What Is an Interconnect? How Chips and Computing Systems Exchange Data.

What Is an Interconnect?

An interconnect is a communication pathway that transfers data between components of a computing system.

Interconnects connect processors, memory, accelerators, storage devices, and sometimes entire servers.

They are important in AI computing because powerful processors need a continuous supply of information to perform their calculations efficiently.

For example, a server containing multiple GPUs may use high-speed interconnect technology to exchange model-related data between them.

Key Takeaways

• Interconnects provide communication pathways between computing components.
• Their performance depends on bandwidth, latency, topology, and communication overhead.
• An inefficient interconnect can limit AI system performance even when the processors themselves are extremely powerful.

How Does an Interconnect Work?

Imagine a computer containing a CPU, GPU, and system memory.

The components need to exchange instructions and data.

A communication interface carries information between them according to defined electrical and software protocols.

For example, PCI Express is widely used to connect GPUs, storage devices, and other components to computing systems.

Advanced AI servers may also use specialized GPU-to-GPU connections.

These interconnects help computing devices exchange information without relying exclusively on slower or less suitable communication pathways.

What Are Common Interconnect Technologies?

PCI Express (PCIe): Widely used for communication between computing devices and peripheral hardware.

NVLink: NVIDIA technology designed for high-speed communication between compatible processors and accelerators.

Compute Express Link (CXL): Supports communication and memory-related capabilities between compatible devices.

InfiniBand: Connects computing systems in high-performance clusters, particularly where efficient network communication is important.

These technologies serve different purposes and are not direct substitutes in every application.

Interconnect Bandwidth vs. Latency

Bandwidth measures how much information can be transferred per unit of time.

Latency measures how long it takes information to travel through a communication path or complete a defined exchange.

A high-bandwidth connection can move large volumes of information efficiently.

A low-latency connection can respond quickly to individual communication requests.

Both characteristics matter, but their relative importance depends on the workload.

For example, transferring large model tensors may place substantial demands on bandwidth, while exchanging small synchronization messages may be sensitive to latency.

Why Do Interconnects Matter for AI?

Large AI models may be distributed across multiple GPUs.

During training, those GPUs often need to exchange information.

If communication is slow, some processors may spend time waiting instead of calculating.

Efficient interconnects help reduce these bottlenecks.

Interconnect performance also matters inside smaller robotics computers, where cameras, processors, memory, and accelerators share limited communication resources.

Frequently Asked Questions

Is an interconnect the same as a computer network?

Not necessarily. The term can describe connections inside a chip, between devices in one computer, or across multiple computers.

Does a faster interconnect make every AI model faster?

No. It helps most when communication is a significant performance bottleneck.

The Bottom Line

Interconnects determine how effectively computing components exchange information. As AI systems become more complex, communication performance can be just as important as processor performance.