Why Ethernet vs InfiniBand Matters for AI Infrastructure?

Ethernet vs InfiniBand for AI Infrastructure

AI infrastructure supports rapid data processing unlike we've seen before. When building AI networks, organizations require massive amounts of compute power that is high performance, low latency, and provides reliable data transmission. This is why they typically choose between either InfiniBand or Ethernet networks, based on their application's requirements and the distinct advantages of each network type.

What is Ethernet?

Ethernet is a wired network specification standard designed to physically connect computer systems with protocols for the exchange of information. A main function of Ethernet is to control how the two (or more) systems exchange information. how information should be exchanged.

If multiple systems try to exchange information at the exact same time, a “data packet collision” occurs. Ethernet prevents collisions with rules that allow networked devices to talk to each other without collisions.

What is InfiniBand?

InfiniBand is an open standard network communications technology used in high-performance computing (HPC). It's architecture is a high-speed, low-latency interconnected fabric. This composition is especially beneficial in AI infrastructure. Cloud GPU providers like Voltage Park also prefer InfiniBand for data centers as it easily supports communications between tens of thousands of nodes.

InfiniBand for AI Infrastructure

InfiniBand is renowned for its high performance, ultra low latency and scalable architecture. It is typically a preferred choice in high performance computing (HPC) environments and demanding AI applications. It excels in scenarios where ultra low latency, high bandwidth, and reliable data transmission are essential. This includes high frequency trading, high performance computing, and large-scale AI clusters.

Standout feature

Remote Direct Memory Access (RDMA) allows devices to exchange information directly between memory, bypassing the CPU and reducing latency to a minimum. This offers high throughput with minimal latency. Both are critical for AI workloads requiring rapid data processing and reliable data transmission.

Ethernet for AI Infrastructure

Ethernet is widely used in local area networks (LANs) as a cost-effective solution for AI infrastructure. It is a highly scalable option for organizations prioritizing flexibility and the ability to support larger networks or cloud-based AI environments.

Ethernet technology has evolved to support higher bandwidths and improved network performance, but can experience higher latency and packet loss compared to InfiniBand.

Standout feature

To address latency challenges, innovations such as converged Ethernet and packet spraying help reduce lag and improve data integrity for scalable AI networking.

The choice between InfiniBand and Ethernet networks for AI infrastructure comes down to balancing performance, scalability, and cost effectiveness.

By understanding the strengths and limitations of each technology, organizations can design AI networks that deliver the rapid data processing, reliability, and network performance required for today’s most demanding artificial intelligence workloads.

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