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. | ||
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==Usage Examples== | ==Usage Examples== | ||
Latest revision as of 10:38, 17 November 2022
Contents
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)