Difference between revisions of "Applications/Scalapack"
From HPC
m |
m |
||
| Line 16: | Line 16: | ||
==Usage Examples== | ==Usage Examples== | ||
| − | === | + | ===Interactive=== |
| + | As this is a library only the module add is shown and would be used with another application or binary. | ||
<pre style="background-color: #000000; color: white; border: 2px solid black; font-family: monospace, sans-serif;"> | <pre style="background-color: #000000; color: white; border: 2px solid black; font-family: monospace, sans-serif;"> | ||
| Line 28: | Line 29: | ||
</pre> | </pre> | ||
| + | |||
| + | ===Batch Script=== | ||
| + | |||
| + | As this is a library only the module add is shown and would be used with another application or binary. | ||
| + | |||
| + | <pre style="background-color: #000000; color: white; border: 2px solid black; font-family: monospace, sans-serif;"> | ||
| + | |||
| + | #!/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) | ||
| + | |||
| + | </pre> | ||
| + | |||
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)