The challenges facing AI computing
Fragmented AI computing resources and provider challenge
Inconsistent AI compute usage patterns and interfaces
AI computing standards and governance challenge
AI computing cost measurement challenge
Supercomputing resources are fragmented and numerous providers are available.
Inconsistent usage patterns and interfaces Lack of unified norms and standards
Unable to enforce unified regulation; energy consumption usage cannot be monitored.
Inability to uniformly measure costs
What is an AI computing power scheduling platform?
CloudChef AI Computing Power Scheduling Platform integrates heterogeneous computing platforms, resource pools, clusters, and queues. It schedules workloads by application, model, capacity, and resource requirements, then standardizes delivery with lifecycle management, utilization analysis, energy monitoring, and computing cost governance.
AI computing power scheduling platform architecture
Full Lifecycle Management of Computing Power Services
Full lifecycle management of AI computing services
High-performance computing service workflow
Basic Process of High-Performance Computing Services in Supercomputing Clusters
Principles for Compliance Optimization of Computing Power Costs
Computing power cost governance framework
Unified computing power analysis with multi-dimensional visualization
Multi-dimensional AI computing power analysis dashboard
Computing Power Resource Scheduling Platform: Scheduling Center
AI Computing Scheduling Workflow
Obtain resource information of data centers, clusters, and queues through the resource pool.
Dynamically perceive the load of underlying resources.
The rules engine implements rule-based decisions on resource usage.
The AI training platform optimizes the rules engine.
The task engine accepts tasks.   The task executor implements the execution of different tasks.   Tasks are scheduled based on the load.
AI computing resource pool and cluster discovery
Rules engine for AI computing resource optimization
Task engine for workload and resource scheduling