Difference between revisions of "Applications/Scalapack"

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*Module: scalapack/intel/intelmpi/2.0.2
 
*Module: scalapack/intel/intelmpi/2.0.2
 
*Licence:  modified BSD license
 
*Licence:  modified BSD license
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===Description===
 
===Description===
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* ScaLAPACK is designed for heterogeneous computing and is portable on any computer that supports MPI.
 
* ScaLAPACK is designed for heterogeneous computing and is portable on any computer that supports MPI.
 
* ScaLAPACK depends on PBLAS operations in the same way LAPACK depends on BLAS.
 
* ScaLAPACK depends on PBLAS operations in the same way LAPACK depends on BLAS.
 
  
 
==Usage Examples==
 
==Usage Examples==

Latest revision as of 10:38, 17 November 2022

Application Details

  • Description: A library of high-performance linear algebra routines for parallel distributed memory machines. ScaLAPACK solves dense and banded linear systems, least squares problems, eigenvalue problems, and singular value problems.
  • Version: 2.0.2
  • Module: scalapack/intel/intelmpi/2.0.2
  • Licence: modified BSD license


Description

The ScaLAPACK (or Scalable LAPACK) library includes a subset of LAPACK routines redesigned for distributed memory MIMD parallel computers. It is currently written in a Single-Program-Multiple-Data style using explicit message passing for interprocessor communication. It assumes matrices are laid out in a two-dimensional block cyclic decomposition.

  • ScaLAPACK is designed for heterogeneous computing and is portable on any computer that supports MPI.
  • ScaLAPACK depends on PBLAS operations in the same way LAPACK depends on BLAS.

Usage Examples

Interactive

As this is a library only the module add is shown and would be used with another application or binary.


[@login01 ~]$ interactive
salloc: Granted job allocation 3619715
Job ID 3619715 connecting to c081, please wait...
c081.vc-main
[pysdlb@c081 ~]$ module add scalapack/intel/intelmpi/2.0.2

Batch Script

As this is a library only the module add is shown and would be used with another application or binary.


#!/bin/bash
#SBATCH -J jobname                # Job name, you can change it to whatever you want
#SBATCH -n 1                      # Number of cores 
#SBATCH -o %N.%j.out              # Standard output will be written here
#SBATCH -e %N.%j.err              # Standard error will be written here
#SBATCH -p compute                # Slurm partition, where you want the job to be queued 
#SBATCH -t=20:00:00               # Run for 20 hours
#SBATCH --mail-user=your email    # Mail to email address when finished


module purge
module add scalapack/intel/intelmpi/2.0.2

(User-provided application here)


Next Steps





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