science Software for Scientists and Engineers This project provides software for engineering and natural science. http://en.opensuse.org/Portal:Science If you like to help to maintain the repository, please contact the respective maintainer: http://en.opensuse.org/openSUSE:Science_team For electrical engineering see electronics project: https://build.opensuse.org/project/show/electronics https://download.opensuse.org/repositories/science/openSUSE_Factory_PowerPC/ openSUSE:Factory:PowerPC openSUSE Factory PowerPC This is a project clone to build entire openSUSE:Factory for the PowerPC (PPC) architecture https://download.opensuse.org/repositories/openSUSE:/Factory:/PowerPC/standard/ openSUSE:Factory The next openSUSE distribution Any user who wishes to have the newest packages that include, but are not limited to, the Linux kernel, SAMBA, git, desktops, office applications and many other packages, will want Tumbleweed. Tumbleweed appeals to Power Users, Software Developers and openSUSE Contributors. If you require the latest software stacks and Integrated Development Environment or need a stable platform closest to bleeding edge Linux, Tumbleweed is the best choice for you. Staging dashboard is located at: https://build.opensuse.org/staging_workflows/openSUSE:Factory List of known devel projects: https://build.opensuse.org/package/view_file/openSUSE:Factory:Staging/dashboard/devel_projects Have a look at http://en.opensuse.org/Portal:Factory for more details. https://download.opensuse.org/repositories/openSUSE:/Factory/ports/ elpa A massively parallel eigenvector solver A new efficient distributed parallel direct eigenvalue solver for symmetric matrices. It contains both an improved one-step ScaLAPACK type solver (ELPA1) and the two-step solver ELPA2. ELPA uses the same matrix layout as ScaLAPACK. The actual parallel linear algebra routines are completely rewritten. ELPA1 implements the same linear algebra as traditional solutions (reduction to tridiagonal form by Householder transforms, divide & conquer solution, eigenvector backtransform). In ELPA2, the reduction to tridiagonal form and the corresponding backtransform are replaced by a two-step version, giving an additional significant performance improvement. ELPA has demonstrated good scalability for large matrices on up to 294.000 cores of a BlueGene/P system.