HPC
InfiniBand vs Ethernet in the Data Center
December 16, 2025
8 min read
Introduction
High-speed networking has become a foundational element of modern high-performance computing (HPC) and large-scale artificial intelligence (AI) infrastructures. As compute density increases and clusters scale to thousands of GPUs, the interconnect fabric often becomes the determining factor for overall system performance. Low latency, high bandwidth, and predictable communication behavior is just as important as the compute hardware itself.
Ethernet and InfiniBand remain the two primary technologies used to build high-performance interconnects. Each has evolved significantly, such as 800G/1.6T Ethernet, and next-generation InfiniBand HDR/NDR/XDR fabrics.
We will explain each technology, highlight its latest capabilities, and evaluate which networking architecture is the best fit for your computing infrastructure.
What Is Ethernet?
Ethernet is a widely used networking protocol for connecting devices in local area networks (LANs) and data centers, valued for its scalability, mature ecosystem, and consistent upgrade roadmap. Originally built for LANs, it has evolved into a high-performance fabric supporting 100GbE, 200GbE, 400GbE, and 800GbE links, with 1.6T Ethernet now entering early deployment.
Ethernet’s versatility makes it suitable for virtualized environments, large distributed systems, and AI clusters that prioritize scale and interoperability. Technologies such as RoCEv2, advanced congestion control, and DPU/SmartNIC acceleration extend Ethernet’s ability to deliver low-latency, RDMA-capable performance across large multi-rack deployments.
When to Use Ethernet
Ethernet is the preferred choice for general-purpose, cloud, and large-scale distributed workloads where cost efficiency, broad interoperability, and operational simplicity matter most. Its mature ecosystem and compatibility with standard TCP/IP environments make it easy to integrate across diverse data centers, including hybrid and multi-cloud deployments. Modern enhancements—such as RoCEv2, advanced congestion control, and DPU/SmartNIC acceleration—further strengthen Ethernet’s suitability for high-throughput applications.
Use Ethernet when:
- Running virtualized, containerized, or cloud-native workloads
- Managing infrastructure services such as monitoring, orchestration, or job scheduling
- Prioritizing cost efficiency and scalability across many racks or sites
- Applications do not require the ultra-low latency of specialized HPC fabrics
- Ensuring seamless compatibility with hybrid cloud or multi-vendor environments
What Is InfiniBand?
InfiniBand is a high-speed, low-latency interconnect designed for HPC and large-scale AI training. Its native RDMA architecture enables direct memory communication across nodes with minimal CPU involvement, reducing latency and improving throughput for tightly coupled workloads.
InfiniBand has progressed through several bandwidth generations—FDR (56 Gb/s), EDR (100 Gb/s), HDR (200 Gb/s), and today’s NDR (400 Gb/s), as well as emerging XDR class—providing predictable performance at scale. The ecosystem around InfiniBand, including GPUDirect RDMA, SHARP in-network acceleration, OpenMPI, and HPC schedulers, further optimizes collective operations and multi-node GPU performance.
When to Use InfiniBand
InfiniBand is the preferred interconnect for environments that require ultra-low latency, high sustained bandwidth, and efficient inter-node communication. Its native RDMA implementation, advanced congestion control, and predictable performance under load make it purpose-built for tightly coupled HPC workloads and large multi-node AI training.
Use InfiniBand when:
- Running workloads across many compute nodes, such as:
- Large-scale AI/ML training
- Scientific simulations (CFD, weather, molecular dynamics, physics codes)
- Applications require extremely low latency for frequent inter-node communication
- Workloads depend on high throughput and consistent performance during long-running jobs
- Leveraging MPI-based parallel frameworks, common in HPC and simulation workloads
- Deploying systems with high-speed GPU interconnects (e.g., NVIDIA NVLinkâ„¢/NVLink Switch on NVIDIA H200 NVL, HGXâ„¢ H200, HGX B200), where low-latency networking complements fast GPU-to-GPU communication across nodes
Deploying InfiniBand and Ethernet?
In modern HPC and AI data centers, Ethernet and InfiniBand often coexist to balance cost, performance, and operational flexibility. These hybrid fabrics assign each technology to the roles that best leverage its strengths.
Hybrid Deployment Strategy
A common approach separates control and compute traffic:
- Ethernet manages the control plane, including system monitoring, job scheduling, management traffic, and data I/O. Its broad compatibility and ecosystem support make it ideal for general infrastructure functions.
- InfiniBand connects compute nodes with ultra-low-latency, high-bandwidth links, optimizing tightly coupled workloads and speeding up time-to-result for AI training and HPC applications.
Dual-NIC Server Design
Some deployments equip servers with two NICs—one for Ethernet and one for InfiniBand:
- InfiniBand NIC handles RDMA, MPI traffic, and inter-node data movement for HPC and AI workloads.
- Ethernet NIC connects to storage, orchestration services, cloud gateways, or administrative interfaces.
This design is particularly effective for:
- AI clusters using GPUDirect RDMA over InfiniBand alongside NFS/S3 storage traffic over Ethernet
- HPC clusters where MPI traffic runs on InfiniBand, while large data transfers use Ethernet
- Hybrid cloud environments where Ethernet provides external connectivity and InfiniBand supports local high-performance compute
Frequently Asked Questions About InfiniBand vs Ethernet
1. Is Ethernet fast enough for AI and HPC workloads?
Yes—for many workloads. Modern Ethernet (400G–800G) with RoCE and DPUs performs well for distributed AI and large-scale data processing, but ultra-low-latency workloads may still benefit from InfiniBand.
2. When is InfiniBand the better choice?
InfiniBand is best for tightly coupled HPC and large AI training jobs that require predictable, ultra-low latency, and high sustained bandwidth across many nodes.
3. Can Ethernet and InfiniBand be used together?
Yes. Many organizations deploy mixed fabrics, using Ethernet for management, storage, and cloud connectivity, and InfiniBand for compute-intensive inter-node traffic.
4. How does network choice impact AI training time and efficiency?
Network latency and bandwidth directly affect GPU utilization and job completion time. High-performance fabrics like InfiniBand reduce communication overhead during gradient exchange and collective operations, improving overall training efficiency at scale.
5. How do I choose the right fabric for my environment?
In many cases, a hybrid approach delivers the best balance. Ethernet is often the best fit for distributed, cloud-integrated, or cost-sensitive environments, while InfiniBand is better suited for tightly coupled HPC and large AI training clusters that demand predictable, ultra-low-latency performance.
Conclusion
Ethernet and InfiniBand each serve distinct roles in modern data centers. Selecting the right fabric depends on your workload type, scale, and budget, and many organizations adopt a hybrid approach to leverage the strengths of both technologies.
- Ethernet offers broad compatibility, scalability, and cost-efficiency, making it ideal for general-purpose, cloud, and hybrid workloads.
- InfiniBand, by contrast, provides ultra-low latency, high bandwidth, and predictable performance, making it the preferred choice for HPC, large-scale AI, and tightly coupled workloads.
| Feature | Ethernet | InfiniBand |
| Latency | Higher | Lower |
| Bandwidth | 100 GbE – 800 GbE (1.6 TbE emerging) | HDR/NDR: 200–800 Gb/s per link; XDR (800-1.6Tbps) emerging |
| CPU Overhead | Moderate to high | Very low (native RDMA) |
| RDMA Support | Yes (RoCEv2, UEC standards) | Native |
| Scalability | High (large cloud/hybrid deployments) | Very high (HPC clusters, AI) |
| Cost | Lower | Higher |
| Ecosystem | Cloud, enterprise, edge | HPC, AI, GPU clusters |
Mixed fabrics provide flexibility but also introduce complexity in routing, monitoring, and tuning. Proper planning is essential to maximize performance and value.
Exxact can help with fabric design and optimization tailored to your specific workloads. We offer full-rack integration, professional network mapping, and multi-node cluster deployment, ensuring your infrastructure is built for optimal performance. Contact us today to get started.
Fueling Innovation with an Exxact Designed Computing Cluster
Deploying full-scale AI models can be accelerated exponentially with the right computing infrastructure. Storage, head node, networking, compute - all components of your next Exxact cluster are configurable to your workload to drive and accelerate research and innovation.
Get a Quote Today
HPC
InfiniBand vs Ethernet in the Data Center
December 16, 20258 min read
Introduction
High-speed networking has become a foundational element of modern high-performance computing (HPC) and large-scale artificial intelligence (AI) infrastructures. As compute density increases and clusters scale to thousands of GPUs, the interconnect fabric often becomes the determining factor for overall system performance. Low latency, high bandwidth, and predictable communication behavior is just as important as the compute hardware itself.
Ethernet and InfiniBand remain the two primary technologies used to build high-performance interconnects. Each has evolved significantly, such as 800G/1.6T Ethernet, and next-generation InfiniBand HDR/NDR/XDR fabrics.
We will explain each technology, highlight its latest capabilities, and evaluate which networking architecture is the best fit for your computing infrastructure.
What Is Ethernet?
Ethernet is a widely used networking protocol for connecting devices in local area networks (LANs) and data centers, valued for its scalability, mature ecosystem, and consistent upgrade roadmap. Originally built for LANs, it has evolved into a high-performance fabric supporting 100GbE, 200GbE, 400GbE, and 800GbE links, with 1.6T Ethernet now entering early deployment.
Ethernet’s versatility makes it suitable for virtualized environments, large distributed systems, and AI clusters that prioritize scale and interoperability. Technologies such as RoCEv2, advanced congestion control, and DPU/SmartNIC acceleration extend Ethernet’s ability to deliver low-latency, RDMA-capable performance across large multi-rack deployments.
When to Use Ethernet
Ethernet is the preferred choice for general-purpose, cloud, and large-scale distributed workloads where cost efficiency, broad interoperability, and operational simplicity matter most. Its mature ecosystem and compatibility with standard TCP/IP environments make it easy to integrate across diverse data centers, including hybrid and multi-cloud deployments. Modern enhancements—such as RoCEv2, advanced congestion control, and DPU/SmartNIC acceleration—further strengthen Ethernet’s suitability for high-throughput applications.
Use Ethernet when:
- Running virtualized, containerized, or cloud-native workloads
- Managing infrastructure services such as monitoring, orchestration, or job scheduling
- Prioritizing cost efficiency and scalability across many racks or sites
- Applications do not require the ultra-low latency of specialized HPC fabrics
- Ensuring seamless compatibility with hybrid cloud or multi-vendor environments
What Is InfiniBand?
InfiniBand is a high-speed, low-latency interconnect designed for HPC and large-scale AI training. Its native RDMA architecture enables direct memory communication across nodes with minimal CPU involvement, reducing latency and improving throughput for tightly coupled workloads.
InfiniBand has progressed through several bandwidth generations—FDR (56 Gb/s), EDR (100 Gb/s), HDR (200 Gb/s), and today’s NDR (400 Gb/s), as well as emerging XDR class—providing predictable performance at scale. The ecosystem around InfiniBand, including GPUDirect RDMA, SHARP in-network acceleration, OpenMPI, and HPC schedulers, further optimizes collective operations and multi-node GPU performance.
When to Use InfiniBand
InfiniBand is the preferred interconnect for environments that require ultra-low latency, high sustained bandwidth, and efficient inter-node communication. Its native RDMA implementation, advanced congestion control, and predictable performance under load make it purpose-built for tightly coupled HPC workloads and large multi-node AI training.
Use InfiniBand when:
- Running workloads across many compute nodes, such as:
- Large-scale AI/ML training
- Scientific simulations (CFD, weather, molecular dynamics, physics codes)
- Applications require extremely low latency for frequent inter-node communication
- Workloads depend on high throughput and consistent performance during long-running jobs
- Leveraging MPI-based parallel frameworks, common in HPC and simulation workloads
- Deploying systems with high-speed GPU interconnects (e.g., NVIDIA NVLinkâ„¢/NVLink Switch on NVIDIA H200 NVL, HGXâ„¢ H200, HGX B200), where low-latency networking complements fast GPU-to-GPU communication across nodes
Deploying InfiniBand and Ethernet?
In modern HPC and AI data centers, Ethernet and InfiniBand often coexist to balance cost, performance, and operational flexibility. These hybrid fabrics assign each technology to the roles that best leverage its strengths.
Hybrid Deployment Strategy
A common approach separates control and compute traffic:
- Ethernet manages the control plane, including system monitoring, job scheduling, management traffic, and data I/O. Its broad compatibility and ecosystem support make it ideal for general infrastructure functions.
- InfiniBand connects compute nodes with ultra-low-latency, high-bandwidth links, optimizing tightly coupled workloads and speeding up time-to-result for AI training and HPC applications.
Dual-NIC Server Design
Some deployments equip servers with two NICs—one for Ethernet and one for InfiniBand:
- InfiniBand NIC handles RDMA, MPI traffic, and inter-node data movement for HPC and AI workloads.
- Ethernet NIC connects to storage, orchestration services, cloud gateways, or administrative interfaces.
This design is particularly effective for:
- AI clusters using GPUDirect RDMA over InfiniBand alongside NFS/S3 storage traffic over Ethernet
- HPC clusters where MPI traffic runs on InfiniBand, while large data transfers use Ethernet
- Hybrid cloud environments where Ethernet provides external connectivity and InfiniBand supports local high-performance compute
Frequently Asked Questions About InfiniBand vs Ethernet
1. Is Ethernet fast enough for AI and HPC workloads?
Yes—for many workloads. Modern Ethernet (400G–800G) with RoCE and DPUs performs well for distributed AI and large-scale data processing, but ultra-low-latency workloads may still benefit from InfiniBand.
2. When is InfiniBand the better choice?
InfiniBand is best for tightly coupled HPC and large AI training jobs that require predictable, ultra-low latency, and high sustained bandwidth across many nodes.
3. Can Ethernet and InfiniBand be used together?
Yes. Many organizations deploy mixed fabrics, using Ethernet for management, storage, and cloud connectivity, and InfiniBand for compute-intensive inter-node traffic.
4. How does network choice impact AI training time and efficiency?
Network latency and bandwidth directly affect GPU utilization and job completion time. High-performance fabrics like InfiniBand reduce communication overhead during gradient exchange and collective operations, improving overall training efficiency at scale.
5. How do I choose the right fabric for my environment?
In many cases, a hybrid approach delivers the best balance. Ethernet is often the best fit for distributed, cloud-integrated, or cost-sensitive environments, while InfiniBand is better suited for tightly coupled HPC and large AI training clusters that demand predictable, ultra-low-latency performance.
Conclusion
Ethernet and InfiniBand each serve distinct roles in modern data centers. Selecting the right fabric depends on your workload type, scale, and budget, and many organizations adopt a hybrid approach to leverage the strengths of both technologies.
- Ethernet offers broad compatibility, scalability, and cost-efficiency, making it ideal for general-purpose, cloud, and hybrid workloads.
- InfiniBand, by contrast, provides ultra-low latency, high bandwidth, and predictable performance, making it the preferred choice for HPC, large-scale AI, and tightly coupled workloads.
| Feature | Ethernet | InfiniBand |
| Latency | Higher | Lower |
| Bandwidth | 100 GbE – 800 GbE (1.6 TbE emerging) | HDR/NDR: 200–800 Gb/s per link; XDR (800-1.6Tbps) emerging |
| CPU Overhead | Moderate to high | Very low (native RDMA) |
| RDMA Support | Yes (RoCEv2, UEC standards) | Native |
| Scalability | High (large cloud/hybrid deployments) | Very high (HPC clusters, AI) |
| Cost | Lower | Higher |
| Ecosystem | Cloud, enterprise, edge | HPC, AI, GPU clusters |
Mixed fabrics provide flexibility but also introduce complexity in routing, monitoring, and tuning. Proper planning is essential to maximize performance and value.
Exxact can help with fabric design and optimization tailored to your specific workloads. We offer full-rack integration, professional network mapping, and multi-node cluster deployment, ensuring your infrastructure is built for optimal performance. Contact us today to get started.
Fueling Innovation with an Exxact Designed Computing Cluster
Deploying full-scale AI models can be accelerated exponentially with the right computing infrastructure. Storage, head node, networking, compute - all components of your next Exxact cluster are configurable to your workload to drive and accelerate research and innovation.
Get a Quote Today.jpg?format=webp)