High-performance AI training infrastructure deployment solution for Kubernetes clusters, optimized for NVIDIA A100/A800 GPU clusters with InfiniBand networking.
- 🚀 High Performance: Optimized for NVIDIA A100/A800 GPU clusters
- 🌐 Advanced Networking: InfiniBand support with RDMA
- 📊 Comprehensive Monitoring: GPU and network metrics tracking
- 🔄 Automated Deployment: Streamlined setup process
- 🛡️ Production Ready: Enterprise-grade security and stability
graph TB
subgraph "Physical Network"
B[Bond4]
IB[InfiniBand Network]
lan0[LAN0] --> B
lan1[LAN1] --> B
lan2[LAN2] --> IB
lan3[LAN3] --> IB
lan4[LAN4] --> IB
lan5[LAN5] --> IB
end
subgraph "Network Control Plane"
NO[NVIDIA Network Operator]
VPC[VPC CNI]
MC[Multus CNI]
SRIOV[SR-IOV Device Plugin]
RDMA[RDMA Device Plugin]
NO --> VPC
NO --> MC
NO --> SRIOV
NO --> RDMA
end
subgraph "Pod Networking"
P1[AI Training Pod]
eth0[eth0]
rdma[RDMA Interface]
P1 --> eth0
P1 --> rdma
eth0 --> B
rdma --> IB
end
subgraph "Monitoring System"
PM[Prometheus]
GF[Grafana]
PM --> GF
end
- Kubernetes 1.20+
- NVIDIA A100/A800 GPUs
- Mellanox InfiniBand NICs
- Helm 3.0+
- Configure network environment:
./scripts/setup-network.sh- Deploy NVIDIA Network Operator:
./scripts/deploy-network-operator.sh- Verify deployment:
./scripts/test-network.sh- Bond4 configuration for management traffic
- InfiniBand network for high-speed data transfer
- RDMA support for direct memory access
- SR-IOV for network virtualization
- Prometheus for metrics collection
- Grafana for visualization
- Custom exporters for GPU and network metrics
- Comprehensive alerting rules
- Distributed training support
- GPU-aware scheduling
- NCCL optimization
- Topology-aware placement
- NVLink: Up to 600 GB/s bidirectional bandwidth
- InfiniBand: Up to 200 Gb/s network speed
- RDMA: Ultra-low latency communication
- GPUDirect: Optimized GPU-to-GPU transfer
Contributions are welcome! Please read our Contributing Guidelines for details.
This project is licensed under the Apache License 2.0 - see the LICENSE file for details.