A well-architected network is the backbone of a high-performance AI cluster. We design three dedicated networks to eliminate bottlenecks and maximize parallel computing efficiency.
High-bandwidth, low-latency network infrastructure purpose-built for GPU-to-GPU collective communication. Supports NCCL, RDMA over Converged Ethernet (RoCE), and InfiniBand to maximize GPU utilization during large-model training.
Ultra-high-throughput network dedicated to data read/write and storage traffic. Provisioned with premium specifications to ensure I/O never becomes a bottleneck that constrains parallel-computing performance or training throughput.
Dedicated management plane for cluster device administration, user access control, and business operation workflows. Isolated from compute traffic to ensure security, stability, and predictable latency for control-plane operations.
For large-scale AI clusters, RDMA over Converged Ethernet (GRoCE) delivers significantly lower total cost of ownership while maintaining high-performance collective communication across thousands of GPUs.
SEA recommends GRoCE as the default compute network solution for clusters requiring rapid deployment, cost efficiency, and operational simplicity without sacrificing performance.
GRoCE can be delivered within weeks, compared to several months for InfiniBand lead times.
Fully compatible with standard Ethernet infrastructure, enabling seamless integration with existing data center environments and operational tools.
Mature technology with extensive production deployments. DCQCN congestion control and PFC ensure lossless, predictable network behavior under heavy AI workloads.
Leverages commodity Ethernet switches and standard cables, dramatically reducing CapEx while maintaining near-IB performance for distributed training.
Comprehensive data center infrastructure planning to ensure your AI cluster is built on a solid, scalable foundation. SEA's engineering team conducts thorough site surveys and produces detailed floor plans before any equipment is deployed.
Professional on-site construction, integration, and commissioning to bring your AI cluster online safely and efficiently. Every step follows a strict quality checklist verified jointly with the customer.
From initial planning to ongoing operations, SEA covers every phase of the AI cluster lifecycle with professional expertise and proven methodologies.
Site surveys, rack planning, equipment commissioning, and hardware validation — every step documented and quality-checked.
Physical site assessment: power availability, cooling capacity, floor space, and network fiber access for the target cluster footprint.
Rack layout planning, air conditioning positioning, PDU outlet selection, and cable tray routing aligned with cluster network topology.
Joint inspection on delivery: outer packaging condition, hardware configuration verification, BMC access, and SN-based asset registration.
GPU power burn-in using gpu-burn tools to validate stability and cooling performance under full compute load.
Multi-layered, modular, system-level tuning that delivers the high-performance network environment required by large-model AI workloads.
The AI computing center monitoring and management system provides enterprises with comprehensive O&M services — from monitoring and alerting to automated operations and intelligent analytics.
Multi-tenant isolation, quota management, resource allocation, and billing for cloud-native AI compute clusters.
Hardware asset inventory, lifecycle tracking, warranty management, and hardware change management.
Real-time GPU/CPU/memory/network metrics, temperature, power consumption, and utilization dashboards.
Configurable thresholds, multi-channel alerts (email, SMS, webhook), and intelligent anomaly detection.
Root cause analysis, error code lookup, topology visualization, and guided remediation workflows.
Scheduled tasks, batch operations, firmware updates, and self-healing scripts for unattended O&M.
Predictive analytics, capacity forecasting, training job profiling, and performance trend analysis.
Expert CLI interface for rapid device configuration. DCQCN, RDMA NIC parameters, and trap-alarm settings management.
Purpose-built for the management, scheduling, and end-to-network O&M of large-model AI training workloads.
Multi-level priority queues ensure high-importance jobs get GPU resources first. Configurable priority rules per tenant, user, or job type.
Preemption support allows critical jobs to temporarily suspend lower-priority workloads, maximizing cluster responsiveness to urgent compute demands.
Automatic job restart and checkpoint-based recovery upon GPU or node failures. Minimize wasted compute cycles from transient hardware issues.
Intelligent job placement that considers network topology, NVLink/NUMA affinity, and NCCL communication patterns to minimize cross-node bandwidth bottlenecks.
The scheduling platform provides a unified real-time view of all cluster resources — GPU availability by node, network topology, job queue status, training efficiency metrics (MFU), and cost attribution per tenant. Spine-Leaf architecture planning ensures optimal East-West traffic patterns with maximum path diversity and minimal oversubscription.
Complete range of GPU models, high cost-effectiveness, ready to use — serving multiple applications with a thousand-card cluster and professional full-lifecycle services.
Utilize SEA's mature AI cloud computing technology to help your team integrate existing computing resources and easily go to the cloud.
Not only H100, A100, but also multiple types of GPU resources to meet various computing power needs across large models, AIGC, finance, and healthcare.
7×24 hour on-site technical support, with rich experience in daily operation and maintenance, fault handling, and emergency response.
Redundant disaster recovery, strict access control monitoring, and fiber optic ring network with a connectivity rate of 99.99%.
Pre-planning, post-operation and maintenance management, personalized solutions, supporting module customization and flexible infrastructure customization.
Utilize SEA's comprehensive AI computing power cluster management system to alleviate the work pressure of cluster managers and improve efficiency.
SEA IT Innovation optimizes GPU underlying hardware and software to define a high-performance GPU computing platform. We provide industry users with flexible, ready-to-use GPU computing power and acceleration services, accelerating the delivery of applications in AI across various industries.
Contact SEA IT today for a professional cluster networking assessment and customized solution design.
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