Memory leaks and single-allocation limits are common causes of 'out of memory' errors, even when sufficient physical memory exists. 'cuda-memcheck' is specifically designed to find memory errors in CUDA applications. While driver incompatibility is possible, leaks and allocation size limits are more frequent occurrences.

Explanation:Diagnosing GPU interconnect bottlenecks requires a multi-faceted approach. Visualizing the topology with 'nvidia-smi topo -m' , running NCCL benchmarks, monitoring GPU utilization for imbalances, and checking system logs for errors are all necessary for identifying and resolving communication issues. Ignoring any of these steps could lead to incomplete diagnosis and suboptimal performance.

DCGM is specifically designed for monitoring and managing GPUs in data centers, including detailed NVLink statistics in real time.
'nvidia-smi -display=nvlink' provides a snapshot, not real-time data. 'nvprof is a profiling tool and not ideal for continuous monitoring. 'iftop' and 'tcpdump' monitor network traffic, not NVLink. 'gpustat' does not offer the granular NVLink data of DCGM.

MIG instances being in a 'Disabled' state indicates a fundamental problem with the MIG configuration. Incompatible drivers (A) will prevent the instances from being properly initialized. If the GPU is not explicitly placed into MIG mode (B), no MIG instances will be available. The 'nvidia-persistenced' service (D) ensures that driver state persists across reboots, and its absence can cause MIG instances to revert to a disabled state. While unallocated instances (C) will exist, they should be in an 'Idle' state, not 'Disabled'. An insufficient power supply (E) might prevent the GPU from functioning correctly, but it's less likely to specifically cause a 'Disabled' MIG state.

Node affinity rules allow you to specify constraints on which nodes a pod can be scheduled on. By using node affinity rules, you can ensure that CPU-intensive tasks are scheduled on nodes without GPUs and GPU-intensive tasks are scheduled on nodes with GPUs. This optimizes resource utilization and cost. Taints and tolerations can be used, but affinity is more flexible. Resource quotas limit resource usage but do not control placement.