eFlows4HPC project aims at providing workflow software stack and an additional set of services to enable the integration of HPC simulations and modelling with big data analytics and machine learning in scientific and industrial applications. The project is also developing the HPC Workflows as a Service (HPCWaaS) methodology that aims at providing tools to simplify the development, deployment, execution and reuse of workflows. The project demonstrates its advances through three application Pillars ...
Web page: https://eflows4hpc.eu
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 ...
Organisms: Not specified
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.
Date Published: 1st Nov 2022
Publication Type: Proceedings
Citation: 2022 IEEE/ACM Workshop on Workflows in Support of Large-Scale Science (WORKS),pp.1-9,IEEE
Name: K-means Contact Person: email@example.com Access Level: Public License Agreement: Apache2 Platform: COMPSs
K-means clustering is a method of cluster analysis that aims to partition ''n'' points into ''k'' clusters in which each point belongs to the cluster with the nearest mean. It follows an iterative refinement strategy to find the centers of natural clusters in the data.
When executed with COMPSs, K-means first generates the input points by means of ...
Name: SparseLU Contact Person: firstname.lastname@example.org Access Level: public License Agreement: Apache2 Platform: COMPSs
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. ...
Name: Matrix Multiplication Contact Person: email@example.com Access Level: public License Agreement: Apache2 Platform: COMPSs
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 ...