Cheetah is an experiment harness for running codesign experiments to study the effects of online data analysis at the exascale. It provides a way to run large campaigns of experiments to understand the advantages and tradeoffs of different compression and reduction algorithms run using different orchestration mechanisms. Experiments can be run to analyze data offline, in situ (via a function that is part of the application), or online (in a separate, stand-alone application). The workflow may be composed so that different executables reside on separate nodes, or share compute nodes, in addition to fine-tuning the number of processes per node.
Users create a campaign specification file in Python that describes the applications that form the workflow, and the parameters that they are interested in exploring. Cheetah creates the campaign endpoint on the target machine, and users can then launch experiments using the generated submission script.
Cheetah's runtime framework, Savanna, translates experiment metadata into scheduler calls for the underlying system and manages the allocated resources for running experiments. Savanna contains definitions for different supercomputers; based upon this information about the target machine, Savanna uses the appropriate scheduler interface (aprun, jsrun, slurm) and the corresponding scheduler options to launch experiments.
Cheetah is centered around ADIOS, a middleware library that provides an I/O framework along with a publish-subscribe API for exchanging data in memory. Typically, all ADIOS-specific settings are set in an XML file that is read by the application. Cheetah provides an interface to edit ADIOS XML files to tune I/O options.
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Dependency: Linux, Python 3.5+, psutil
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On supercomputers it should be installed at a location accessible from the parallel file system
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Cheetah can be installed via the Spack package manager as
spack install codar-cheetah@develop. -
Users can also download Cheetah and set the PATH:
git clone git@github.com:CODARcode/cheetah.git cd cheetah python3 -m venv venv-cheetah source venv-cheetah/bin/activate pip install --editable .
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Cheetah has been tested on Summit (ORNL), Andes (ORNL), Theta (ANL), Cori (LBNL), and standalone Linux computers
source <cheetah dir>/venv-cheetah/bin/activateThe recommended start is to go through the Cheetah Tutorial under docs/Tutorials.
The Cheetah documentation can be found at https://codarcode.github.io/cheetah.
The current release is 1.1.3.
| System Name | Cheetah Support | System supports Node-Sharing | Cheetah Node-Sharing Support |
|---|---|---|---|
| Local Linux machines | ✅ | N/A | N/A |
| Frontier (ORNL) | ✅ | -- | -- |
| Perlmutter (NERSC) | ✅ | -- | -- |
| Summit (ORNL) | ✅ | ✅ | ✅ |
| Andes (ORNL) | ✅ | ❌ | ❌ |
| Spock (ORNL) | ✅ | -- | -- |
| Theta (ANL) | ✅ | ❌ | N/A |
| Cori (LBNL) | ✅ | ✅ | In progress |
The primary authors of Cheetah are Kshitij Mehta (ORNL) and Bryce Allen (University of Chicago). All contributors are listed here.
To refer to Cheetah in a publication, please cite the following paper:
- Mehta, Kshitij, Allen, Bryce, Wolf, Matthew, Logan, Jeremy, Suchyta, Eric, Singhal, Swati, Choi, Jong Youl, Takahashi, Keichi, Huck, Kevin, Yakushin, Igor, Sussman, Alan, Munson, Todd, Foster, Ian, and Klasky, Scott.
"A codesign framework for online data analysis and reduction"
Journal: Concurrency and Computation: Practice and Experience
https://doi.org/10.1002/cpe.6519.
Other paper:
- K. Mehta et al., "A Codesign Framework for Online Data Analysis and Reduction," 2019 IEEE/ACM Workflows in Support of Large-Scale Science (WORKS), Denver, CO, USA, 2019, pp. 11-20.
doi: 10.1109/WORKS49585.2019.00007
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8943548&isnumber=8943488
For more examples of using Cheetah, see the examples directory.
- Calculating Euler's number
- Using Cheetah to run coupled applications
- Brusselator
- The Gray-Scott Reaction-Diffusion Benchmark
- Gray-Scott with compression, Z-Checker and FTK
Cheetah is open source and we invite the community to collaborate. Create a pull-request to add your changes to the dev branch.
Please open an issue on the github issues page to report a bug.
Cheetah is licensed under the Apache License v2.0. See the accompanying Copyright.txt for more details.