Add draft gpu troubles

Author: mhuguesaws

troubleshooting/GPU-Troubleshooting.md

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+# GPU Troubleshooting Guide
+
+This guide presents how to identify and resolve issues on Amazon EC2 instances with NVIDIA GPUs.
+
+While running High-Performance Computing or Machine Learning workloads, GPUs may fail for various reasons captured by Xid messages.
+Those messages are placed in `/var/log/messages` for Amazon Linux or for Ubuntu in `/var/log/syslog` and `/var/log/kern.log`
+
+| Xid | Failure                                                                                           | Resolution          | Orchestrator                                            |
+| --- | ------------------------------------------------------------------------------------------------- | ------------------- | ------------------------------------------------------- |
+| 48  | Double Bit ECC                                                                                    | Terminate instances | [AWS ParallelCluster](#Terminate-and-replace-instances) |
+| 64  | ECC page retirement or row remapper recording failure<br> All reserved rows for bank are remapped | Terminate instances | [AWS ParallelCluster](#Terminate-and-replace-instances) |
+|     |                                                                                                   |                     |                                                         |
+| 79  | GPU has fallen off the bus                                                                        | Reboot              |                                                         |
+| 94  | Contained ECC error                                                                               | Reset GPUs          | [AWS ParallelCluster](#reset-gpus)                      |
+| 95  | Uncontained ECC error                                                                             | Reset GPUs          | [AWS ParallelCluster](#reset-gpus)                      |
+| 120 | GSP Error                                                                                         | Terminate instances | [AWS ParallelCluster](#Terminate-and-replace-instances) |
+
+# AWS ParallelCluster
+
+## Terminate and replace instances
+
+1. Create a reservation to isolate the node from being used by any jobs.
+
+   ```bash
+   sudo /opt/slurm/bin/scontrol create res starttime=now duration=infinite flags=ignore_jobs user=root nodes=[NODE_TO_TERMINATE]
+   ```
+
+1. Identify jobs using nodes to terminate
+
+   ```bash
+   squeue -w [NODE_TO_TERMINATE] -o %A -h
+   ```
+
+1. Cancel
+
+   ```bash
+   scancel [JOB_ID]
+   ```
+
+1. Place the node in **DRAIN**.
+
+   ```bash
+   sudo /opt/slurm/bin/scontrol update node=[NODE_TO_TERMINATE] state=drain reason=gpus-fail
+   ```
+
+   The node will have a **DRAIN** status. Then the instance will be terminated and replaced.
+
+1. Delete the reservation
+
+   ```bash
+   sudo /opt/slurm/bin/scontrol delete res root_[RES_NUMBER]
+   ```
+
+## Reset GPUs
+
+1. Create a reservation to isolate the node from being used by any jobs.
+
+   ```bash
+   sudo /opt/slurm/bin/scontrol create res starttime=now duration=infinite flags=ignore_jobs user=root nodes=[NODE_TO_TERMINATE]
+   ```
+
+1. Identify jobs using nodes to terminate
+
+   ```bash
+   squeue -w [NODE_TO_TERMINATE] -o %A -h
+   ```
+
+1. Cancel
+
+   ```bash
+   scancel [JOB_ID]
+   ```
+
+1. Reset the GPUs
+
+   ```bash
+   sudo /opt/slurm/bin/srun -w [NODE_TO_TERMINATE] nvidia-smi -r
+   ```
+
+1. Delete the reservation
+
+   ```bash
+   sudo /opt/slurm/bin/scontrol delete res root_[RES_NUMBER]
+   ```
+
+# Amazon SageMaker HyperPod
+
+TBD
+
+# Amazon EKS
+
+TBD