Difference between revisions of "Performance Monitoring"
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* [https://www.clustercockpit.org/ ClusterCockpit] | * [https://www.clustercockpit.org/ ClusterCockpit] | ||
* [https://compendium.hpc.tu-dresden.de/software/pika/ PIKA] | * [https://compendium.hpc.tu-dresden.de/software/pika/ PIKA] | ||
| + | |||
| + | |||
| + | Individual metrics are typically collected with low level tools like: | ||
| + | |||
| + | * [[Likwid]] | ||
| + | * [[Perf]] | ||
| + | * RAPL | ||
| + | * ibstat | ||
| + | * nvidia-smi, nvml | ||
| + | * lctl, beegfs-sctl, mmpmon, nfsstat | ||
Revision as of 13:22, 17 September 2024
Performance monitoring can be done in the form of Performance profiling by the user or developer of an application or as a background service by the operator of an HPC cluster.
Monitoring the performance on a cluster-level gives the operator insight into the stable operation, utilization and possible defects of the cluster.
If the monitored data is available to the user, it can give insights into Job efficiency.
The available Performance metrics are a trade-off between usefulness and interference with job execution.
Take a look at the Site-specific documentation to figure out if performance monitoring is available at your cluster.
The following list shows some performance monitoring solutions:
Individual metrics are typically collected with low level tools like: