Metadata examples

This Section intends to be a compilation of references where you can find Workflow Provenance metadata examples generated by COMPSs and real shared use cases. Since the metadata generation evolves on each COMPSs version, here you will see examples for the different versions of COMPSs that support its generation (i.e. from version 3.0).

For a more extensive list, you can go to WorkflowHub, click Discover and filter by Workflow type COMPSs (direct link).

At Zenodo, you can filter by Subject -> COMPSs (direct link).

COMPSs 3.4

• General Sensitivity Analysis (GSA) using CAELESTIS HPC-based workflows:

  • https://doi.org/10.5281/zenodo.18934347

  • https://doi.org/10.48546/workflowhub.workflow.2109.1

COMPSs 3.3.3

• [DTC-V3] WF5301: PyCOMPSs DT-LAVA-WF - Etna 2006 lava test-case: https://workflowhub.eu/workflows/1838

COMPSs 3.3.1

• CAELESTIS mechanical testing simulation, using Decision Tree regressor model, 8 n_samples, and 4 MN5 nodes, ALYA_PROCS 56 https://doi.org/10.48546/workflowhub.workflow.1198.1

• SC24 Lysozyme in water full (4 MPI processes) https://doi.org/10.48546/workflowhub.workflow.1197.1

• CAELESTIS mechanical testing simulation, using SVR model, 8 n_samples, and 2 MN5 nodes, ALYA_PROCS 28 https://doi.org/10.48546/workflowhub.workflow.1195.1

• PhysioNet CascadeSVM Kfold: https://doi.org/10.48546/workflowhub.workflow.1124.1

• PhysioNet kNN Kfold: https://doi.org/10.48546/workflowhub.workflow.1123.2

• PhysioNet RF Kfold: https://doi.org/10.48546/workflowhub.workflow.1122.1

• GridSearch on kNN non data persistence: https://doi.org/10.48546/workflowhub.workflow.1095.1

• GridSearch on kNN: https://doi.org/10.48546/workflowhub.workflow.1094.1

• Java COMPSs Matrix Multiplication, out-of-core using files, reproducible example, data persistence False, MareNostrum V: https://doi.org/10.48546/workflowhub.workflow.1088.1

• Java COMPSs Matrix Multiplication, out-of-core using files, reproducible example, data persistence True: https://doi.org/10.48546/workflowhub.workflow.1086.1

• Lysozyme in water full (GitHub): https://doi.org/10.48546/workflowhub.workflow.1076.2

• Randomized SVD: https://doi.org/10.48546/workflowhub.workflow.1070.1

• Java COMPSs LU Factorization for Sparse Matrices, MareNostrum V, 3 nodes, no data persistence: https://doi.org/10.48546/workflowhub.workflow.1047.1

• PyCOMPSs Matrix Multiplication, out-of-core using files. Example using DIRECTORY parameters executed at laptop, data persistence True: https://doi.org/10.48546/workflowhub.workflow.1046.1

• PyCOMPSs: Matrix multiplication without data persistence: https://doi.org/10.48546/workflowhub.workflow.839.1

• PyCOMPSs: Matrix multiplication with data persistence: https://doi.org/10.48546/workflowhub.workflow.838.1

COMPSs 3.3

• COMPSs GPU Cache DNN Distributed Training: https://doi.org/10.48546/workflowhub.workflow.802.1

• COMPSs GPU DNN Distributed Training: https://doi.org/10.48546/workflowhub.workflow.801.1

• COMPSs GPU Cache K-Means: https://doi.org/10.48546/workflowhub.workflow.800.1

• COMPSs GPU K-Means: https://doi.org/10.48546/workflowhub.workflow.799.1

• COMPSs GPU Cache Matrix Multiplication: https://doi.org/10.48546/workflowhub.workflow.798.1

• COMPSs GPU Matrix Multiplication: https://doi.org/10.48546/workflowhub.workflow.797.1

• PyCOMPSs Probabilistic Tsunami Forecast (PTF) - Kos-Bodrum 2017 earthquake and tsunami test-case: https://doi.org/10.48546/workflowhub.workflow.781.1

• PyCOMPSs Probabilistic Tsunami Forecast (PTF) - Boumerdes-2003 earthquake and tsunami test-case: https://doi.org/10.48546/workflowhub.workflow.779.1

• Random Forest Classifier executed in 3 nodes, 1 master and 2 workers, with a generated dataset, using 1 Million rows x 100 features: https://doi.org/10.48546/workflowhub.workflow.748.1

• Lysozyme in water sample, dataset_small, data_persistence True, nct00014 username, 4 workers: https://doi.org/10.48546/workflowhub.workflow.714.1

• Cluster Comparison data_persistence True: https://doi.org/10.48546/workflowhub.workflow.713.1

• K-means data_persistence True: https://doi.org/10.48546/workflowhub.workflow.712.1

• Cholesky factorisation, SIZE 4, BSIZE 512, data_persistence True: https://doi.org/10.48546/workflowhub.workflow.711.1

• Wordcount reduce version, data_persistence True: https://doi.org/10.48546/workflowhub.workflow.710.1

• Wordcount merge version, data_persistence False: https://doi.org/10.48546/workflowhub.workflow.709.1

• Lysozyme in water full version, using dataset_small, data_persistence False: https://doi.org/10.48546/workflowhub.workflow.708.1

• Lanczos SVD: https://doi.org/10.48546/workflowhub.workflow.690.1

• PyCOMPSs Wordcount test, dividing input file in blocks, only Python dictionaries used as task parameters (run at MareNostrum IV): https://doi.org/10.48546/workflowhub.workflow.687.1

• Java COMPSs wordcount example (laptop run, files used as inputs): https://doi.org/10.48546/workflowhub.workflow.684.1

• PyCOMPSs Increment example, ran at Marenostrum IV supercomputer, example of INOUT file and compss_open usage: https://doi.org/10.48546/workflowhub.workflow.678.1

• PyCOMPSs simple example (ran on macOS laptop, input generated by the code, INOUT file example): https://doi.org/10.48546/workflowhub.workflow.673.1

• Java COMPSs K-means clustering example (executed at Marenostrum IV supercomputer, inputs generated by the code): https://doi.org/10.48546/workflowhub.workflow.663.1

• PyCOMPSs WordCount Example: https://doi.org/10.48546/workflowhub.workflow.635.1

• PyCOMPSs Matrix Multiplication with Objects (inputs generated by the code): https://doi.org/10.48546/workflowhub.workflow.627.1

• eFlows4HPC Demo ROM Workflow: https://doi.org/10.48546/workflowhub.workflow.614.1

COMPSs 3.2

• Sample workflow that combines simulations with data analytics: https://doi.org/10.48546/workflowhub.workflow.541.1

• Java COMPSs LU Factorization for Sparse Matrices: https://doi.org/10.48546/workflowhub.workflow.515.1

• PyCOMPSs Matrix Multiplication, out-of-core, using files: https://doi.org/10.48546/workflowhub.workflow.485.1

• Java COMPSs Matrix Multiplication, out-of-core, using files: https://doi.org/10.48546/workflowhub.workflow.484.1

COMPSs 3.1

• BackTrackBB: Multi-band array detection and location of seismic sources (PyCOMPSs implementation): https://doi.org/10.5281/zenodo.7602137

COMPSs 3.0

• BackTrackBB: Multi-band array detection and location of seismic sources: https://doi.org/10.48546/workflowhub.workflow.386.2

• Lysozyme in Water COMPSs workflow: https://doi.org/10.48546/workflowhub.workflow.379.1