PyCOMPSs Matrix Multiplication, out-of-core, using files
Version 1

Workflow Type: COMPSs

Name: Matrix multiplication with Files
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 rows in A are multiplied with corresponding columns in B.

In this implementation, A and B are square matrices (same number of rows and columns), and so it is the result matrix C. Each matrix is divided in N blocks of M doubles. The multiplication of two blocks is done by a multiply task method with a simple three-nested-loop implementation. When executed with COMPSs, the main program generates N^3^ tasks arranged as N^2^ chains of N tasks in the dependency graph.

Execution instructions

Usage:

runcompss --lang=python src/matmul_files.py numberOfBlocks blockSize

where:

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

Execution Examples

runcompss --lang=python src/matmul_files.py 4 4
runcompss src/matmul_files.py 4 4
python -m pycompss src/matmul_files.py 4 4

Build

No build is required

Click and drag the diagram to pan, double click or use the controls to zoom.

Version History

Version 1 (earliest) Created 30th May 2023 at 09:55 by Raül Sirvent

No revision comments

Frozen Version-1 a0f749a
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). PyCOMPSs Matrix Multiplication, out-of-core, using files. WorkflowHub. https://doi.org/10.48546/WORKFLOWHUB.WORKFLOW.485.1
Activity

Views: 2095   Downloads: 230

Created: 30th May 2023 at 09:55

Last updated: 26th Oct 2023 at 10:42

help Attributions

None

Total size: 4.26 MB
Powered by
(v.1.16.0-main)
Copyright © 2008 - 2024 The University of Manchester and HITS gGmbH