# packages

pkgId: 0133efb93cf5c744ebbcc5e71ece7957cb6a688bd0e0749225ab247a2ef6a216
name: scls-alderlake-intel-intelmpi-cuda-armadillo
arch: x86_64
version: 12.8.0
epoch: 0
release: 2.el9
summary: Fast C++ matrix library with syntax similar to MATLAB and Octave
url: http://arma.sourceforge.net/
rpm_license: ASL 2.0
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-alderlake-intel-intelmpi-cuda-armadillo-12.8.0-2.el9.src.rpm
location_href: scls-alderlake-intel-intelmpi-cuda-armadillo-12.8.0-2.el9.x86_64.rpm
checksum_type: sha256
description:
  Armadillo is a C++ linear algebra library (matrix maths)
  aiming towards a good balance between speed and ease of use.
  Integer, floating point and complex numbers are supported,
  as well as a subset of trigonometric and statistics functions.
  Various matrix decompositions are provided through optional
  integration with LAPACK and ATLAS libraries.
  A delayed evaluation approach is employed (during compile time)
  to combine several operations into one and reduce (or eliminate)
  the need for temporaries. This is accomplished through recursive
  templates and template meta-programming.
  This library is useful if C++ has been decided as the language
  of choice (due to speed and/or integration capabilities), rather
  than another language like Matlab or Octave.


pkgId: 20ccc7fd4de48ce08f2da418e4b6056463ab2ee98e20aca0ac87009d503c7171
name: scls-alderlake-intel-intelmpi-cuda-arpack
arch: x86_64
version: 3.9.1
epoch: 0
release: 1.el9
summary: Fortran 77 subroutines for solving large scale eigenvalue problems
url: https://github.com/opencollab/arpack-ng
rpm_license: BSD
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-alderlake-intel-intelmpi-cuda-arpack-3.9.1-1.el9.src.rpm
location_href: scls-alderlake-intel-intelmpi-cuda-arpack-3.9.1-1.el9.x86_64.rpm
checksum_type: sha256
description:
  ARPACK is a collection of Fortran 77 subroutines designed to solve large
  scale eigenvalue problems.

  The package is designed to compute a few eigenvalues and corresponding
  eigenvectors of a general n by n matrix A. It is most appropriate for
  large sparse or structured matrices A where structured means that a
  matrix-vector product w <- Av requires order n rather than the usual
  order n**2 floating point operations. This software is based upon an
  algorithmic variant of the Arnoldi process called the Implicitly
  Restarted Arnoldi Method (IRAM).


pkgId: f8a40c2e3cfc75583431db0e4fad6ba60292e9d5198a6e790fc2369ebe432a14
name: scls-alderlake-intel-intelmpi-cuda-blaspp
arch: x86_64
version: 2023.11.05
epoch: 0
release: 1.el9
summary: A C++ wrapper around CPU and GPU BLAS
url: https://icl.utk.edu/slate/
rpm_license: BSD
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-alderlake-intel-intelmpi-cuda-blaspp-2023.11.05-1.el9.src.rpm
location_href: scls-alderlake-intel-intelmpi-cuda-blaspp-2023.11.05-1.el9.x86_64.rpm
checksum_type: sha256
description:
  The Basic Linear Algebra Subprograms (BLAS) have been around for many
  decades and serve as the de facto standard for performance-portable and
  numerically robust implementation of essential linear algebra
  functionality. Originally, they were written in Fortran, and later
  furnished with a C API (CBLAS).

  The objective of BLAS++ is to provide a convenient, performance
  oriented API for development in the C++ language, that,
  for the most part, preserves established conventions, while, at the
  same time, takes advantages of modern C++ features, such as:
  namespaces, templates, exceptions, etc.

  BLAS++ is part of the SLATE project
  (Software for Linear Algebra Targeting Exascale), which is funded by
  the Department of Energy as part of its Exascale Computing Initiative
  (ECP). Closely related to BLAS++ is the LAPACK++ project,
  which provides a C++ API for LAPACK.


pkgId: fcc755cdea6b1ae2c8d9e1524808ee6c128e11d80a70c72fbefb636e7da9458f
name: scls-alderlake-intel-intelmpi-cuda-blaze
arch: x86_64
version: 3.8.2
epoch: 0
release: 1.el9
summary: A high-performance C++ math library for dense and sparse arithmetic
url: https://bitbucket.org/blaze-lib/blaze
rpm_license: BSD
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-alderlake-intel-intelmpi-cuda-blaze-3.8.2-1.el9.src.rpm
location_href: scls-alderlake-intel-intelmpi-cuda-blaze-3.8.2-1.el9.x86_64.rpm
checksum_type: sha256
description:
  Blaze is an open-source, high-performance C++ math library for dense and \
  sparse arithmetic. With its state-of-the-art Smart Expression Template \
  implementation Blaze combines the elegance and ease of use of a \
  domain-specific language with HPC-grade performance, making it one of \
  the most intuitive and fastest C++ math libraries available. \


pkgId: 4ead0f1cee70850475b90c7da469c7c9e48809fafee4ad0b481b82f5aeb12d30
name: scls-alderlake-intel-intelmpi-cuda-butterflypack
arch: x86_64
version: 2.4.0
epoch: 0
release: 1.el9
summary: rapid solving of large-scale dense linear systems
url: https://github.com/liuyangzhuan/ButterflyPACK
rpm_license: BSD-3-Clause
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-alderlake-intel-intelmpi-cuda-butterflypack-2.4.0-1.el9.src.rpm
location_href: scls-alderlake-intel-intelmpi-cuda-butterflypack-2.4.0-1.el9.x86_64.rpm
checksum_type: sha256
description:
  ButterflyPACK is a mathematical software for rapidly solving large-scale dense linear systems that exhibit off-diagonal rank-deficiency. These systems arise frequently from boundary element methods, or factorization phases in finite-difference/finite-element methods. ButterflyPACK relies on low-rank or butterfly formats under Hierarchical matrix, HODLR or other hierarchically nested frameworks to compress, factor and solve the linear system in quasi-linear time. The computationally most intensive phase, factorization, is accelerated via randomized linear algebras. The butterfly format, originally inspired by the butterfly data flow in fast Fourier Transform, is a linear algebra tool well-suited for compressing matrices arising from high-frequency wave equations or highly oscillatory integral operators. ButterflyPACK also provides preconditioned TFQMR iterative solvers.

  ButterflyPACK is written in Fortran 2003, it also has C++ interfaces. ButterflyPACK supports hybrid MPI/OpenMP programming models. In addition, ButterflyPACK can be readily invoked from the software STRUMPACK for solving dense and sparse linear systems.


pkgId: 66c15e22acc9bd9a87011939181541d13e8378074c055e05301fe3a8771ac57c
name: scls-alderlake-intel-intelmpi-cuda-cmake
arch: x86_64
version: 3.28.3
epoch: 0
release: 2.el9
summary: Cross-platform make system
url: http://www.cmake.org
rpm_license: BSD-3-Clause AND MIT-open-group AND Zlib AND Apache-2.0
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-alderlake-intel-intelmpi-cuda-cmake-3.28.3-2.el9.src.rpm
location_href: scls-alderlake-intel-intelmpi-cuda-cmake-3.28.3-2.el9.x86_64.rpm
checksum_type: sha256
description:
  CMake is used to control the software compilation process using simple
  platform and compiler independent configuration files. CMake generates
  native makefiles and workspaces that can be used in the compiler
  environment of your choice. CMake is quite sophisticated: it is possible
  to support complex environments requiring system configuration, preprocessor
  generation, code generation, and template instantiation.


pkgId: d91d4637f015e0f0cb8838f5debf8ca1f7f2e1b3c4851c82a173f24b4ef94adc
name: scls-alderlake-intel-intelmpi-cuda-exodus
arch: x86_64
version: 2023.11.27
epoch: 0
release: 1.el9
summary: EXODUS is an advanced FE data file format
url: https://github.com/sandialabs/seacas
rpm_license: BSD-3-Clause
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-alderlake-intel-intelmpi-cuda-exodus-2023.11.27-1.el9.src.rpm
location_href: scls-alderlake-intel-intelmpi-cuda-exodus-2023.11.27-1.el9.x86_64.rpm
checksum_type: sha256
description:
  EXODUS is the successor of the widely used finite element (FE) data file format EXODUS (henceforth referred to as EXODUS I) developed by Mills-Curran and Flanagan. It continues the concept of a common database for multiple application codes (mesh generators, analysis codes, visualization software, etc.) rather than code-specific utilities, affording flexibility and robustness for both the application code developer and application code user. By using the EXODUS data model, a user inherits the flexibility of using a large array of application codes (including vendor-supplied codes) which access this common data file directly or via translators.

  The uses of the EXODUS data model include the following:

  	o Problem definition – mesh generation, specification of locations of boundary conditions and load application,
  	o specification of material types.
  	o Simulation – model input and results output.
  	o Visualization – model verification, results postprocessing, data interrogation, and analysis tracking.


pkgId: f1037f5481ce4560f850dd4a19b85c45309bc053ac4de5e81ced23a95a4e6a38
name: scls-alderlake-intel-intelmpi-cuda-gmp
arch: x86_64
version: 6.3.0
epoch: 0
release: 1.el9
summary: GNU arbitrary precision library
url: https://gmplib.org/
rpm_license: LGPLv3+ or GPLv2+
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-alderlake-intel-intelmpi-cuda-gmp-6.3.0-1.el9.src.rpm
location_href: scls-alderlake-intel-intelmpi-cuda-gmp-6.3.0-1.el9.x86_64.rpm
checksum_type: sha256
description:
  The gmp package contains GNU MP, a library for arbitrary precision
  arithmetic, signed integers operations, rational numbers and floating
  point numbers. GNU MP is designed for speed, for both small and very
  large operands. GNU MP is fast because it uses fullwords as the basic
  arithmetic type, it uses fast algorithms, it carefully optimizes
  assembly code for many CPUs' most common inner loops, and it generally
  emphasizes speed over simplicity/elegance in its operations.


pkgId: 151ba0268c4f3b21f48a42ff64ccd4be361d1d507f8e30c5e4c3cfca5264e826
name: scls-alderlake-intel-intelmpi-cuda-googletest
arch: x86_64
version: 1.14.0
epoch: 0
release: 1.el9
summary: GoogleTest - Google Testing and Mocking Framework
url: https://github.com/google/googletest
rpm_license: BSD-3-Clause
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-alderlake-intel-intelmpi-cuda-googletest-1.14.0-1.el9.src.rpm
location_href: scls-alderlake-intel-intelmpi-cuda-googletest-1.14.0-1.el9.x86_64.rpm
checksum_type: sha256
description:
  Googletest is a comprehensive testing framework for C++ designed to support test-driven development and Google's extensive internal test suites. It provides a rich set of assertions, user-defined assertions, death tests, and easy-to-use fixtures for writing both small and large test cases. Googletest is portable and can be used across diverse platforms. It encourages organized, expressive, and efficient testing practices, and integrates well with various build systems. This makes it suitable for both new and existing C++ projects looking to implement robust testing.


pkgId: b6f62a7edcc03145a920fd2ea030884c6db5c202b11e8b0e5031a5eb8fa21553
name: scls-alderlake-intel-intelmpi-cuda-gperftools
arch: x86_64
version: 2.15
epoch: 0
release: 1.el9
summary: Very fast malloc and performance analysis tools
url: https://github.com/gperftools/gperftools
rpm_license: BSD
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-alderlake-intel-intelmpi-cuda-gperftools-2.15-1.el9.src.rpm
location_href: scls-alderlake-intel-intelmpi-cuda-gperftools-2.15-1.el9.x86_64.rpm
checksum_type: sha256
description:
  Perf Tools is a collection of performance analysis tools, including a
  high-performance multi-threaded malloc() implementation that works
  particularly well with threads and STL, a thread-friendly heap-checker,
  a heap profiler, and a cpu-profiler.

  This is a metapackage which pulls in all of the gperftools (and pprof)
  binaries, libraries, and development headers, so that you can use them.


pkgId: b30381aca0ecc72d322be69acb818be4486e35a54d5ad8bc7c9739118096b9e0
name: scls-alderlake-intel-intelmpi-cuda-hdf5
arch: x86_64
version: 1.14.3
epoch: 0
release: 1.el9
summary: A general purpose library and file format for storing scientific data
url: https://www.hdfgroup.org/solutions/hdf5
rpm_license: BSD
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-alderlake-intel-intelmpi-cuda-hdf5-1.14.3-1.el9.src.rpm
location_href: scls-alderlake-intel-intelmpi-cuda-hdf5-1.14.3-1.el9.x86_64.rpm
checksum_type: sha256
description:
  HDF5 is a general purpose library and file format for storing scientific data.
  HDF5 can store two primary objects: datasets and groups. A dataset is
  essentially a multidimensional array of data elements, and a group is a
  structure for organizing objects in an HDF5 file. Using these two basic
  objects, one can create and store almost any kind of scientific data
  structure, such as images, arrays of vectors, and structured and unstructured
  grids. You can also mix and match them in HDF5 files according to your needs.


pkgId: 476522b71981e8e1d115fd6f97dc25d07217cb32ebaeb4e3d13e7234bef5c74d
name: scls-alderlake-intel-intelmpi-cuda-hdf5-examples
arch: x86_64
version: 1.14.3
epoch: 0
release: 1.el9
summary: C-example files for HDF5
url: https://www.hdfgroup.org/solutions/hdf5
rpm_license: BSD
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-alderlake-intel-intelmpi-cuda-hdf5-1.14.3-1.el9.src.rpm
location_href: scls-alderlake-intel-intelmpi-cuda-hdf5-examples-1.14.3-1.el9.x86_64.rpm
checksum_type: sha256
description:
  This package contains example programs for the installed APIs and scripts to
  compile and run them.  Examples in the c and hl/c subdirectories are always
  installed, and those in fortran, hl/fortran, c++ and hl/c++ will be installed
  when fortran or c++ are enabled.

  Running the run-all-ex.sh script in this directory will run the scripts and in
  turn the examples in all the subdirectories where examples are installed.  The
  scripts can also be run individually.  The appropriate compile scripts in the
  bin directory for this install will be used by default to compile and link the
  example programs.  Note that h5redeploy must be run if these binaries are
  copied or extracted in a directory other than the one where they were initially
  installed.  Compile scripts from other locations can be used by setting an
  environment variable prefix to the path of the directory containing the bin
  directory with the compile scripts h5cc, h5fc, etc.  For example, export
  prefix=/opt/scls/alderlake-intel-intelmpi-cuda to use h5cc, h5fc, etc. in /opt/scls/alderlake-intel-intelmpi-cuda/bin.


pkgId: f928bbf7097eb6169834371259a949d78cb923fb2bdf92c243081f77969f6bcc
name: scls-alderlake-intel-intelmpi-cuda-hwloc
arch: x86_64
version: 2.10.0
epoch: 0
release: 1.el9
summary: Portable Hardware Locality
url: https://www-lb.open-mpi.org/software/hwloc/v2.10/
rpm_license: BSD
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-alderlake-intel-intelmpi-cuda-hwloc-2.10.0-1.el9.src.rpm
location_href: scls-alderlake-intel-intelmpi-cuda-hwloc-2.10.0-1.el9.x86_64.rpm
checksum_type: sha256
description:
  The Portable Hardware Locality (hwloc) software package provides a portable abstraction (across OS, versions, architectures, ...) of the hierarchical topology of modern architectures, including NUMA memory nodes (DRAM, HBM, non-volatile memory, CXL, etc.), sockets, shared caches, cores and simultaneous multithreading. It also gathers various system attributes such as cache and memory information as well as the locality of I/O devices such as network interfaces, InfiniBand HCAs or GPUs.

  hwloc primarily aims at helping applications with gathering information about increasingly complex parallel computing platforms so as to exploit them accordingly and efficiently. For instance, two tasks that tightly cooperate should probably be placed onto cores sharing a cache. However, two independent memory-intensive tasks should better be spread out onto different sockets so as to maximize their memory throughput. As described in this paper, OpenMP threads have to be placed according to their affinities and to the hardware characteristics. MPI implementations apply similar techniques while also adapting their communication strategies to the network locality as described in this paper or this one.

  hwloc may also help many applications just by providing a portable CPU and memory binding API and a reliable way to find out how many cores and/or hardware threads are available.


pkgId: 90ada57a06949f311ec485f7f8bd8211ca25c313f2efe506b45c0b5c4fd2b869
name: scls-alderlake-intel-intelmpi-cuda-lapackpp
arch: x86_64
version: 2023.11.05
epoch: 0
release: 1.el9
summary: C++ API for the Linear Algebra Package
url: https://icl.utk.edu/slate/
rpm_license: BSD
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-alderlake-intel-intelmpi-cuda-lapackpp-2023.11.05-1.el9.src.rpm
location_href: scls-alderlake-intel-intelmpi-cuda-lapackpp-2023.11.05-1.el9.x86_64.rpm
checksum_type: sha256
description:
  he Linear Algebra PACKage (LAPACK) is a standard software library for numerical linear algebra. It provides routines for solving systems of linear equations and linear least squares problems, eigenvalue problems, and singular value decomposition. It also includes routines to implement the associated matrix factorizations such as LU, QR, Cholesky, etc. LAPACK was originally written in FORTRAN 77, and moved to Fortran 90 in version 3.2 (2008). LAPACK provides routines for handling both real and complex matrices in both single and double precision.

  The objective of LAPACK++ is to provide a convenient, performance oriented API for development in the C++ language, that, for the most part, preserves established conventions, while, at the same time, takes advantages of modern C++ features, such as: namespaces, templates, exceptions, etc.


pkgId: 8d8ec15ef08636c9defa64a9da23b308d7d3042fdab73a9f72f080d59817c998
name: scls-alderlake-intel-intelmpi-cuda-libevent
arch: x86_64
version: 2.1.12
epoch: 0
release: 1.el9
summary: Abstract asynchronous event notification library
url: https://libevent.org/
rpm_license: BSD and ISC
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-alderlake-intel-intelmpi-cuda-libevent-2.1.12-1.el9.src.rpm
location_href: scls-alderlake-intel-intelmpi-cuda-libevent-2.1.12-1.el9.x86_64.rpm
checksum_type: sha256
description:
  The libevent API provides a mechanism to execute a callback function
  when a specific event occurs on a file descriptor or after a timeout
  has been reached. libevent is meant to replace the asynchronous event
  loop found in event driven network servers. An application just needs
  to call event_dispatch() and can then add or remove events dynamically
  without having to change the event loop.


pkgId: 48c58eaa4217d0db1262b9b41e947b9676475920133c3a25bf7d86981030d9be
name: scls-alderlake-intel-intelmpi-cuda-metis
arch: x86_64
version: 5.1.0
epoch: 0
release: 1.el9
summary: Serial Graph Partitioning and Fill-reducing Matrix Ordering
url: http://glaros.dtc.umn.edu/gkhome/views/metis
rpm_license: ASL 2.0 and BSD and LGPLv2+
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-alderlake-intel-intelmpi-cuda-metis-5.1.0-1.el9.src.rpm
location_href: scls-alderlake-intel-intelmpi-cuda-metis-5.1.0-1.el9.x86_64.rpm
checksum_type: sha256
description:
  METIS is a set of serial programs for partitioning graphs,
  partitioning finite element meshes, and producing fill reducing
  orderings for sparse matrices.
  The algorithms implemented in METIS are based on the multilevel
  recursive-bisection, multilevel k-way, and multi-constraint
  partitioning schemes developed in our lab.
  METIS is distributed with OpenMP support.


pkgId: ad7853e2a235861965dbaa620e6c6981ea2db0ed057a4ac3385fd5bd739f2046
name: scls-alderlake-intel-intelmpi-cuda-mpfr
arch: x86_64
version: 4.2.1
epoch: 0
release: 1.el9
summary: C library for multiple-precision floating-point computations
url: https://www.mpfr.org/
rpm_license: LGPL-3.0-or-later
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-alderlake-intel-intelmpi-cuda-mpfr-4.2.1-1.el9.src.rpm
location_href: scls-alderlake-intel-intelmpi-cuda-mpfr-4.2.1-1.el9.x86_64.rpm
checksum_type: sha256
description:
  The MPFR library is a C library for multiple-precision floating-point
  computations with "correct rounding". The MPFR is efficient and
  also has a well-defined semantics. It copies the good ideas from the
  ANSI/IEEE-754 standard for double-precision floating-point arithmetic
  (53-bit mantissa). MPFR is based on the GMP multiple-precision library.


pkgId: 8121d71d86782dd6897c0cb90a57f699405f52917c5154e1e404e59e907cdf0b
name: scls-alderlake-intel-intelmpi-cuda-mumps
arch: x86_64
version: 5.6.2
epoch: 0
release: 2.el9
summary: A MUltifrontal Massively Parallel sparse direct Solver
url: https://mumps-solver.org
rpm_license: CeCILL-C
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-alderlake-intel-intelmpi-cuda-mumps-5.6.2-2.el9.src.rpm
location_href: scls-alderlake-intel-intelmpi-cuda-mumps-5.6.2-2.el9.x86_64.rpm
checksum_type: sha256
description:
  MUMPS implements a direct solver for large sparse linear systems, with a
  particular focus on symmetric positive definite matrices.  It can
  operate on distributed matrices e.g. over a cluster.  It has Fortran and
  C interfaces, and can interface with ordering tools such as Scotch.


pkgId: 7148f15966fc2ea98b9cf123f31f90a44c9402644f6fc76700a95290e71215f7
name: scls-alderlake-intel-intelmpi-cuda-netcdf
arch: x86_64
version: 4.9.2
epoch: 0
release: 1.el9
summary: Libraries for the Unidata network Common Data Form
url: http://www.unidata.ucar.edu/software/netcdf/
rpm_license: NetCDF
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-alderlake-intel-intelmpi-cuda-netcdf-4.9.2-1.el9.src.rpm
location_href: scls-alderlake-intel-intelmpi-cuda-netcdf-4.9.2-1.el9.x86_64.rpm
checksum_type: sha256
description:
  NetCDF (network Common Data Form) is an interface for array-oriented
  data access and a freely-distributed collection of software libraries
  for C, Fortran, C++, and perl that provides an implementation of the
  interface.  The NetCDF library also defines a machine-independent
  format for representing scientific data.  Together, the interface,
  library, and format support the creation, access, and sharing of
  scientific data. The NetCDF software was developed at the Unidata
  Program Center in Boulder, Colorado.

  NetCDF data is:

     o Self-Describing: A NetCDF file includes information about the
       data it contains.

     o Network-transparent:  A NetCDF file is represented in a form that
       can be accessed by computers with different ways of storing
       integers, characters, and floating-point numbers.

     o Direct-access:  A small subset of a large dataset may be accessed
       efficiently, without first reading through all the preceding
       data.

     o Appendable:  Data can be appended to a NetCDF dataset along one
       dimension without copying the dataset or redefining its
       structure. The structure of a NetCDF dataset can be changed,
       though this sometimes causes the dataset to be copied.

     o Sharable:  One writer and multiple readers may simultaneously
       access the same NetCDF file.


pkgId: 11ce98a589c5cac3cb5b13282c8f311148369a775e6a312844a63efc6e8555fc
name: scls-alderlake-intel-intelmpi-cuda-nlopt
arch: x86_64
version: 2.7.1
epoch: 0
release: 1.el9
summary: nonlinear local and global optimization
url: https://nlopt.readthedocs.io/
rpm_license: BSD and LGPLv2+ and MIT and Public Domain
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-alderlake-intel-intelmpi-cuda-nlopt-2.7.1-1.el9.src.rpm
location_href: scls-alderlake-intel-intelmpi-cuda-nlopt-2.7.1-1.el9.x86_64.rpm
checksum_type: sha256
description:
  NLopt is a library for nonlinear local and global optimization, for
  functions with and without gradient information.  It is designed as
  as simple, unified interface and packaging of several free/open-source
  nonlinear optimization libraries.

  It features bindings for GNU Guile, Octave and Python.  This build has
  been made with C++-support enabled.


pkgId: b1dee4bc0a776ca466e19e8d8539ba0444de27a0c0237b8c0ec50e64284a25eb
name: scls-alderlake-intel-intelmpi-cuda-parmetis
arch: x86_64
version: 4.0.3
epoch: 0
release: 1.el9
summary: ParMETIS - Parallel Graph Partitioning and Fill-reducing Matrix Ordering
url: http://glaros.dtc.umn.edu/gkhome/views/metis
rpm_license: ASL 2.0 and BSD and LGPLv2+
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-alderlake-intel-intelmpi-cuda-metis-5.1.0-1.el9.src.rpm
location_href: scls-alderlake-intel-intelmpi-cuda-parmetis-4.0.3-1.el9.x86_64.rpm
checksum_type: sha256
description:
  ParMETIS is an MPI-based parallel library that implements a variety of
  algorithms for partitioning unstructured graphs, meshes, and for
  computing fill-reducing orderings of sparse matrices. ParMETIS extends
  the functionality provided by METIS and includes routines that are
  especially suited for parallel AMR computations and large scale
  numerical simulations. The algorithms implemented in ParMETIS are
  based on the parallel multilevel k-way graph-partitioning, adaptive
  repartitioning, and parallel multi-constrained partitioning schemes
  developed at the Karzpis Lab, University of Minesota.


pkgId: d8cf9533c6681667765e43f8e736742ed66dd9512cf50a58f6ff074bcc6ebc0b
name: scls-alderlake-intel-intelmpi-cuda-petsc
arch: x86_64
version: 3.20.5
epoch: 0
release: 2.el9
summary: Portable Extensible Toolkit for Scientific Computation
url: https://petsc.org/
rpm_license: BSD-2-Clause
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-alderlake-intel-intelmpi-cuda-petsc-3.20.5-2.el9.src.rpm
location_href: scls-alderlake-intel-intelmpi-cuda-petsc-3.20.5-2.el9.x86_64.rpm
checksum_type: sha256
description:
  PETSc is a suite of data structures and routines for the scalable
  (parallel) solution of scientific applications modeled by partial
  differential equations.


pkgId: 7d9b99b682470bade24da240962c27f62f0208dd814d204d67c336c3851072c8
name: scls-alderlake-intel-intelmpi-cuda-scotch
arch: x86_64
version: 7.0.4
epoch: 0
release: 1.el9
summary: Graph, mesh and hypergraph partitioning library
url: https://www.labri.fr/perso/pelegrin/scotch/
rpm_license: CeCILL-C
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-alderlake-intel-intelmpi-cuda-scotch-7.0.4-1.el9.src.rpm
location_href: scls-alderlake-intel-intelmpi-cuda-scotch-7.0.4-1.el9.x86_64.rpm
checksum_type: sha256
description:
  Scotch is a software package for graph and mesh/hypergraph partitioning and
  sparse matrix ordering. The parallel scotch libraries are packaged in the


pkgId: d797fa8b901d553a89a1d92619acf394480ffdbdf7bf31b880dd25197293a676
name: scls-alderlake-intel-intelmpi-cuda-slate
arch: x86_64
version: 2023.11.05
epoch: 0
release: 1.el9
summary: Basic linear algebra for distributed memory systems
url: https://icl.bitbucket.io/slate/
rpm_license: BSD-3-Clause
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-alderlake-intel-intelmpi-cuda-slate-2023.11.05-1.el9.src.rpm
location_href: scls-alderlake-intel-intelmpi-cuda-slate-2023.11.05-1.el9.x86_64.rpm
checksum_type: sha256
description:
  Software for Linear Algebra Targeting Exascale (SLATE) is being developed as part of the Exascale Computing Project (ECP), which is a joint project of the U.S. Department of Energy's Office of Science and National Nuclear Security Administration (NNSA). SLATE will deliver fundamental dense linear algebra capabilities for current and upcoming distributed-memory systems, including GPU-accelerated systems as well as more traditional multi core-only systems.

  SLATE will provide coverage of existing LAPACK and ScaLAPACK functionality, including parallel implementations of Basic Linear Algebra Subroutines (BLAS), linear systems solvers, least squares solvers, and singular value and eigenvalue solvers. In this respect, SLATE will serve as a replacement for LAPACK and ScaLAPACK, which, after two decades of operation, cannot be adequately retrofitted for modern, GPU-accelerated architectures.

  SLATE is built on top of standards, such as MPI and OpenMP, and de facto-standard industry solutions such as NVIDIA CUDA and AMD HIP. SLATE also relies on high performance implementations of numerical kernels from vendor libraries, such as Intel MKL, IBM ESSL, NVIDIA cuBLAS, and AMD rocBLAS. SLATE interacts with these libraries through a layer of C++ APIs. This figure shows SLATE's position in the ECP software stack.


pkgId: 0ff37a76a02970910a044a3aaa13da1cb0fb80d512de31b01997880a2732369e
name: scls-alderlake-intel-intelmpi-cuda-strumpack
arch: x86_64
version: 7.1.0
epoch: 0
release: 1.el9
url: https://portal.nersc.gov/project/sparse/strumpack
rpm_license: BSD-3-Clause
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-alderlake-intel-intelmpi-cuda-strumpack-7.1.0-1.el9.src.rpm
location_href: scls-alderlake-intel-intelmpi-cuda-strumpack-7.1.0-1.el9.x86_64.rpm
checksum_type: sha256
summary:
  linear algebra routines and linear system solvers for sparse and for dense rank-structured linear systems.

description:
  STRUMPACK - STRUctured Matrix PACKage - is a software library providing linear algebra routines and linear system solvers for sparse and for dense rank-structured linear systems. Many large dense matrices are rank structured, meaning they exhibit some kind of low-rank property, for instance in hierarchically defined sub-blocks. In sparse direct solvers based on LU factorization, the LU factors can often also be approximated well using rank-structured matrix compression, leading to robust preconditioners. The sparse solver in STRUMPACK can also be used as an exact direct solver, in which case it functions similarly as for instance SuperLU or Superlu_Dist. The STRUMPACK sparse direct solver delivers good performance and distributed memory scalability and provides excellent CUDA support.


pkgId: 655a8940ce66fcaf00db3c276e480972d194df33140bdfa5456ddd44ce38ff2b
name: scls-alderlake-intel-intelmpi-cuda-suitesparse
arch: x86_64
version: 7.6.1
epoch: 0
release: 1.el9
summary: A collection of sparse matrix libraries
url: http://faculty.cse.tamu.edu/davis/suitesparse.html
rpm_license: (LGPLv2+ or BSD) and LGPLv2+ and GPLv2+
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-alderlake-intel-intelmpi-cuda-suitesparse-7.6.1-1.el9.src.rpm
location_href: scls-alderlake-intel-intelmpi-cuda-suitesparse-7.6.1-1.el9.x86_64.rpm
checksum_type: sha256
description:
  suitesparse is a collection of libraries for computations involving sparse
  matrices.  The package includes the following libraries:
    AMD                 approximate minimum degree ordering
    BTF                 permutation to block triangular form (beta)
    CAMD                constrained approximate minimum degree ordering
    COLAMD              column approximate minimum degree ordering
    CCOLAMD             constrained column approximate minimum degree ordering
    CHOLMOD             sparse Cholesky factorization
    CSparse             a concise sparse matrix package
    CXSparse            CSparse extended: complex matrix, int and long int support
    KLU                 sparse LU factorization, primarily for circuit simulation
    LDL                 a simple LDL factorization
    SQPR                a multithread, multifrontal, rank-revealing sparse QR
                        factorization method
    UMFPACK             sparse LU factorization
    SuiteSparse_config  configuration file for all the above packages.
    RBio                read/write files in Rutherford/Boeing format


pkgId: 1815d1c43d5be5432723ab7d0a63badf12918903dd9933b3ee762d50ca361699
name: scls-alderlake-intel-intelmpi-cuda-sundials
arch: x86_64
version: 6.7.0
epoch: 0
release: 1.el9
summary: Nonlinear and DIfferential/ALgebraic Equation Solvers
url: https://www.llnl.gov/casc/sundials/
rpm_license: BSD-3-Clause
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-alderlake-intel-intelmpi-cuda-sundials-6.7.0-1.el9.src.rpm
location_href: scls-alderlake-intel-intelmpi-cuda-sundials-6.7.0-1.el9.x86_64.rpm
checksum_type: sha256
description:
  SUNDIALS is a SUite of Non-linear DIfferential/ALgebraic equation Solvers
  for use in writing mathematical software.

  SUNDIALS was implemented with the goal of providing robust time integrators
  and nonlinear solvers that can easily be incorporated into existing simulation
  codes. The primary design goals were to require minimal information from the
  user, allow users to easily supply their own data structures underneath the
  solvers, and allow for easy incorporation of user-supplied linear solvers and
  preconditioners.


pkgId: fc8b0104c154e8d439e08aaa3b05fa7c2b2fdf5fbeece2e60b2dd2b01902c431
name: scls-alderlake-intel-intelmpi-cuda-superlu
arch: x86_64
version: 6.0.1
epoch: 0
release: 1.el9
summary: Subroutines to directly solve sparse linear systems
url: https://github.com/xiaoyeli/superlu
rpm_license: BSD
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-alderlake-intel-intelmpi-cuda-superlu-6.0.1-1.el9.src.rpm
location_href: scls-alderlake-intel-intelmpi-cuda-superlu-6.0.1-1.el9.x86_64.rpm
checksum_type: sha256
description:
  SuperLU contains a set of subroutines to solve a sparse linear system
  A*X=B. It uses Gaussian elimination with partial pivoting (GEPP).
  The columns of A may be preordered before factorization; the
  preordering for sparsity is completely separate from the factorization.


pkgId: 1759e9377abf1edb024af9f5317cb4329b7c6fdbc4ba584d84e59f89742eeb8c
name: scls-alderlake-intel-intelmpi-cuda-testsweeper
arch: x86_64
version: 2023.11.05
epoch: 0
release: 1.el9
summary: A C++ testing framework for parameter sweeps
url: https://github.com/icl-utk-edu/testsweeper
rpm_license: BSD
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-alderlake-intel-intelmpi-cuda-testsweeper-2023.11.05-1.el9.src.rpm
location_href: scls-alderlake-intel-intelmpi-cuda-testsweeper-2023.11.05-1.el9.x86_64.rpm
checksum_type: sha256
description:
  TestSweeper is a C++ testing framework for parameter sweeps.
  It handles parsing command line options, iterating over the test space,
  and printing results. This simplifies test functions by allowing them to
  concentrate on setting up and solving one problem at a time.

  TestSweeper is part of the SLATE project
  (Software for Linear Algebra Targeting Exascale), which is funded by
  the Department of Energy as part of its Exascale Computing Initiative
  (ECP).


pkgId: 14a6831b44006a968e322bf76bb953019f7d42f30fbf1d8e6e73991e509be460
name: scls-alderlake-intel-intelmpi-cuda-tinyxml2
arch: x86_64
version: 10.0.0
epoch: 0
release: 1.el9
summary: a simple, small, efficient, C++ XML parser
url: https://github.com/leethomason/tinyxml2
rpm_license: zlib
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-alderlake-intel-intelmpi-cuda-tinyxml2-10.0.0-1.el9.src.rpm
location_href: scls-alderlake-intel-intelmpi-cuda-tinyxml2-10.0.0-1.el9.x86_64.rpm
checksum_type: sha256
description:
  TinyXML-2 is a simple, small, efficient, C++ XML parser that can be
  easily integrated into other programs. It uses a Document Object Model
  (DOM), meaning the XML data is parsed into a C++ objects that can be
  browsed and manipulated, and then written to disk or another output stream.

  TinyXML-2 doesn't parse or use DTDs (Document Type Definitions) nor XSLs
  (eXtensible Stylesheet Language).

  TinyXML-2 uses a similar API to TinyXML-1, But the implementation of the
  parser was completely re-written to make it more appropriate for use in a
  game. It uses less memory, is faster, and uses far fewer memory allocations.


pkgId: c6deb6641c27f1a9b8f3e14b461f0a2639030c14f2e281d0cdcf4e2aeeebfd9c
name: scls-alderlake-intel-intelmpi-cuda-vtk
arch: x86_64
version: 9.3.0
epoch: 0
release: 1.el9
summary: The Visualization Toolkit - A high level 3D visualization library
url: https://vtk.org/
rpm_license: BSD-3-Clause
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-alderlake-intel-intelmpi-cuda-vtk-9.3.0-1.el9.src.rpm
location_href: scls-alderlake-intel-intelmpi-cuda-vtk-9.3.0-1.el9.x86_64.rpm
checksum_type: sha256
description:
  VTK is an open-source software system for image processing, 3D
  graphics, volume rendering and visualization. VTK includes many
  advanced algorithms (e.g., surface reconstruction, implicit modeling,
  decimation) and rendering techniques (e.g., hardware-accelerated
  volume rendering, LOD control).


pkgId: 7772018a2cfa866797fe720a32301e2d38321add935363e205fd3ca13e1c7a59
name: scls-alderlake-intel-intelmpi-cuda-zfp
arch: x86_64
version: 1.0.1
epoch: 0
release: 1.el9
summary: Library for compressed numerical arrays with high throughput R/W random access
url: https://computation.llnl.gov/projects/floating-point-compression
rpm_license: BSD-3-Clause
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-alderlake-intel-intelmpi-cuda-zfp-1.0.1-1.el9.src.rpm
location_href: scls-alderlake-intel-intelmpi-cuda-zfp-1.0.1-1.el9.x86_64.rpm
checksum_type: sha256
description:
  This is zfp, an open source C/C++ library for compressed numerical arrays
  that support high throughput read and write random access. zfp was written by
  Peter Lindstrom at Lawrence Livermore National Laboratory, and is loosely
  based on the algorithm described in the following paper:

  Peter Lindstrom
  "Fixed-Rate Compressed Floating-Point Arrays"
  IEEE Transactions on Visualization and Computer Graphics,
    20(12):2674-2683, December 2014
  doi:10.1109/TVCG.2014.2346458

  zfp was originally designed for floating-point data only, but has been
  extended to also support integer data, and could for instance be used to
  compress images and quantized volumetric data. To achieve high compression
  ratios, zfp uses lossy but optionally error-bounded compression. Although
  bit-for-bit lossless compression of floating-point data is not always
  possible, zfp is usually accurate to within machine epsilon in near-lossless
  mode.

  zfp works best for 2D and 3D arrays that exhibit spatial coherence, such as
  smooth fields from physics simulations, images, regularly sampled terrain
  surfaces, etc. Although zfp also provides a 1D array class that can be used
  for 1D signals such as audio, or even unstructured floating-point streams,
  the compression scheme has not been well optimized for this use case, and
  rate and quality may not be competitive with floating-point compressors
  designed specifically for 1D streams.


pkgId: b1d43e181943bb41c21b862c68dcd5ce349392755f8306405ba7b5c7efaa1e2c
name: scls-alderlake-intel-intelmpi-mkl-hdf5-examples
arch: x86_64
version: 1.14.3
epoch: 0
release: 1.el9
summary: C-example files for HDF5
url: https://www.hdfgroup.org/solutions/hdf5
rpm_license: BSD
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-alderlake-intel-intelmpi-mkl-hdf5-1.14.3-1.el9.src.rpm
location_href: scls-alderlake-intel-intelmpi-mkl-hdf5-examples-1.14.3-1.el9.x86_64.rpm
checksum_type: sha256
description:
  This package contains example programs for the installed APIs and scripts to
  compile and run them.  Examples in the c and hl/c subdirectories are always
  installed, and those in fortran, hl/fortran, c++ and hl/c++ will be installed
  when fortran or c++ are enabled.

  Running the run-all-ex.sh script in this directory will run the scripts and in
  turn the examples in all the subdirectories where examples are installed.  The
  scripts can also be run individually.  The appropriate compile scripts in the
  bin directory for this install will be used by default to compile and link the
  example programs.  Note that h5redeploy must be run if these binaries are
  copied or extracted in a directory other than the one where they were initially
  installed.  Compile scripts from other locations can be used by setting an
  environment variable prefix to the path of the directory containing the bin
  directory with the compile scripts h5cc, h5fc, etc.  For example, export
  prefix=/opt/scls/alderlake-intel-intelmpi-mkl to use h5cc, h5fc, etc. in /opt/scls/alderlake-intel-intelmpi-mkl/bin.


pkgId: b508995ed8c388d1a67e63c4d7e8d74a2e77d1c91452b3e115f65d22a81562f5
name: scls-cascadelake-intel-intelmpi-cuda-hdf5-examples
arch: x86_64
version: 1.14.3
epoch: 0
release: 1.el9
summary: C-example files for HDF5
url: https://www.hdfgroup.org/solutions/hdf5
rpm_license: BSD
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-cascadelake-intel-intelmpi-cuda-hdf5-1.14.3-1.el9.src.rpm
location_href: scls-cascadelake-intel-intelmpi-cuda-hdf5-examples-1.14.3-1.el9.x86_64.rpm
checksum_type: sha256
description:
  This package contains example programs for the installed APIs and scripts to
  compile and run them.  Examples in the c and hl/c subdirectories are always
  installed, and those in fortran, hl/fortran, c++ and hl/c++ will be installed
  when fortran or c++ are enabled.

  Running the run-all-ex.sh script in this directory will run the scripts and in
  turn the examples in all the subdirectories where examples are installed.  The
  scripts can also be run individually.  The appropriate compile scripts in the
  bin directory for this install will be used by default to compile and link the
  example programs.  Note that h5redeploy must be run if these binaries are
  copied or extracted in a directory other than the one where they were initially
  installed.  Compile scripts from other locations can be used by setting an
  environment variable prefix to the path of the directory containing the bin
  directory with the compile scripts h5cc, h5fc, etc.  For example, export
  prefix=/opt/scls/cascadelake-intel-intelmpi-cuda to use h5cc, h5fc, etc. in /opt/scls/cascadelake-intel-intelmpi-cuda/bin.


pkgId: 3eb49b9111cca7e04d54190c62a1a542be0978ce30c72a8d9cada9e47138b98a
name: scls-cascadelake-intel-intelmpi-mkl-hdf5-examples
arch: x86_64
version: 1.14.3
epoch: 0
release: 1.el9
summary: C-example files for HDF5
url: https://www.hdfgroup.org/solutions/hdf5
rpm_license: BSD
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-cascadelake-intel-intelmpi-mkl-hdf5-1.14.3-1.el9.src.rpm
location_href: scls-cascadelake-intel-intelmpi-mkl-hdf5-examples-1.14.3-1.el9.x86_64.rpm
checksum_type: sha256
description:
  This package contains example programs for the installed APIs and scripts to
  compile and run them.  Examples in the c and hl/c subdirectories are always
  installed, and those in fortran, hl/fortran, c++ and hl/c++ will be installed
  when fortran or c++ are enabled.

  Running the run-all-ex.sh script in this directory will run the scripts and in
  turn the examples in all the subdirectories where examples are installed.  The
  scripts can also be run individually.  The appropriate compile scripts in the
  bin directory for this install will be used by default to compile and link the
  example programs.  Note that h5redeploy must be run if these binaries are
  copied or extracted in a directory other than the one where they were initially
  installed.  Compile scripts from other locations can be used by setting an
  environment variable prefix to the path of the directory containing the bin
  directory with the compile scripts h5cc, h5fc, etc.  For example, export
  prefix=/opt/scls/cascadelake-intel-intelmpi-mkl to use h5cc, h5fc, etc. in /opt/scls/cascadelake-intel-intelmpi-mkl/bin.


pkgId: ef671d028f0c59f4e6ebb51d1913c609e7332207cd87aa3c45dc636042665c57
name: scls-release
arch: noarch
version: 2024
epoch: 0
release: 1.el9
summary: Repository configuration for Scientific Core Libraries (SCLS)
url: https://belfem.lbl.gov/scls
rpm_license: GPLv2
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-release-2024-1.el9.src.rpm
location_href: scls-release-2024-1.el9.noarch.rpm
checksum_type: sha256
description:
  This package provides the Scientific Core Libraries (SCLs) repository configuration
  and GPG key for Enterprise Linux 9.


pkgId: eb8e36c1e41818bf3d6bba51f92334fa9cd35755dc201f0e33a51f15c93d2cac
name: scls-skylake-gnu-mpich-cuda-hdf5-examples
arch: x86_64
version: 1.14.3
epoch: 0
release: 1.el9
summary: C-example files for HDF5
url: https://www.hdfgroup.org/solutions/hdf5
rpm_license: BSD
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-skylake-gnu-mpich-cuda-hdf5-1.14.3-1.el9.src.rpm
location_href: scls-skylake-gnu-mpich-cuda-hdf5-examples-1.14.3-1.el9.x86_64.rpm
checksum_type: sha256
description:
  This package contains example programs for the installed APIs and scripts to
  compile and run them.  Examples in the c and hl/c subdirectories are always
  installed, and those in fortran, hl/fortran, c++ and hl/c++ will be installed
  when fortran or c++ are enabled.

  Running the run-all-ex.sh script in this directory will run the scripts and in
  turn the examples in all the subdirectories where examples are installed.  The
  scripts can also be run individually.  The appropriate compile scripts in the
  bin directory for this install will be used by default to compile and link the
  example programs.  Note that h5redeploy must be run if these binaries are
  copied or extracted in a directory other than the one where they were initially
  installed.  Compile scripts from other locations can be used by setting an
  environment variable prefix to the path of the directory containing the bin
  directory with the compile scripts h5cc, h5fc, etc.  For example, export
  prefix=/opt/scls/skylake-gnu-mpich-cuda to use h5cc, h5fc, etc. in /opt/scls/skylake-gnu-mpich-cuda/bin.


pkgId: 8b5069492cee4bb5ae907734b3c8bceb60e92ce24c87f5d7e00a9a45bff96e64
name: scls-skylake-gnu-mpich-cuda-mpich
arch: x86_64
version: 4.1.2
epoch: 0
release: 1.el9
summary: A high-performance implementation of MPI
url: https://www.mpich.org/
rpm_license: MIT
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-skylake-gnu-mpich-cuda-mpich-4.1.2-1.el9.src.rpm
location_href: scls-skylake-gnu-mpich-cuda-mpich-4.1.2-1.el9.x86_64.rpm
checksum_type: sha256
description:
  MPICH is a high-performance and widely portable implementation of the Message
  Passing Interface (MPI) standard (MPI-1, MPI-2 and MPI-3). The goals of MPICH
  are: (1) to provide an MPI implementation that efficiently supports different
  computation and communication platforms including commodity clusters (desktop
  systems, shared-memory systems, multicore architectures), high-speed networks
  (10 Gigabit Ethernet, InfiniBand, Myrinet, Quadrics) and proprietary high-end
  computing systems (Blue Gene, Cray) and (2) to enable cutting-edge research in
  MPI through an easy-to-extend modular framework for other derived
  implementations.

  The mpich binaries in this RPM packages were configured to use the default
  process manager (Hydra) using the default device (ch3). The ch3 device
  was configured with support for the nemesis channel that allows for
  shared-memory and TCP/IP sockets based communication.

  This build also include support for using the 'module environment' to select
  which MPI implementation to use when multiple implementations are installed.
  If you want MPICH support to be automatically loaded, you need to install the
  mpich-autoload package.


pkgId: 0e40b0533fb7e3764592917d6b89696d0ca71d27f55211b0df4c9add54d5ecfa
name: scls-skylake-gnu-mpich-cuda-pmix
arch: x86_64
version: 4.2.9
epoch: 0
release: 1.el9
summary: An extended/exascale implementation of the PMIx Standard
url: https://github.com/openpmix/openpmix
rpm_license: BSD
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-skylake-gnu-mpich-cuda-pmix-4.2.9-1.el9.src.rpm
location_href: scls-skylake-gnu-mpich-cuda-pmix-4.2.9-1.el9.x86_64.rpm
checksum_type: sha256
description:
  The Process Management Interface (PMI) has been used for quite some time as a
  means of exchanging wireup information needed for interprocess communication. Two
  versions (PMI-1 and PMI-2) have been released as part of the MPICH effort. While
  PMI-2 demonstrates better scaling properties than its PMI-1 predecessor, attaining
  rapid launch and wireup of the roughly 1M processes executing across 100k nodes
  expected for exascale operations remains challenging.

  PMI Exascale (PMIx) represents an attempt to resolve these questions by providing
  an extended version of the PMI standard specifically designed to support clusters
  up to and including exascale sizes. The overall objective of the project is to
  eliminate some current restrictions that impact scalability, and provide
  a reference implementation of the PMIx-server that demonstrates the desired level of
  scalability.


pkgId: dfb1e9b912090bc5ef0312430841abce901de97d9ef3a2d1a3fd9538823fdd09
name: scls-skylake-gnu-mpich-lapack-blas
arch: x86_64
version: 3.12.0
epoch: 0
release: 1.el9
summary: The Basic Linear Algebra Subprograms library
url: http://www.netlib.org/lapack/
rpm_license: BSD
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-skylake-gnu-mpich-lapack-lapack-3.12.0-1.el9.src.rpm
location_href: scls-skylake-gnu-mpich-lapack-blas-3.12.0-1.el9.x86_64.rpm
checksum_type: sha256
description:
  BLAS (Basic Linear Algebra Subprograms) is a standard library which
  provides a number of basic algorithms for numerical algebra.


pkgId: b540ac81b6a03880213b4bba981e1696a9eba62d710edc712b3b54654b062006
name: scls-skylake-gnu-mpich-lapack-cblas
arch: x86_64
version: 3.12.0
epoch: 0
release: 1.el9
summary: C interfaces for BLAS
url: http://www.netlib.org/lapack/
rpm_license: BSD
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-skylake-gnu-mpich-lapack-lapack-3.12.0-1.el9.src.rpm
location_href: scls-skylake-gnu-mpich-lapack-cblas-3.12.0-1.el9.x86_64.rpm
checksum_type: sha256
description:
  CBLAS, the C interface to the Basic Linear Algebra Subprograms (BLAS),
  is a standardized set of low-level routines that provide efficient
  linear algebra operations, primarily for vector and matrix calculations.
  Originally developed in FORTRAN for use in high-performance computing
  BLAS has been fundamental in scientific computing and forms the backbone
  of many complex numerical computing tasks.
  CBLAS is a C language interface to the BLAS library.


pkgId: dc4923a7c961330c771e430930c9791dcc56b183976062edf1ef54f266f3741c
name: scls-skylake-gnu-mpich-lapack-fspblas
arch: x86_64
version: 0.5
epoch: 0
release: 2.el9
summary: The NIST Reference Implementation of the Fortran Sparse Matrix Toolkit
url: https://math.nist.gov/spblas/
rpm_license: Public Domain
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-skylake-gnu-mpich-lapack-fspblas-0.5-2.el9.src.rpm
location_href: scls-skylake-gnu-mpich-lapack-fspblas-0.5-2.el9.x86_64.rpm
checksum_type: sha256
description:
  FSPBLAS, from NIST, serves as a reference Fortran implementation for sparse matrix computations, akin to the role of BLAS in linear algebra. It supports key formats like CSR, CSC, and COO, and includes routines for matrix multiplication and triangular solves. While primarily used for development and testing in scientific computing, for performance-critical applications, alternatives like Intel's MKL are recommended.


pkgId: 6c7a49f03fd53a732eb981d36f7c2e9edb9566b7c3342a88f98642e622d1a5e3
name: scls-skylake-gnu-mpich-lapack-hdf5-examples
arch: x86_64
version: 1.14.3
epoch: 0
release: 1.el9
summary: C-example files for HDF5
url: https://www.hdfgroup.org/solutions/hdf5
rpm_license: BSD
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-skylake-gnu-mpich-lapack-hdf5-1.14.3-1.el9.src.rpm
location_href: scls-skylake-gnu-mpich-lapack-hdf5-examples-1.14.3-1.el9.x86_64.rpm
checksum_type: sha256
description:
  This package contains example programs for the installed APIs and scripts to
  compile and run them.  Examples in the c and hl/c subdirectories are always
  installed, and those in fortran, hl/fortran, c++ and hl/c++ will be installed
  when fortran or c++ are enabled.

  Running the run-all-ex.sh script in this directory will run the scripts and in
  turn the examples in all the subdirectories where examples are installed.  The
  scripts can also be run individually.  The appropriate compile scripts in the
  bin directory for this install will be used by default to compile and link the
  example programs.  Note that h5redeploy must be run if these binaries are
  copied or extracted in a directory other than the one where they were initially
  installed.  Compile scripts from other locations can be used by setting an
  environment variable prefix to the path of the directory containing the bin
  directory with the compile scripts h5cc, h5fc, etc.  For example, export
  prefix=/opt/scls/skylake-gnu-mpich-lapack to use h5cc, h5fc, etc. in /opt/scls/skylake-gnu-mpich-lapack/bin.


pkgId: 21c71e87adc3b3cb8aac17e3a65a3a59c1d2cfff368da841e95e047fcad6ef92
name: scls-skylake-gnu-mpich-lapack-lapack
arch: x86_64
version: 3.12.0
epoch: 0
release: 1.el9
summary: Numerical linear algebra package libraries
url: http://www.netlib.org/lapack/
rpm_license: BSD
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-skylake-gnu-mpich-lapack-lapack-3.12.0-1.el9.src.rpm
location_href: scls-skylake-gnu-mpich-lapack-lapack-3.12.0-1.el9.x86_64.rpm
checksum_type: sha256
description:
  LAPACK (Linear Algebra PACKage) is a standard library for numerical
  linear algebra. LAPACK provides routines for solving systems of
  simultaneous linear equations, least-squares solutions of linear
  systems of equations, eigenvalue problems, and singular value
  problems. Associated matrix factorizations (LU, Cholesky, QR, SVD,
  Schur, and generalized Schur) and related computations (i.e.,
  reordering of Schur factorizations and estimating condition numbers)
  are also included. LAPACK can handle dense and banded matrices, but
  not general sparse matrices. Similar functionality is provided for
  real and complex matrices in both single and double precision. LAPACK
  is coded in Fortran90 and built with gcc.
  }


pkgId: db5c78a253a931835d516d9dc2d69bfb1e69965fe9007912f6b6d7081bccff64
name: scls-skylake-gnu-mpich-lapack-lapacke
arch: x86_64
version: 3.12.0
epoch: 0
release: 1.el9
summary: C Interface to Linear Algebra Package (LAPACK)
url: http://www.netlib.org/lapack/
rpm_license: BSD
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-skylake-gnu-mpich-lapack-lapack-3.12.0-1.el9.src.rpm
location_href: scls-skylake-gnu-mpich-lapack-lapacke-3.12.0-1.el9.x86_64.rpm
checksum_type: sha256
description:
  LAPACKE is the C language interface to the widely-used LAPACK library,
  which is renowned for its comprehensive collection of algorithms for
  solving various linear algebra problems. Originally developed for
  Fortran, LAPACK's capabilities are essential in numerous scientific and
  engineering applications, ranging from solving systems of linear equations
  to eigenvalue problems and matrix factorizations.

  LAPACKE provides a seamless and straightforward way for C and C++
  programmers to integrate these powerful LAPACK routines into their
  applications. It simplifies the process of calling LAPACK functions
  from C/C++ code by handling the differences between the Fortran and
  C calling conventions and data representations.


pkgId: 5cf1bb7b62ddeb8fb15d9e377a29525f0adbcd97a719c62b7204ab251ff3b94e
name: scls-skylake-gnu-mpich-lapack-scalapack
arch: x86_64
version: 2.2.0
epoch: 0
release: 1.el9
summary: A subset of LAPACK routines redesigned for heterogeneous computing
url: http://www.netlib.org/scalapack/
rpm_license: Public Domain
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-skylake-gnu-mpich-lapack-scalapack-2.2.0-1.el9.src.rpm
location_href: scls-skylake-gnu-mpich-lapack-scalapack-2.2.0-1.el9.x86_64.rpm
checksum_type: sha256
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 inter-processor 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 or PVM.

  Like LAPACK, the ScaLAPACK routines are based on
  block-partitioned algorithms in order to minimize the frequency
  of data movement between different levels of the memory hierarchy.
  (For such machines, the memory hierarchy includes the off-processor
  memory of other processors, in addition to the hierarchy of registers,
  cache, and local memory on each processor.) The fundamental building
  blocks of the ScaLAPACK library are distributed memory versions (PBLAS)
  of the Level 1, 2 and 3 BLAS, and a set of Basic Linear Algebra
  Communication Subprograms (BLACS) for communication tasks that arise
  frequently in parallel linear algebra computations. In the ScaLAPACK
  routines, all inter-processor communication occurs within the PBLAS and the
  BLACS. One of the design goals of ScaLAPACK was to have the ScaLAPACK
  routines resemble their LAPACK equivalents as much as possible.


pkgId: 32224959914cacde300056cec494544c44fd0db416698e9c162cee7dfbab6b03
name: scls-skylake-gnu-mpich-mkl-hdf5-examples
arch: x86_64
version: 1.14.3
epoch: 0
release: 1.el9
summary: C-example files for HDF5
url: https://www.hdfgroup.org/solutions/hdf5
rpm_license: BSD
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-skylake-gnu-mpich-mkl-hdf5-1.14.3-1.el9.src.rpm
location_href: scls-skylake-gnu-mpich-mkl-hdf5-examples-1.14.3-1.el9.x86_64.rpm
checksum_type: sha256
description:
  This package contains example programs for the installed APIs and scripts to
  compile and run them.  Examples in the c and hl/c subdirectories are always
  installed, and those in fortran, hl/fortran, c++ and hl/c++ will be installed
  when fortran or c++ are enabled.

  Running the run-all-ex.sh script in this directory will run the scripts and in
  turn the examples in all the subdirectories where examples are installed.  The
  scripts can also be run individually.  The appropriate compile scripts in the
  bin directory for this install will be used by default to compile and link the
  example programs.  Note that h5redeploy must be run if these binaries are
  copied or extracted in a directory other than the one where they were initially
  installed.  Compile scripts from other locations can be used by setting an
  environment variable prefix to the path of the directory containing the bin
  directory with the compile scripts h5cc, h5fc, etc.  For example, export
  prefix=/opt/scls/skylake-gnu-mpich-mkl to use h5cc, h5fc, etc. in /opt/scls/skylake-gnu-mpich-mkl/bin.


pkgId: a7b0c5d69e4c9f44c975b778b615d1777a404e120ed0ac987b5a556b61f528c6
name: scls-skylake-gnu-openmpi-cuda-hdf5-examples
arch: x86_64
version: 1.14.3
epoch: 0
release: 1.el9
summary: C-example files for HDF5
url: https://www.hdfgroup.org/solutions/hdf5
rpm_license: BSD
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-skylake-gnu-openmpi-cuda-hdf5-1.14.3-1.el9.src.rpm
location_href: scls-skylake-gnu-openmpi-cuda-hdf5-examples-1.14.3-1.el9.x86_64.rpm
checksum_type: sha256
description:
  This package contains example programs for the installed APIs and scripts to
  compile and run them.  Examples in the c and hl/c subdirectories are always
  installed, and those in fortran, hl/fortran, c++ and hl/c++ will be installed
  when fortran or c++ are enabled.

  Running the run-all-ex.sh script in this directory will run the scripts and in
  turn the examples in all the subdirectories where examples are installed.  The
  scripts can also be run individually.  The appropriate compile scripts in the
  bin directory for this install will be used by default to compile and link the
  example programs.  Note that h5redeploy must be run if these binaries are
  copied or extracted in a directory other than the one where they were initially
  installed.  Compile scripts from other locations can be used by setting an
  environment variable prefix to the path of the directory containing the bin
  directory with the compile scripts h5cc, h5fc, etc.  For example, export
  prefix=/opt/scls/skylake-gnu-openmpi-cuda to use h5cc, h5fc, etc. in /opt/scls/skylake-gnu-openmpi-cuda/bin.


pkgId: c6c7fd3b6081ea0cdff69f72d987de5a8fe69943f9cd158d02678ad7a6f8447d
name: scls-skylake-gnu-openmpi-cuda-openmpi
arch: x86_64
version: 5.0.2
epoch: 0
release: 3.el9
summary: A powerful implementation of MPI/SHMEM
url: https://www.open-mpi.org/
rpm_license: BSD
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-skylake-gnu-openmpi-cuda-openmpi-5.0.2-3.el9.src.rpm
location_href: scls-skylake-gnu-openmpi-cuda-openmpi-5.0.2-3.el9.x86_64.rpm
checksum_type: sha256
description:
  Open MPI is an open source implementation of the Message Passing
  Interface specification (https://www.mpi-forum.org/) developed and
  maintained by a consortium of research, academic, and industry
  partners.

  Open MPI also includes an implementation of the OpenSHMEM parallel
  programming API (https://www.openshmem.org/).  OpenSHMEM is a
  Partitioned Global Address Space (PGAS) abstraction layer, which
  provides fast inter-process communication using one-sided
  communication techniques.

  This RPM contains all the tools necessary to compile, link, and run
  Open MPI and OpenSHMEM jobs


pkgId: f1298ad4a80411b8bd11264e63b73dcefcca35a2cf653b40d7870623acbf9e0d
name: scls-skylake-gnu-openmpi-lapack-hdf5-examples
arch: x86_64
version: 1.14.3
epoch: 0
release: 1.el9
summary: C-example files for HDF5
url: https://www.hdfgroup.org/solutions/hdf5
rpm_license: BSD
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-skylake-gnu-openmpi-lapack-hdf5-1.14.3-1.el9.src.rpm
location_href: scls-skylake-gnu-openmpi-lapack-hdf5-examples-1.14.3-1.el9.x86_64.rpm
checksum_type: sha256
description:
  This package contains example programs for the installed APIs and scripts to
  compile and run them.  Examples in the c and hl/c subdirectories are always
  installed, and those in fortran, hl/fortran, c++ and hl/c++ will be installed
  when fortran or c++ are enabled.

  Running the run-all-ex.sh script in this directory will run the scripts and in
  turn the examples in all the subdirectories where examples are installed.  The
  scripts can also be run individually.  The appropriate compile scripts in the
  bin directory for this install will be used by default to compile and link the
  example programs.  Note that h5redeploy must be run if these binaries are
  copied or extracted in a directory other than the one where they were initially
  installed.  Compile scripts from other locations can be used by setting an
  environment variable prefix to the path of the directory containing the bin
  directory with the compile scripts h5cc, h5fc, etc.  For example, export
  prefix=/opt/scls/skylake-gnu-openmpi-lapack to use h5cc, h5fc, etc. in /opt/scls/skylake-gnu-openmpi-lapack/bin.


pkgId: 522ae1b73a02d8388d6d3422e9a386771ef0325ed791ae7f11600a4564ce4b39
name: scls-skylake-gnu-openmpi-mkl-hdf5-examples
arch: x86_64
version: 1.14.3
epoch: 0
release: 1.el9
summary: C-example files for HDF5
url: https://www.hdfgroup.org/solutions/hdf5
rpm_license: BSD
rpm_group: Unspecified
rpm_buildhost: 8-92-4-d9-9-b.dhcp.lbl.gov
rpm_sourcerpm: scls-skylake-gnu-openmpi-mkl-hdf5-1.14.3-1.el9.src.rpm
location_href: scls-skylake-gnu-openmpi-mkl-hdf5-examples-1.14.3-1.el9.x86_64.rpm
checksum_type: sha256
description:
  This package contains example programs for the installed APIs and scripts to
  compile and run them.  Examples in the c and hl/c subdirectories are always
  installed, and those in fortran, hl/fortran, c++ and hl/c++ will be installed
  when fortran or c++ are enabled.

  Running the run-all-ex.sh script in this directory will run the scripts and in
  turn the examples in all the subdirectories where examples are installed.  The
  scripts can also be run individually.  The appropriate compile scripts in the
  bin directory for this install will be used by default to compile and link the
  example programs.  Note that h5redeploy must be run if these binaries are
  copied or extracted in a directory other than the one where they were initially
  installed.  Compile scripts from other locations can be used by setting an
  environment variable prefix to the path of the directory containing the bin
  directory with the compile scripts h5cc, h5fc, etc.  For example, export
  prefix=/opt/scls/skylake-gnu-openmpi-mkl to use h5cc, h5fc, etc. in /opt/scls/skylake-gnu-openmpi-mkl/bin.


