Distributed AI Cluster Management
A system method for organizing, scheduling and optimizing large-scale AI computing resources deployed in distributed arrays
Resource Orchestration
- Automated Node Discovery & Registration
- Unified Resource Pool Management
- Topology-Aware Scheduling
Distributed Training
- Hybrid Parallelism Strategy
- Elastic Parameter Server Architecture
- AllReduce Optimization Suite
Elastic Scaling
- Dynamic Node Membership Management
- Fault Tolerance & Checkpoint Recovery
- Intelligent Auto-Scaling
Communication Optimization
- RDMA High-Speed Network
- Gradient Compression
- Communication-Computation Overlap
Low Latency
High Throughput
Storage & Monitoring
- Distributed File System Integration
- Data Localization Cache
- Cluster Health Monitoring
- Visualization Dashboard