AI Infra
GPU-based AI Infrastructure
Design and operate GPU cluster-based AI infrastructure.
Guarantee high availability for AI training/inference with CoreLab Cluster.
Key Features
🖥️ GPU Cluster Build
Cluster design and deployment with NVIDIA H200 / H100 / L40S / RTX A6000 GPUs.
Optimize multi-GPU training with NVLink and InfiniBand networking.
⚡ AI Environment HA
Automatic failover on GPU server failure prevents training/inference downtime.
CoreLab Cluster guarantees 99.99% availability.
💾 Shared Storage
NVMe-based high-speed shared storage for model checkpoints and datasets,
synchronized in real-time across cluster nodes.
📊 Resource Monitoring
Real-time monitoring of GPU utilization, VRAM, temperature, and power consumption.
Track training job resource usage on a unified dashboard.
Supported GPUs
NVIDIA H200
HBM3e 141GB · NVLink 4.0
Maximum memory bandwidth, optimized for LLM training
NVIDIA H100
HBM3 80GB · NVLink 4.0
Optimized for large-scale LLM training
NVIDIA L40S
GDDR6 48GB · PCIe Gen4
Optimized for inference and generative AI
NVIDIA RTX A6000
GDDR6 48GB · PCIe Gen4
Cost-effective GPU option for various workloads
Infrastructure
| Compute | 2+ GPU servers (Active-Standby / Multi-GPU) |
| Network | InfiniBand NDR 400Gbps |
| Storage | NVMe SSD shared storage (model/dataset sync), local NVMe disk replication (A-A setup) |
| Platform | NVIDIA CUDA, Docker, Kubernetes (optional) |
| High Availability | CoreLab Cluster — Auto failover, real-time sync, web console |