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eBook·Whitepaper
GPU Monitoring Strategies for Sustainable AI Infrastructure Operations
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As AI adoption accelerates, GPUs have become a core piece of strategic infrastructure that directly shapes enterprise competitiveness. However, GPUs come with inherent structural constraints—high acquisition costs, ongoing supply shortages, and rapid generational turnover. Without disciplined management, these factors can significantly erode the return on investment across the entire AI infrastructure stack.

In this content, we examine the key challenges facing GPU operations, outline practical strategies for improving utilization efficiency, and present a GPU monitoring methodology designed to enable effective AI infrastructure governance.

Chapter 1: Strategic Value of AI Infrastructure and GPU

  • The Strategic Significance of GPUs in the AI Era
  • The Surge in Global GPU Demand
  • Operational Challenges: High Capital Costs and Resource Scarcity

Chapter 2: Why GPU Monitoring Matters

  • Addressing GPU Resource Contention and Utilization Disparity
  • Monitoring for Waste Reduction and Efficiency Improvement
  • Case Study: NERSC Perlmutter Supercomputer

Chapter 3: How GPU Monitoring Differs from Traditional Methods

  • Differences Between GPU and Traditional Infrastructure Management
  • Limitations of Cloud and Bare-Metal Approaches
  • The Necessity of AI Workload-Specific Monitoring

Chapter 4: GPU Resource Management Strategies

  • Efficiency and Limitations of High-Performance GPU Adoption
  • Resource Partitioning Methods: vGPU and MIG
  • Physical Isolation and Stability Enhancement Based on MIG

Chapter 5: GPU Monitoring Methodologies

  • Job Scheduler-Based Management and Prediction
  • Container-Native Observability Approaches
  • Combined Analysis of Metrics, Traces, and Logs

Chapter 6: WhaTap Labs' GPU Monitoring Approach

  • Integrated Monitoring for MIG and Kubernetes Environments
  • GPU Trend and Inventory-Based Management
  • Pod-Level Tracking and Real-Time Anomaly Detection

Chapter 7: GPU Monitoring: The Cornerstone of AI Governance

  • The Rise of Generative AI and Uncertainty Management
  • GPU Operation Strategy and Cost Optimization
  • The Core Starting Point for Establishing Governance
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