Java COMPSs LU Factorization for Sparse Matrices
Version 1

Workflow Type: COMPSs
Stable

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. On the other hand, due to the sparseness of the matrix, some of its blocks might not be allocated and, therefore, no work is generated for them.

When executed with COMPSs, Sparse LU produces several types of task with different granularity and numerous dependencies between them.

Versions

There are three versions of Sparse LU, depending on the data types used to store the blocks.

Version 1

''files'', where the matrix blocks are stored in files.

Version 2

''objects'', where the matrix blocks are represented by objects.

Version 3

''arrays'', where the matrix blocks are stored in arrays.

Execution instructions

Usage:

runcompss sparseLU.files.SparseLU numberOfBlocks blockSize
runcompss sparseLU.objects.SparseLU numberOfBlocks blockSize
runcompss sparseLU.arrays.SparseLU numberOfBlocks blockSize

where:

  • numberOfBlocks: Number of blocks inside each matrix
  • blockSize: Size of each block

Execution Example

runcompss sparseLU.objects.SparseLU 16 4 
runcompss sparseLU.files.SparseLU 16 4
runcompss sparseLU.arrays.SparseLU 16 4 

Build

Option 1: Native java

cd application_sources/; javac src/main/java/sparseLU/*/*.java
cd src/main/java/; jar cf sparseLU.jar sparseLU/
cd ../../../; mv src/main/java/sparseLU.jar jar/

Option 2: Maven

cd application_sources/
mvn clean package

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Version History

Version 1 (earliest) Created 23rd Jun 2023 at 15:03 by Raül Sirvent

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Frozen Version-1 a378b09
help Creators and Submitter
Creator
Additional credit

The Workflows and Distributed Computing Team (https://www.bsc.es/discover-bsc/organisation/scientific-structure/workflows-and-distributed-computing)

Submitter
Citation
Sirvent, R. (2023). Java COMPSs LU Factorization for Sparse Matrices. WorkflowHub. https://doi.org/10.48546/WORKFLOWHUB.WORKFLOW.515.1
Activity

Views: 691

Created: 23rd Jun 2023 at 15:03

Last updated: 30th Oct 2023 at 14:29

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