AI Computing Network
The AI computing network solution covers GPU clusters, training platforms, inference pools, InfiniBand, RoCE, lossless Ethernet, 400G/800G links, operations, and monitoring.
Solution Capabilities
GPU cluster planning
Design switching and links based on GPU count, node topology, and communication patterns.
InfiniBand networking
Support IB switching, HCA, cables, port rates, partitions, and link health.
RoCE lossless Ethernet
Plan PFC, ECN, QoS, buffer strategy, and congestion control.
Training network monitoring
Monitor errors, drops, congestion, utilization, and job communication anomalies.
Key domains of AI networks
Training, storage, management, service access, and monitoring traffic must be designed as coordinated network domains.
GPU-to-GPU communication with low latency and lossless transport.
Dataset access, checkpointing, model storage, and shared file systems.
Node management, scheduling, logs, alerts, and health monitoring.
Implementation Path
Scale assessment
Confirm GPUs, nodes, framework, job size, and expansion plan.
Technology route
Choose IB, RoCE, or hybrid design based on performance and budget.
Cabling design
Plan 400G/800G modules, DAC/AOC, and high-density cabling.
Validation
Validate link quality, lossless settings, and communication performance.
Monitoring
Track port errors, congestion, link health, and job network issues.
Application Scenarios
AI training clusters
Large-scale distributed training and dense GPU clusters.
Inference resource pools
Stable network access and operations for multi-service inference.
Research HPC
Parallel computing, simulation, and scientific workloads.
Need a solution assessment?
Lingtao Technology can assess topology, operations, monitoring, security, and delivery scope based on your project scenario.
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