⚡ HPC Resource Library

High-speed network infrastructure solutions and best practices for AI Computing Centers, AI Data Centers, and GPU Clusters

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AI Computing Center Network Architecture

Network Architecture

From Spine-Leaf architecture to three-tier networks, detailed explanation of AI Computing Center network topology design principles and bandwidth planning strategies.

  • Spine-Leaf Architecture Design
  • 100G/400G Uplink Bandwidth Planning
  • East-West Traffic Optimization
  • Network Convergence Ratio Calculation
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25G/100G NIC Selection

Bandwidth Planning

For AI Computing Center scenarios, detailed explanation of how to select appropriate NICs and optical module solutions based on GPU cluster scale.

  • 25G vs 100G Cost-Benefit Analysis
  • Multi-NIC Bonding (LAG) Solutions
  • NIC and Switch Port Matching
  • Bandwidth Requirement Calculation
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Low Latency Network Configuration

Latency Optimization

Comprehensive network latency optimization from NIC drivers to switch configuration, supporting trillion-parameter LLM training.

  • Enable NIC Offload Features
  • Jumbo Frame Configuration
  • QoS Priority Queue Settings
  • Latency Testing and Monitoring
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RDMA Network Configuration

RDMA Configuration

RoCEv2, iWARP, InfiniBand... Detailed explanation of mainstream RDMA technologies and configuration practices in VMware environments.

  • RoCEv2 vs iWARP Comparison
  • PFC Flow Control Configuration
  • DCB QoS Settings
  • RDMA Performance Verification
PDF Coming Soon
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GPU Cluster Interconnect Solutions

Cluster Solutions

Best practices for NIC and DAC/optical module pairing in AI training clusters and HPC computing scenarios.

  • GPUDirect RDMA Configuration
  • NCCL Cluster Communication Optimization
  • DAC vs Optical Module Selection
  • Cluster Network Troubleshooting
PDF Coming Soon
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Computing Center Upgrade Path

Upgrade Solutions

Smooth evolution strategies from 1G to 10G and from 25G to 100G, reducing upgrade risks and total cost of ownership.

  • Existing Infrastructure Assessment
  • Phased Upgrade Strategy
  • Compatibility Assurance Measures
  • Upgrade Effectiveness Metrics
PDF Coming Soon

📈 EZMAX Network Solution Performance Metrics

<2μs
End-to-End Latency
99.99%
Network Availability
100G
Single Port Bandwidth
<1%
Packet Loss Rate

💡 HPC Network Best Practices

Prioritize Spine-Leaf Architecture

For AI Computing Centers with more than 100 servers, Spine-Leaf architecture is recommended. East-west traffic bandwidth is sufficient, and network convergence ratio can be controlled within 1:1.5.

Decouple NICs from Switches

When selecting NICs, verify compatibility with mainstream switches (Huawei, H3C, Arista, etc.) to avoid awkward situations where purchased equipment cannot be connected.

Prioritize DAC over Optical Modules

For intra-rack interconnection (within 3 meters), prioritize DAC high-speed copper cables. Lower cost, ultra-low latency, and no optical module failure worries.

Plan Optical Module Inventory in Advance

AI Computing Centers involve large quantities of optical modules. Establish a green channel for optical module procurement with suppliers to avoid out-of-stock risks during failures.

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