How to Install and Uninstall ocaml-parmap Package on openSUSE Leap
Last updated: November 23,2024
1. Install "ocaml-parmap" package
This is a short guide on how to install ocaml-parmap on openSUSE Leap
$
sudo zypper refresh
Copied
$
sudo zypper install
ocaml-parmap
Copied
2. Uninstall "ocaml-parmap" package
Please follow the steps below to uninstall ocaml-parmap on openSUSE Leap:
$
sudo zypper remove
ocaml-parmap
Copied
3. Information about the ocaml-parmap package on openSUSE Leap
Information for package ocaml-parmap:
-------------------------------------
Repository : Main Repository
Name : ocaml-parmap
Version : 20200124.526acc4-1.18
Arch : x86_64
Vendor : SUSE LLC
Installed Size : 25.8 KiB
Installed : No
Status : not installed
Source package : ocaml-parmap-20200124.526acc4-1.18.src
Upstream URL : http://rdicosmo.github.io/parmap/
Summary : Multicore architecture exploitation for OCaml programs with minimal modifications
Description :
If you want to use your many cores to accelerate an operation
which happens to be a map, fold or map/fold (map-reduce), just use
Parmap's parmap, parfold and parmapfold primitives in place of the
standard List.map and friends; you can specify the number of
subprocesses to use with the optional parameter ncores, and the
size of granularity of the parallel computation with the optional
parameter chunksize.
-------------------------------------
Repository : Main Repository
Name : ocaml-parmap
Version : 20200124.526acc4-1.18
Arch : x86_64
Vendor : SUSE LLC
Installed Size : 25.8 KiB
Installed : No
Status : not installed
Source package : ocaml-parmap-20200124.526acc4-1.18.src
Upstream URL : http://rdicosmo.github.io/parmap/
Summary : Multicore architecture exploitation for OCaml programs with minimal modifications
Description :
If you want to use your many cores to accelerate an operation
which happens to be a map, fold or map/fold (map-reduce), just use
Parmap's parmap, parfold and parmapfold primitives in place of the
standard List.map and friends; you can specify the number of
subprocesses to use with the optional parameter ncores, and the
size of granularity of the parallel computation with the optional
parameter chunksize.