Distributed computing aims to offer tools and mechanisms that enable the sharing, selection, and aggregation of a wide variety of geographically distributed computational resources in a transparent way. The research done in this team is based on the past expertise of the group, and on extending it towards the aspects of distributed computing that can benefit from this expertise. The team at BSC has a strong focus on programming models and resource management and scheduling in distributed computing ...

Team created to publish applications during COMPSs Tutorials, and share them among participants.

This team is to publish workflows executed from WPs that are not the three main pillars of the project.

It explores the modelling of natural catastrophes – in particular, earthquakes and their associated tsunamis shortly after such an event is recorded.

It develops innovative adaptive workflows for climate and for the study of Tropical Cyclones (TC) in the context of the CMIP6 experiment, including in-situ analytics.

It focuses on the construction of DigitalTwins for the prototyping of complex manufactured objects integrating state-of-the-art adaptive solvers with machine learning and data-mining, contributing to the Industry 4.0 vision.

Project that aims to create the NeuroPlat portal for neurodrug design

Presentation conducted during the Workflow Run RO-Crate bi-weekly meeting on how the Provenance Run Crate profile has been adopted by the COMPSs Workflow Management System.

Provenance registration is becoming more and more important, as we increase the size and number of experiments performed using computers. In particular, when provenance is recorded in HPC environments, it must be efficient and scalable. In this paper, we propose a provenance registration method for scientific workflows, efficient enough to run in supercomputers (thus, it could run in other ...

Session during the Innovative HPC workflows for industry (https://eflows4hpc.eu/event/innovative-hpc-workflows-for-industry/) that describes how Workflow Provenance is recorded with COMPSs: the background on the tools used, how the recording has been designed, and how to use it and inspect metadata.

Cheat sheet that serves as a quick guide to the many advanced features that PyCOMPSs offers. Updated for COMPSs release version 3.3.2.

This experiment has been executed using:

• Model: Decision Tree regressor (test.yaml)
• n_samples: 8 (number of ALYA simulations to be run)
• Nodes used in the MN5 supercomputer: 4
• ALYA_PROCS = 56

Adapted version of a workflow used in CAELESTIS for mechanical testing simulation which was developed by Riccardo Cecco (Workflows and Distributed Computing Group, BSC) with the guidance of Gerard Guillamet (Dual Technologies Research Group, BSC) and Aravind Sasikumar (AMADE Research UDG). The workflow ...

This experiment has been executed using:

• Model: SVR (test_SVR.yaml)
• n_samples: 8 (number of ALYA simulations to be run)
• Nodes used in the MN5 supercomputer: 2
• ALYA_PROCS = 28

Adapted version of a workflow used in CAELESTIS for mechanical testing simulation which was developed by Riccardo Cecco (Workflows and Distributed Computing Group, BSC) with the guidance of Gerard Guillamet (Dual Technologies Research Group, BSC) and Aravind Sasikumar (AMADE Research UDG). The workflow is distributed ...

Lysozyme in water full COMPSs application example, used during the Supercomputing 24 conference at the COMPSs Tutorial session.

Sensitivity Analysis to identify the material properties governing the structural failure of an open-hole test

Introduction

The certification of composite structures in the aeronautical sector follows a building-block pyramid approach, in which structural complexity, material uncertainties, and computational cost increase progressively across scales. To reduce reliance on extensive experimental campaigns, high-fidelity finite element simulations are increasingly employed for virtual testing. ...

Application that perform the multiplication between matrices.

K-means COMPSs application

COMPSs Matrix Multiplication resourceUsage profiling example.

MN5 MSIZE=20 BSIZE=768 7 Nodes (6 workers) (--num_nodes=7 --worker_in_master_cpus=0).

• Total number of tasks: 20^3 = 8000
• Maximum code parallelism: 20^2 = 400
• Total cores: 112*6 = 672
• Maximum utilisation: 400 / 112 = 3,57 Nodes

Overall stats from "pycompss inspect":

│ └── overall 
│ ├── matmul_tasks 
│ │ └── multiply 
│ │ ├── maxTime = 91,111 ms 
│ │ ├── executions = 8,000 
│ │ ├── avgTime = 84,839 ms 
│ │ └── minTime = 79,278 ms
...

Application that perform the multiplication between matrices. In this experiment, a new profiling visualization is available, showing the resource usage such as CPU, memory, data read and written to disk, and data sent and received over the network.

Lysozyme in water full COMPSs application. Added new WRROC profile: Provenance Run Crate

Application that perform the multiplication between matrices.

Name: PhysioNet kNN Kfold Contact Person: [email protected] Access Level: public License Agreement: Apache2 Platform: COMPSs Machine: MareNostrum5

Kfold to evaluate kNN accuracy on PhysioNet dataset (https://b2drop.bsc.es/index.php/s/8Q8MefXX2rrzaWs). This application used dislib-0.9.0

Name: PhysioNet CascadeCSVM Kfold Contact Person: [email protected] Access Level: public License Agreement: Apache2 Platform: COMPSs Machine: MareNostrum5

Kfold to evaluate CascadeCSVM accuracy on PhysioNet dataset (https://b2drop.bsc.es/index.php/s/8Q8MefXX2rrzaWs). This application used dislib-0.9.0

Name: PhysioNet RF Kfold Contact Person: [email protected] Access Level: public License Agreement: Apache2 Platform: COMPSs Machine: MareNostrum5

Kfold to evaluate RandomForest accuracy on PhysioNet dataset (https://b2drop.bsc.es/index.php/s/8Q8MefXX2rrzaWs). This application used dislib-0.9.0

Name: Random Forest Contact Person: [email protected] Access Level: public License Agreement: Apache2 Platform: COMPSs Machine: MareNostrum4 This is an example of Random Forest algorithm from dislib. To show the usage, the code generates a synthetical input matrix. The results are printed by screen. This application used dislib-0.9.0

Name: GridSearchCV Contact Person: [email protected] Access Level: public License Agreement: Apache2 Platform: COMPSs Machine: MareNostrum5

GridSearch of kNN algorithm for the iris.csv dataset (https://gist.githubusercontent.com/netj/8836201/raw/6f9306ad21398ea43cba4f7d537619d0e07d5ae3/iris.csv). This application used dislib-0.9.0

Name: GridSearchCV Contact Person: [email protected] Access Level: public License Agreement: Apache2 Platform: COMPSs Machine: MareNostrum5

GridSearch of kNN algorithm for the iris.csv dataset (https://gist.githubusercontent.com/netj/8836201/raw/6f9306ad21398ea43cba4f7d537619d0e07d5ae3/iris.csv). This application used dislib-0.9.0

Name: Matrix Multiplication Contact Person: [email protected] Access Level: public License Agreement: Apache2 Platform: COMPSs

Description

Matrix multiplication is a binary operation that takes a pair of matrices and produces another matrix.

If A is an n×m matrix and B is an m×p matrix, the result AB of their multiplication is an n×p matrix defined only if the number of columns m in A is equal to the number of rows m in B. When multiplying A and B, the elements of the ...

Name: Matrix Multiplication Contact Person: [email protected] Access Level: public License Agreement: Apache2 Platform: COMPSs

Description

Matrix multiplication is a binary operation that takes a pair of matrices and produces another matrix.

If A is an n×m matrix and B is an m×p matrix, the result AB of their multiplication is an n×p matrix defined only if the number of columns m in A is equal to the number of rows m in B. When multiplying A and B, the elements of the ...

Lysozyme in water full COMPSs application

Solutions to the exercises on the Workflow Provenance part, during January 2024 COMPSs Tutorial.