GPU Scheduling and Resource Management in Containerized Environments

  1. GPU Allocation and Sharing Strategies
    1. Exclusive GPU Allocation
      1. One-to-One Mapping Model
        1. Dedicated GPU Assignment
          1. Resource Isolation Benefits
            1. Performance Predictability
            2. Use Cases for Exclusive Access
              1. High-Performance Training
                1. Production Inference
                  1. Sensitive Workloads
                  2. Implementation Considerations
                    1. Resource Waste Potential
                      1. Cost Implications
                        1. Scheduling Complexity
                      2. GPU Time-Slicing
                        1. Temporal Sharing Principles
                          1. Context Switching Mechanisms
                            1. Time Quantum Management
                              1. Scheduling Algorithms
                              2. Implementation Approaches
                                1. Driver-Level Time-Slicing
                                  1. Container Runtime Integration
                                    1. Kubernetes Scheduler Extensions
                                    2. Performance Characteristics
                                      1. Latency Implications
                                        1. Throughput Impact
                                          1. Memory Overhead
                                          2. Configuration and Tuning
                                            1. Time Slice Duration
                                              1. Priority Scheduling
                                                1. Fairness Policies
                                              2. GPU Spatial Partitioning
                                                1. NVIDIA Multi-Instance GPU
                                                  1. MIG Architecture Overview
                                                    1. GPU Instance Creation
                                                      1. Compute Instance Management
                                                        1. Memory Partitioning
                                                          1. Hardware Isolation Features
                                                            1. Configuration Tools
                                                              1. Kubernetes Integration
                                                                1. Performance Characteristics
                                                                2. AMD GPU Partitioning
                                                                  1. Partitioning Capabilities
                                                                    1. Configuration Methods
                                                                      1. Kubernetes Support
                                                                      2. Intel GPU Partitioning
                                                                        1. SR-IOV Support
                                                                          1. Virtual Function Management
                                                                            1. Kubernetes Integration
                                                                          2. Virtual GPU Technologies
                                                                            1. GPU Virtualization Approaches
                                                                              1. API Interception
                                                                                1. Hardware Virtualization
                                                                                  1. Paravirtualization
                                                                                  2. vGPU Implementation
                                                                                    1. NVIDIA GRID vGPU
                                                                                      1. AMD MxGPU
                                                                                        1. Intel GVT-g
                                                                                        2. Container Integration
                                                                                          1. vGPU Device Plugins
                                                                                            1. Resource Management
                                                                                              1. Performance Considerations
                                                                                              2. Licensing and Support
                                                                                                1. Commercial Licensing Models
                                                                                                  1. Open Source Alternatives
                                                                                                    1. Support Limitations

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                                                                                                3. Core Mechanisms for GPU Management in Kubernetes

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                                                                                                5. Advanced GPU Scheduling