---
license: cc-by-4.0
task_categories:
- time-series-forecasting
language:
- en
tags:
- HPC
pretty_name: ClusterWise
size_categories:
- 100B<n<1T
---
## Data Overview

ClusterWise is a comprehensive dataset (240GB) containing real-world operational data from the OLCF Summit HPC cluster, one of the world's most powerful supercomputers. The dataset provides a rich collection of system telemetry, including:
- Job scheduler logs
- GPU failure event logs
- High-resolution temperature measurements from CPUs and GPUs
- Detailed power consumption metrics among components
- Physical layout information of the nodes

The complete dataset related pipeline is available in our [GitHub repository](https://github.com/AnemonePetal/hpc_dataset), enabling reproduction of the full 450GB dataset.

This dataset is ready for commercial/non-commercial use.


## Data Fields


| Field           | Type          | Description                                                                                     |
| :-------------- | :------------ | :---------------------------------------------------------------------------------------------- |
| timestamp       | timestamp[ms] | Timestamp of the record                                                                         |
| node_state      | string        | State of the node                                                                               |
| hostname        | string        | Hostname of the node, indicating its physical location. Format: `<cabinet_column:[a-h]><cabinet_row:[0-24]>n<node_in_rack:[1-18]>`. Node position in rack is from bottom (1) to top (18). |
| job_begin_time  | timestamp[ms] | Timestamp of when the job started                                                               |
| job_end_time    | timestamp[ms] | Timestamp of when the job terminated                                                            |
| allocation_id   | int64         | Unique identifier of the job                                                                    |
| label           | float64       | Indicates if the record corresponds to a failure event (e.g., 1 for failure, 0 for normal)    |
| xid             | float64       | Nvidia error code representing failure type                                                     |
| gpu0_core_temp  | float         | Core temperature of the 1st Nvidia V100 GPU attached to the first Power9 CPU (Celsius)          |
| gpu0_mem_temp   | float         | Memory (HBM) temperature of the 1st Nvidia V100 GPU attached to the first Power9 CPU (Celsius)  |
| gpu1_core_temp  | float         | Core temperature of the 2nd Nvidia V100 GPU attached to the first Power9 CPU (Celsius)          |
| gpu1_mem_temp   | float         | Memory (HBM) temperature of the 2nd Nvidia V100 GPU attached to the first Power9 CPU (Celsius)  |
| gpu2_core_temp  | float         | Core temperature of the 3rd Nvidia V100 GPU attached to the first Power9 CPU (Celsius)          |
| gpu2_mem_temp   | float         | Memory (HBM) temperature of the 3rd Nvidia V100 GPU attached to the first Power9 CPU (Celsius)  |
| gpu3_core_temp  | float         | Core temperature of the 1st Nvidia V100 GPU attached to the second Power9 CPU (Celsius)         |
| gpu3_mem_temp   | float         | Memory (HBM) temperature of the 1st Nvidia V100 GPU attached to the second Power9 CPU (Celsius) |
| gpu4_core_temp  | float         | Core temperature of the 2nd Nvidia V100 GPU attached to the second Power9 CPU (Celsius)         |
| gpu4_mem_temp   | float         | Memory (HBM) temperature of the 2nd Nvidia V100 GPU attached to the second Power9 CPU (Celsius) |
| gpu5_core_temp  | float         | Core temperature of the 3rd Nvidia V100 GPU attached to the second Power9 CPU (Celsius)         |
| gpu5_mem_temp   | float         | Memory (HBM) temperature of the 3rd Nvidia V100 GPU attached to the second Power9 CPU (Celsius) |
| p0_gpu0_power   | float         | DC power consumption of the 1st Nvidia V100 GPU attached to the first Power9 CPU (Watts)        |
| p0_gpu1_power   | float         | DC power consumption of the 2nd Nvidia V100 GPU attached to the first Power9 CPU (Watts)        |
| p0_gpu2_power   | float         | DC power consumption of the 3rd Nvidia V100 GPU attached to the first Power9 CPU (Watts)        |
| p0_power        | float         | DC power consumption of the first Power9 CPU in the node (Watts)                                |
| p0_temp_max     | float         | Maximum core temperature of the first Power9 CPU (Celsius)                                      |
| p0_temp_mean    | float         | Mean core temperature of the first Power9 CPU (Celsius)                                         |
| p0_temp_min     | float         | Minimum core temperature of the first Power9 CPU (Celsius)                                      |
| p1_gpu0_power   | float         | DC power consumption of the 1st Nvidia V100 GPU attached to the second Power9 CPU (Watts)       |
| p1_gpu1_power   | float         | DC power consumption of the 2nd Nvidia V100 GPU attached to the second Power9 CPU (Watts)       |
| p1_gpu2_power   | float         | DC power consumption of the 3rd Nvidia V100 GPU attached to the second Power9 CPU (Watts)       |
| p1_power        | float         | DC power consumption of the second Power9 CPU in the node (Watts)                               |
| p1_temp_max     | float         | Maximum core temperature of the second Power9 CPU (Celsius)                                     |
| p1_temp_mean    | float         | Mean core temperature of the second Power9 CPU (Celsius)                                        |
| p1_temp_min     | float         | Minimum core temperature of the second Power9 CPU (Celsius)                                     |
| ps0_input_power | float         | AC input power consumption of the first node power supply (Watts)                               |
| ps1_input_power | float         | AC input power consumption of the second node power supply (Watts)                              |



## How to use it

You can load the dataset with the following lines of code.

````
from datasets import load_dataset
ds = load_dataset("MachaParfait/ClusterWise")
````

## License/Terms of Use

This dataset is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0) available at [https://creativecommons.org/licenses/by/4.0/legalcode](https://creativecommons.org/licenses/by/4.0/legalcode).


## Data Version

1.0 (05/15/2025)


## Intended use

The Clusterwise Dataset is intended to be used by the community to continue to improve open models. The data may be freely used to train models. **However, for each dataset an user elects to use, the user is responsible for checking if the dataset license is fit for the intended purpose**.