linux-support-6.8.9
Support files for Linux 6.8
This package provides support files for the Linux kernel build, e.g.
scripts to handle ABI information and for generation of build system meta
data.
python3-virt-firmware
Tools for manipulating edk2 (ovmf/qemu-efi) firmware images
This is a collection of tools for edk2 firmware images. They support
decoding and printing the content of firmware volumes. Variable stores
(e.g. OVMF_VARS.fd) can be modified, for example to enroll secure boot
certificates. Tools included:
libpetsc-complex3.20
Shared libraries for version 3.20 of PETSc with Complex Numbers
PETSc is the "Portable Extensible Toolkit for Scientific
Computation", a suite of data structures and routines for the
scalable (parallel) solution of scientific applications modeled by
partial differential equations. It employs the MPI standard for all
message-passing communication. Several sample scientific
applications, as well as various papers and talks, demonstrate the
features of the PETSc libraries.
libpetsc64-complex3.20
Shared libraries for version 3.20 of 64-bit PETSc with Complex Numbers
PETSc is the "Portable Extensible Toolkit for Scientific
Computation", a suite of data structures and routines for the
scalable (parallel) solution of scientific applications modeled by
partial differential equations. It employs the MPI standard for all
message-passing communication. Several sample scientific
applications, as well as various papers and talks, demonstrate the
features of the PETSc libraries.
pandoc-filter-diagram
Pandoc filter to render diagrams in Markdown code sections
This Lua filter is used to create figures from code blocks:
images are generated from the code
with the help of external programs.
The filter processes diagram code
for Asymptote, Cetz, Graphviz, Mermaid, Pikchr, PlantUML, and TikZ.
libslepc-complex3.20
Scalable Library for Eigenvalue Problem Computations
SLEPc is a software library for the solution of large scale sparse eigenvalue
problems on parallel computers. It is an extension of PETSc and can be used
for either standard or generalized eigenproblems, with real or complex
arithmetic. It can also be used for computing a partial SVD of a large,
sparse, rectangular matrix.