specialized accelerators. This increases both the volume and complexity of data movement. At the same time, chiplet-based designs and advanced packaging approaches such as 2.5D and 3D integration multiply the number of communication paths within a system.

These trends introduce additional challenges, including:

• Multiple clock domains and power islands 

• Increased need for isolation and security boundaries 

• Greater variability in traffic patterns 

Together, these factors make interconnect design a system-level challenge. In this context, the NoC becomes a primary enabler of AI system scalability, power efficiency, and deterministic behavior, ensuring that distributed compute resources can operate effectively ^{[2] [3]}.

Core NoC Design Trade-offs

Designing an effective NoC requires balancing several competing constraints, each of which directly impacts system performance, power, and scalability.

One key trade-off is bandwidth provisioning versus power and area efficiency. Over-provisioning bandwidth can reduce contention and improve performance, but increases area and energy consumption. Under-provisioning, on the other hand, can lead to congestion and reduced throughput.

Another critical consideration is managing contention, latency, and quality of service (QoS). In heterogeneous systems, different components may have varying latency and bandwidth requirements. Ensuring predictable performance requires mechanisms for prioritization and arbitration.

Energy-aware communication is also increasingly important. Techniques such as power gating and dynamic scaling help reduce energy consumption but must be carefully managed to avoid performance penalties ^[4].

In addition, modern NoC design must be physically aware, considering placement, routing, and timing constraints early in the design process. As technology nodes shrink and system complexity increases, physical and logical considerations are becoming more tightly coupled.

These trade-offs have been the focus of ongoing research and development across the industry, as interconnect design evolves to meet the demands of increasingly complex SoCs.

Security, Safety, and Isolation

As SoCs are deployed in safety-critical and security-sensitive applications, the role of the interconnect extends beyond performance and efficiency.

In automotive and industrial systems, compliance with standards such as ISO 26262 requires robust support for functional safety, including predictable communication and fault isolation (ISO, 2018). The interconnect plays a key role in preventing faults from propagating across system boundaries ^[5].

At the same time, increasing system complexity introduces new security challenges. The NoC, as the central communication fabric, becomes both a potential attack surface and a point of enforcement for system-level policies.

This has led to growing emphasis on hardware assurance—ensuring that system behavior is secure, predictable, and verifiable across all operating conditions. Industry efforts, including those by Cycuity, highlight the importance of validating hardware security properties across complex SoC designs.

Modern NoC architectures must therefore support isolation, monitoring, and policy enforcement at scale, enabling both safety and security requirements to be met.

Build vs. Reuse: The Economics of NoC Design

Historically, many companies developed custom interconnect solutions tailored to their specific SoC architectures. This approach was feasible when systems were less complex and workloads more predictable.

However, the economics of NoC design have changed. Rising R&D costs, long maintenance lifetimes, and the accumulation of verification debt—the increasing effort required to validate evolving systems over time—have made custom development more challenging.

The shift toward AI workloads further increases complexity. Designing interconnects that can handle high bandwidth demands, dynamic traffic patterns, and strict performance requirements adds both cost and risk ^[6].

As a result, data movement infrastructure is increasingly treated as reusable system IP rather than bespoke logic. Industry observations, including those from companies such as Arteris, indicate that this shift allows teams to manage complexity more effectively while reducing development risk ^[1].

By relying on reusable interconnect solutions, engineering teams can focus their efforts on areas of differentiation—such as algorithms, software, and system-level innovation—rather than maintaining underlying communication infrastructure.

Automation and the Future of NoC Development

The scale and complexity of modern AI-driven systems are making manual NoC design increasingly impractical. Automation is emerging as a key enabler in addressing these challenges.

AI workloads act as a forcing function, driving the need for more sophisticated design methodologies. At the same time, the industry faces a shortage of experienced NoC and system IP architects, further increasing reliance on automated approaches.

Automation is now being applied across multiple stages of development, including architecture exploration and RTL generation. These approaches enable systematic evaluation of design trade-offs and help identify optimal configurations more efficiently.

Another important trend is the convergence of physical and logical design considerations earlier in the development process. Incorporating placement, routing, and timing constraints at the architectural stage helps reduce downstream integration challenges.

The benefits of automation include improved performance and power efficiency through systematic design exploration, reduced integration risk, faster time-to-tapeout, and shorter time-to-market for end products. These approaches also enable reusable architectures that can scale across AI generations and chiplet-based systems.

NoC as Enabling Infrastructure

In modern SoCs, the most effective interconnect designs are often the least visible. When designed correctly, they enable seamless communication between components, allowing the rest of the system to operate efficiently.

Robust interconnect design enables innovation in higher-level system functions by abstracting the complexity of data movement. This has led to increased specialization in NoC design, with companies such as Arteris developing expertise across multiple markets and system architectures.

This cross-market experience, accumulated over many generations of SoC development, provides insights into design trade-offs and scalability challenges—expertise that can be difficult for individual teams to build and sustain internally.

As systems continue to grow in complexity, the role of the NoC will only become more central. Rather than being viewed as supporting infrastructure, it is increasingly recognized as a foundational element that enables performance, efficiency, and innovation across modern computing systems.

References

1. Arteris. Data Movement in SoCs: NoC Performance, Power & Scalability. [Online]. Available: http://arteris.com/learn/data-movement

2. Hennessy, J. L., & Patterson, D. A. (2019). Computer Architecture: A Quantitative Approach (6th ed.). Morgan Kaufmann.

3.  NVIDIA, “NVIDIA Hopper Architecture In-Depth,” NVIDIA, Mar. 22, 2022. [Online]. Available: https://resources.nvidia.com/en-us-hpc-ai/nvidia-hopper-architecture

4. Horowitz, M. (2014). Computing’s energy problem (and what we can do about it). IEEE ISSCC.

5. ISO 26262. (2018). Road vehicles – Functional safety. International Organization for Standardization.

6. EE Times Asia. The Data Dilemma: Cracking the Code of Data Movement for the Next Wave of Semiconductor Innovation.