conda-forge / scalapack-feedstock

A conda-smithy repository for scalapack.

About scalapack

Home: http://www.netlib.org/scalapack/

Package license: BSD-2-Clause

Feedstock license: BSD-3-Clause

Summary: ScaLAPACK is a library of high-performance linear algebra routines for parallel distributed memory machines

ScaLAPACK is 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.

Current build status

Azure

Variant Status linux_64_mpimpich linux_64_mpiopenmpi linux_aarch64_mpimpich linux_aarch64_mpiopenmpi linux_ppc64le_mpimpich linux_ppc64le_mpiopenmpi osx_64_mpimpich osx_64_mpiopenmpi osx_arm64_mpimpich osx_arm64_mpiopenmpi

Current release info

Name	Downloads	Version	Platforms

Installing scalapack

Installing scalapack from the conda-forge channel can be achieved by adding conda-forge to your channels with:

conda config --add channels conda-forge
conda config --set channel_priority strict

Once the conda-forge channel has been enabled, scalapack can be installed with:

conda install scalapack

It is possible to list all of the versions of scalapack available on your platform with:

conda search scalapack --channel conda-forge

About conda-forge

conda-forge is a community-led conda channel of installable packages. In order to provide high-quality builds, the process has been automated into the conda-forge GitHub organization. The conda-forge organization contains one repository for each of the installable packages. Such a repository is known as a feedstock.

A feedstock is made up of a conda recipe (the instructions on what and how to build the package) and the necessary configurations for automatic building using freely available continuous integration services. Thanks to the awesome service provided by CircleCI, AppVeyor and TravisCI it is possible to build and upload installable packages to the conda-forge Anaconda-Cloud channel for Linux, Windows and OSX respectively.

To manage the continuous integration and simplify feedstock maintenance conda-smithy has been developed. Using the conda-forge.yml within this repository, it is possible to re-render all of this feedstock's supporting files (e.g. the CI configuration files) with conda smithy rerender.

For more information please check the conda-forge documentation.

Terminology

feedstock - the conda recipe (raw material), supporting scripts and CI configuration.

conda-smithy - the tool which helps orchestrate the feedstock. Its primary use is in the construction of the CI .yml files and simplify the management of many feedstocks.

conda-forge - the place where the feedstock and smithy live and work to produce the finished article (built conda distributions)

Updating scalapack-feedstock

If you would like to improve the scalapack recipe or build a new package version, please fork this repository and submit a PR. Upon submission, your changes will be run on the appropriate platforms to give the reviewer an opportunity to confirm that the changes result in a successful build. Once merged, the recipe will be re-built and uploaded automatically to the conda-forge channel, whereupon the built conda packages will be available for everybody to install and use from the conda-forge channel. Note that all branches in the conda-forge/scalapack-feedstock are immediately built and any created packages are uploaded, so PRs should be based on branches in forks and branches in the main repository should only be used to build distinct package versions.

In order to produce a uniquely identifiable distribution:

• If the version of a package is not being increased, please add or increase the build/number.
• If the version of a package is being increased, please remember to return the build/number back to 0.

Feedstock Maintainers

• @SylvainCorlay
• @dalcinl
• @davidbrochart
• @minrk
• @traversaro

scalapack-feedstock's Issues

macOS builds are using Accelerate's BLAS and LAPACK

Solution to issue cannot be found in the documentation.

• I checked the documentation.

Issue

I just noticed from the log in that the macOS builds are using the Accelerate's BLAS and LAPACK instead of the netlib one installed by conda-forge:

2022-03-08T13:04:42.6762060Z -- CHECKING BLAS AND LAPACK LIBRARIES
2022-03-08T13:04:42.6762060Z -- --> Searching for optimized LAPACK and BLAS libraries on your machine.
2022-03-08T13:04:42.6812850Z -- Looking for Fortran sgemm
2022-03-08T13:04:43.1343170Z -- Looking for Fortran sgemm - not found
2022-03-08T13:04:43.1443540Z -- Looking for pthread.h
2022-03-08T13:04:43.6723120Z -- Looking for pthread.h - found
2022-03-08T13:04:43.6727680Z -- Performing Test CMAKE_HAVE_LIBC_PTHREAD
2022-03-08T13:04:44.0746510Z -- Performing Test CMAKE_HAVE_LIBC_PTHREAD - Success
2022-03-08T13:04:44.0762630Z -- Found Threads: TRUE  
2022-03-08T13:04:44.2117820Z -- Looking for Fortran dgemm
2022-03-08T13:04:44.6135390Z -- Looking for Fortran dgemm - found
2022-03-08T13:04:44.6142540Z -- Found BLAS: /Applications/Xcode_12.4.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX10.9.sdk/System/Library/Frameworks/Accelerate.framework  
2022-03-08T13:04:44.6184500Z -- Looking for Fortran cheev
2022-03-08T13:04:45.0078400Z -- Looking for Fortran cheev - found
2022-03-08T13:04:45.0086180Z -- Found LAPACK: /Applications/Xcode_12.4.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX10.9.sdk/System/Library/Frameworks/Accelerate.framework;-lm;-ldl  
2022-03-08T13:04:45.0090250Z -- BLAS library: /Applications/Xcode_12.4.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX10.9.sdk/System/Library/Frameworks/Accelerate.framework
2022-03-08T13:04:45.0093430Z -- LAPACK library: /Applications/Xcode_12.4.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX10.9.sdk/System/Library/Frameworks/Accelerate.framework;-lm;-ldl

The same snippet of code on Linux is:

2022-03-08T13:00:13.6471881Z -- CHECKING BLAS AND LAPACK LIBRARIES
2022-03-08T13:00:13.6473203Z -- --> Searching for optimized LAPACK and BLAS libraries on your machine.
2022-03-08T13:00:13.6534081Z -- Looking for Fortran sgemm
2022-03-08T13:00:13.8492465Z -- Looking for Fortran sgemm - not found
2022-03-08T13:00:13.8567493Z -- Looking for pthread.h
2022-03-08T13:00:14.0346444Z -- Looking for pthread.h - found
2022-03-08T13:00:14.0355890Z -- Performing Test CMAKE_HAVE_LIBC_PTHREAD
2022-03-08T13:00:14.2113835Z -- Performing Test CMAKE_HAVE_LIBC_PTHREAD - Failed
2022-03-08T13:00:14.2123315Z -- Looking for pthread_create in pthreads
2022-03-08T13:00:14.3582750Z -- Looking for pthread_create in pthreads - not found
2022-03-08T13:00:14.3583920Z -- Looking for pthread_create in pthread
2022-03-08T13:00:14.5219985Z -- Looking for pthread_create in pthread - found
2022-03-08T13:00:14.5239629Z -- Found Threads: TRUE  
2022-03-08T13:00:14.6637814Z -- Looking for Fortran sgemm
2022-03-08T13:00:14.8489123Z -- Looking for Fortran sgemm - found
2022-03-08T13:00:14.8502298Z -- Found BLAS: $PREFIX/lib/libblas.so  
2022-03-08T13:00:14.8540319Z -- Looking for Fortran cheev
2022-03-08T13:00:15.0470594Z -- Looking for Fortran cheev - not found
2022-03-08T13:00:15.0806299Z -- Looking for Fortran cheev
2022-03-08T13:00:15.2309094Z -- Looking for Fortran cheev - not found
2022-03-08T13:00:15.2314019Z -- Looking for Fortran cheev
2022-03-08T13:00:15.4225847Z -- Looking for Fortran cheev - found
2022-03-08T13:00:15.4234593Z -- Found LAPACK: $PREFIX/lib/liblapack.so;$PREFIX/lib/libblas.so  
2022-03-08T13:00:15.4241751Z -- BLAS library: $PREFIX/lib/libblas.so
2022-03-08T13:00:15.4247988Z -- LAPACK library: $PREFIX/lib/liblapack.so;$PREFIX/lib/libblas.so

Installed packages

Not relevant.

Environment info

Not relevant.