Moving Data Between GPUs is Crucial for AI

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Use in Large-Scale AI Models

In applications like large language models (LLMs) and AI training (e.g., models with hundreds of billions or trillions of parameters), the ability to move vast amounts of data between GPUs is crucial. NVLink, particularly in conjunction with NVLink Switch, enables these large-scale models to be trained faster and with higher efficiency by ensuring that GPUs can communicate with minimal overhead.


NVIDIA NVLink and NVLink Switch are critical components in multi-GPU and multi-CPU setups, designed to overcome latency and bandwidth limitations that typically hinder communication between processors, especially in high-performance computing (HPC) and AI workloads. Here's a detailed overview:

1. What is NVLink?

NVLink is a high-speed interconnect technology developed by NVIDIA that allows multiple GPUs (and sometimes CPUs) to communicate directly with each other at much higher bandwidth and with lower latency than traditional PCIe (Peripheral Component Interconnect Express) connections. It achieves this by creating a point-to-point connection between GPUs or CPUs in a system, bypassing many of the bottlenecks of traditional buses like PCIe.

Key Features:

  • High Bandwidth: The latest generation of NVLink provides 1.8 terabytes per second (TB/s) of bidirectional bandwidth per GPU, which is substantially higher than PCIe 5.0, which maxes out around 64 GB/s.
  • Lower Latency: NVLink reduces the latency typically associated with inter-GPU or inter-CPU communication by using a direct connection, eliminating the need to send data through system memory (RAM) or the CPU for coordination.

This is particularly useful in scenarios requiring massive amounts of data transfer between GPUs, such as deep learning, neural network training, and generative AI models.

2. What is NVLink Switch?

NVLink Switch is a technology that allows multiple NVLink connections to be routed efficiently between GPUs or CPUs within a system. Essentially, it acts as a high-speed switching fabric that enables direct communication between multiple GPUs (or GPUs and CPUs), significantly improving the scalability of systems.

  • Multi-GPU Scaling: In systems with a large number of GPUs (e.g., data centers or supercomputers), NVLink Switch ensures that every GPU can talk to every other GPU with minimal latency, creating a more unified architecture. In the case of large AI models or HPC tasks, this is essential for achieving near-linear scalability.
  • High-Speed Communication Across GPUs: The NVLink Switch increases the potential number of GPUs that can communicate directly with each other, enabling up to 576 GPUs to communicate seamlessly in systems like NVIDIA's DGX SuperPOD or similar supercomputing infrastructures​(NVIDIA)​(NVIDIA Investor Relations).

3. Benefits Over PCIe:

In traditional systems, PCIe is often the limiting factor when it comes to data transfer between GPUs or between the GPU and CPU. PCIe has limited bandwidth and relatively high latency, which can become a significant bottleneck in data-intensive applications like AI model training or simulation workloads.

With NVLink:

  • Higher Bandwidth: The bidirectional throughput is much higher than PCIe, enabling faster data exchange between processors.
  • Lower Latency: NVLink minimizes latency by allowing GPUs to bypass system memory and communicate directly, improving the performance of distributed tasks where GPUs need to share large datasets quickly.

For example, in a multi-GPU setup (common in deep learning and AI), GPUs frequently need to synchronize data (weights, gradients, etc.) during training. Without NVLink, this synchronization would need to pass through CPU memory and PCIe, introducing a significant bottleneck.

Use in NVIDIA SuperPODs


The NVLink architecture is integral to NVIDIA’s DGX SuperPOD systems, which combine DGX B200 systems and Grace Blackwell Superchips to create AI supercomputing clusters. These systems are designed to scale up to exascale computing, where multi-GPU and multi-node configurations are critical for AI model training and scientific simulations​(Tom's Hardware)​(NVIDIA Investor Relations).

In summary, NVLink and NVLink Switch are essential for creating high-performance multi-GPU systems by dramatically increasing bandwidth and reducing latency, making them crucial for AI, HPC, and data center applications. These technologies help overcome traditional communication bottlenecks and enable faster, more efficient processing of complex tasks.

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