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

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 ...

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

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.

Name: PhysioNet kNN Kfold Contact Person: support-compss@bsc.es 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: support-compss@bsc.es 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: support-compss@bsc.es 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: support-compss@bsc.es 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: support-compss@bsc.es 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: support-compss@bsc.es 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: support-compss@bsc.es 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: support-compss@bsc.es 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

Lysozyme in water full COMPSs application, using dataset_small

Lysozyme in water full COMPSs application

Name: KMeans Contact Person: support-compss@bsc.es Access Level: public License Agreement: Apache2 Platform: COMPSs Machine: MareNostrum5

KMEans for clustering the housing.csv dataset (https://github.com/sonarsushant/California-House-Price-Prediction/blob/master/housing.csv). This application used dislib-0.9.0

Name: TruncatedSVD (Randomized SVD) Contact Person: support-compss@bsc.es Access Level: public License Agreement: Apache2 Platform: COMPSs Machine: MareNostrum5

TruncatedSVD (Randomized SVD) for computing just 456 singular values out of a (4.5M x 850) size matrix. The input matrix represents a CFD transient simulation of air moving past a cylinder. This application used dislib-0.9.0

Name: SparseLU Contact Person: support-compss@bsc.es Access Level: public License Agreement: Apache2 Platform: COMPSs

Description

The Sparse LU application computes an LU matrix factorization on a sparse blocked matrix. The matrix size (number of blocks) and the block size are parameters of the application.

As the algorithm progresses, the area of the matrix that is accessed is smaller; concretely, at each iteration, the 0th row and column of the current matrix are discarded. ...

COMPSs Matrix Multiplication, out-of-core using files. Hypermatrix size used 2x2 blocks (MSIZE=2), block size used 2x2 elements (BSIZE=2)

Monte Carlo Pi Estimation Program Description

This program is a Monte Carlo simulation designed to estimate the value of Pi using PyCOMPSs.

Tasks in the Program

1. Count Points in Circle Task (count_points_in_circle):

• Generates random points within a square with side length 1.
• Counts points falling within the inscribed circle (x^2 + y^2 <= 1).
• Input: Number of points to generate (num_points)
• Output: Tuple containing count of points within the circle and list of generated ...

Name: Matrix multiplication with Files, reproducibility example, without data persistence Contact Person: support-compss@bsc.es 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 ...

Name: Matrix multiplication with Files, reproducibility example Contact Person: support-compss@bsc.es 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 ...

Name: Incrementation and Fibonacci Access Level: public License Agreement: Apache2 Platform: COMPSs

Description

Brief Overview: Demonstrates COMPSs task parallelism with increment and Fibonacci computations. Helps to understand COMPSs.

Detailed Description:

1. Performs multiple increments of input values in parallel using COMPSs.
2. Concurrently calculates Fibonacci numbers using recursive COMPSs tasks.
3. Demonstrates task synchronization via compss_wait_on.

Execution

...