Feedstock license: BSD-3-Clause
Home: https://github.com/conda-forge/intel_repack-feedstock
Package license: LicenseRef-IntelSimplifiedSoftwareOct2022
Summary: Repackaged Intel libraries
Home: https://github.com/uxlfoundation/oneDAL
Package license: LicenseRef-IntelSimplifiedSoftwareOct2022
Summary: Intel® oneDAL runtime libraries
Documentation: http://uxlfoundation.github.io/oneDAL
OneAPI Data Analytics Library (oneDAL) is a C++ and DPC++ library (powering the
Extension for Scikit-learn in Python)
which implements accelerated machine learning routines for tabular data (e.g. linear regression, K-means clustering,
random forests, etc.) for CPUs, GPUs, and multi-node distributed setups.
Acceleration on CPUs is achieved by leveraging SIMD instructions and exploiting cache structures of modern hardware,
while GPU acceleration leverages the SYCL framework and the oneMKL library.
OneDAL is part of the UXL Foundation
and is an implementation of the oneAPI specification
for the oneDAL component.
Home: https://github.com/uxlfoundation/oneDAL
Package license: LicenseRef-IntelSimplifiedSoftwareOct2022
Summary: Devel package for building against Intel® oneDAL shared libraries
Documentation: http://uxlfoundation.github.io/oneDAL
OneAPI Data Analytics Library (oneDAL) is a C++ and DPC++ library (powering the
Extension for Scikit-learn in Python)
which implements accelerated machine learning routines for tabular data (e.g. linear regression, K-means clustering,
random forests, etc.) for CPUs, GPUs, and multi-node distributed setups.
Acceleration on CPUs is achieved by leveraging SIMD instructions and exploiting cache structures of modern hardware,
while GPU acceleration leverages the SYCL framework and the oneMKL library.
OneDAL is part of the UXL Foundation
and is an implementation of the oneAPI specification
for the oneDAL component.
Home: https://github.com/uxlfoundation/oneDAL
Package license: LicenseRef-IntelSimplifiedSoftwareOct2022
Summary: Headers for building against Intel® oneDAL libraries
Documentation: http://uxlfoundation.github.io/oneDAL
OneAPI Data Analytics Library (oneDAL) is a C++ and DPC++ library (powering the
Extension for Scikit-learn in Python)
which implements accelerated machine learning routines for tabular data (e.g. linear regression, K-means clustering,
random forests, etc.) for CPUs, GPUs, and multi-node distributed setups.
Acceleration on CPUs is achieved by leveraging SIMD instructions and exploiting cache structures of modern hardware,
while GPU acceleration leverages the SYCL framework and the oneMKL library.
OneDAL is part of the UXL Foundation
and is an implementation of the oneAPI specification
for the oneDAL component.
Home: https://github.com/uxlfoundation/oneDAL
Package license: LicenseRef-IntelSimplifiedSoftwareOct2022
Summary: Static libraries for Intel® oneDAL
Documentation: http://uxlfoundation.github.io/oneDAL
OneAPI Data Analytics Library (oneDAL) is a C++ and DPC++ library (powering the
Extension for Scikit-learn in Python)
which implements accelerated machine learning routines for tabular data (e.g. linear regression, K-means clustering,
random forests, etc.) for CPUs, GPUs, and multi-node distributed setups.
Acceleration on CPUs is achieved by leveraging SIMD instructions and exploiting cache structures of modern hardware,
while GPU acceleration leverages the SYCL framework and the oneMKL library.
OneDAL is part of the UXL Foundation
and is an implementation of the oneAPI specification
for the oneDAL component.
Package license: LicenseRef-IntelSimplifiedSoftwareOct2022
Summary: Devel package for building against Intel® MPI libraries
Documentation: https://www.intel.com/content/www/us/en/developer/tools/oneapi/mpi-library.html
Intel® MPI Library is a multifabric message-passing library that implements the open source MPICH specification. Use the library to create, maintain, and test advanced, complex applications that perform better on HPC clusters based on Intel® and compatible processors. This package is a repackaged set of binaries obtained directly from Intel's conda channel.
Package license: LicenseRef-IntelSimplifiedSoftwareOct2022
Summary: Intel® MPI Library
Documentation: https://www.intel.com/content/www/us/en/developer/tools/oneapi/mpi-library.html
Intel® MPI Library is a multifabric message-passing library that implements the open source MPICH specification. Use the library to create, maintain, and test advanced, complex applications that perform better on HPC clusters based on Intel® and compatible processors. This package is a repackaged set of binaries obtained directly from Intel's conda channel.
Package license: LicenseRef-IntelSimplifiedSoftwareOct2022
Summary: Intel® oneAPI Math Kernel Library runtime libraries
Documentation: https://www.intel.com/content/www/us/en/developer/tools/oneapi/onemkl.html
Intel® oneAPI Math Kernel Library is Intel®-Optimized Math Library for Numerical Computing on CPUs & GPUs This package is a repackaged set of binaries obtained directly from Intel's conda channel.
Package license: LicenseRef-IntelSimplifiedSoftwareOct2022
Summary: Devel package for building against Intel® oneMKL libraries
Intel® oneAPI Math Kernel Library headers and libraries for developing software that uses oneMKL This package is a repackaged set of binaries obtained directly from Intel's conda channel.
Package license: LicenseRef-IntelSimplifiedSoftwareOct2022
Summary: Devel package for building against Intel® oneMKL SYCL libraries
Intel® oneAPI Math Kernel Library SYCL libraries for developing software that uses oneMKL with DPCPP This package is a repackaged set of binaries obtained directly from Intel's conda channel.
Package license: LicenseRef-IntelSimplifiedSoftwareOct2022
Summary: Intel® oneAPI Math Kernel Library dpcpp libraries
Documentation: https://www.intel.com/content/www/us/en/developer/tools/oneapi/onemkl.html
Intel® oneAPI Math Kernel Library is Intel®-Optimized Math Library for Numerical Computing on CPUs & GPUs This package is a repackaged set of binaries obtained directly from Intel's conda channel.
Package license: LicenseRef-IntelSimplifiedSoftwareOct2022
Summary: Headers for building against Intel® oneMKL libraries
Documentation: https://www.intel.com/content/www/us/en/developer/tools/oneapi/onemkl.html
Intel® oneAPI Math Kernel Library headers for developing software that uses oneMKL This package is a repackaged set of binaries obtained directly from Intel's conda channel.
Package license: LicenseRef-IntelSimplifiedSoftwareOct2022
Summary: Static libraries for Intel® oneMKL libraries
Intel® oneAPI Math Kernel Library static libraries for developing software that uses oneMKL This package is a repackaged set of binaries obtained directly from Intel's conda channel.
Package license: Apache-2.0
Summary: Intel® oneAPI DPC++ Library
Documentation: https://software.intel.com/content/www/us/en/develop/tools/oneapi/components/dpc-library.html
The Intel® oneAPI DPC++ Library (oneDPL) is a companion to the Intel® oneAPI DPC++/C++ Compiler and provides an alternative for C++ developers who create heterogeneous applications and solutions. Its APIs are based on familiar standards—C++ STL, Parallel STL (PSTL), Boost.Compute, and SYCL*—to maximize productivity and performance across CPUs, GPUs, and FPGAs. This package is a repackaged set of binaries obtained directly from Intel's conda channel.
Package license: LicenseRef-IntelSimplifiedSoftwareOct2022
Summary: Intel® oneAPI Math Kernel Library runtime libraries
Documentation: https://www.intel.com/content/www/us/en/developer/tools/oneapi/onemkl.html
Intel® oneAPI Math Kernel Library is Intel®-Optimized Math Library for Numerical Computing on CPUs & GPUs This package is a repackaged set of binaries obtained directly from Intel's conda channel.
Package license: LicenseRef-IntelSimplifiedSoftwareOct2022
Summary: Intel® oneAPI Math Kernel Library runtime libraries
Documentation: https://www.intel.com/content/www/us/en/developer/tools/oneapi/onemkl.html
Intel® oneAPI Math Kernel Library is Intel®-Optimized Math Library for Numerical Computing on CPUs & GPUs This package is a repackaged set of binaries obtained directly from Intel's conda channel.
Package license: LicenseRef-IntelSimplifiedSoftwareOct2022
Summary: Intel® oneAPI Math Kernel Library runtime libraries
Documentation: https://www.intel.com/content/www/us/en/developer/tools/oneapi/onemkl.html
Intel® oneAPI Math Kernel Library is Intel®-Optimized Math Library for Numerical Computing on CPUs & GPUs This package is a repackaged set of binaries obtained directly from Intel's conda channel.
Package license: LicenseRef-IntelSimplifiedSoftwareOct2022
Summary: Headers for building against Intel® oneMKL oneAPI interface libraries
Documentation: https://www.intel.com/content/www/us/en/developer/tools/oneapi/onemkl.html
Intel® oneAPI Math Kernel Library oneAPI interface headers for developing software that uses oneMKL This package is a repackaged set of binaries obtained directly from Intel's conda channel.
Package license: LicenseRef-IntelSimplifiedSoftwareOct2022
Summary: Intel® oneAPI Math Kernel Library runtime libraries
Documentation: https://www.intel.com/content/www/us/en/developer/tools/oneapi/onemkl.html
Intel® oneAPI Math Kernel Library is Intel®-Optimized Math Library for Numerical Computing on CPUs & GPUs This package is a repackaged set of binaries obtained directly from Intel's conda channel.
Package license: LicenseRef-IntelSimplifiedSoftwareOct2022
Summary: Intel® oneAPI Math Kernel Library runtime libraries
Documentation: https://www.intel.com/content/www/us/en/developer/tools/oneapi/onemkl.html
Intel® oneAPI Math Kernel Library is Intel®-Optimized Math Library for Numerical Computing on CPUs & GPUs This package is a repackaged set of binaries obtained directly from Intel's conda channel.
Package license: LicenseRef-IntelSimplifiedSoftwareOct2022
Summary: Intel® oneAPI Math Kernel Library runtime libraries
Documentation: https://www.intel.com/content/www/us/en/developer/tools/oneapi/onemkl.html
Intel® oneAPI Math Kernel Library is Intel®-Optimized Math Library for Numerical Computing on CPUs & GPUs This package is a repackaged set of binaries obtained directly from Intel's conda channel.
Package license: LicenseRef-IntelSimplifiedSoftwareOct2022
Summary: Intel® oneAPI Math Kernel Library runtime libraries
Documentation: https://www.intel.com/content/www/us/en/developer/tools/oneapi/onemkl.html
Intel® oneAPI Math Kernel Library is Intel®-Optimized Math Library for Numerical Computing on CPUs & GPUs This package is a repackaged set of binaries obtained directly from Intel's conda channel.
Package license: LicenseRef-IntelSimplifiedSoftwareOct2022
Summary: Intel® oneAPI Math Kernel Library runtime libraries
Documentation: https://www.intel.com/content/www/us/en/developer/tools/oneapi/onemkl.html
Intel® oneAPI Math Kernel Library is Intel®-Optimized Math Library for Numerical Computing on CPUs & GPUs This package is a repackaged set of binaries obtained directly from Intel's conda channel.
Home: https://www.intel.com/content/www/us/en/developer/tools/overview.html
Package license: LicenseRef-IntelSimplifiedSoftwareOct2022
Summary: Intel® oneAPI Compiler OpenMP runtime
Documentation: https://www.intel.com/content/www/us/en/developer/tools/overview.html
Intel® oneAPI Compiler OpenMP runtime implementation This package is a repackaged set of binaries obtained directly from Intel's conda channel.
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Installing intel_repack 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, dal, dal-devel, dal-include, dal-static, impi-devel, impi_rt, intel-openmp, mkl, mkl-devel, mkl-devel-dpcpp, mkl-dpcpp, mkl-include, mkl-static, onedpl-devel, onemkl-sycl-blas, onemkl-sycl-datafitting, onemkl-sycl-dft, onemkl-sycl-include, onemkl-sycl-lapack, onemkl-sycl-rng, onemkl-sycl-sparse, onemkl-sycl-stats, onemkl-sycl-vm can be installed with conda:
conda install dal dal-devel dal-include dal-static impi-devel impi_rt intel-openmp mkl mkl-devel mkl-devel-dpcpp mkl-dpcpp mkl-include mkl-static onedpl-devel onemkl-sycl-blas onemkl-sycl-datafitting onemkl-sycl-dft onemkl-sycl-include onemkl-sycl-lapack onemkl-sycl-rng onemkl-sycl-sparse onemkl-sycl-stats onemkl-sycl-vm
or with mamba:
mamba install dal dal-devel dal-include dal-static impi-devel impi_rt intel-openmp mkl mkl-devel mkl-devel-dpcpp mkl-dpcpp mkl-include mkl-static onedpl-devel onemkl-sycl-blas onemkl-sycl-datafitting onemkl-sycl-dft onemkl-sycl-include onemkl-sycl-lapack onemkl-sycl-rng onemkl-sycl-sparse onemkl-sycl-stats onemkl-sycl-vm
It is possible to list all of the versions of dal available on your platform with conda:
conda search dal --channel conda-forge
or with mamba:
mamba search dal --channel conda-forge
Alternatively, mamba repoquery may provide more information:
# Search all versions available on your platform:
mamba repoquery search dal --channel conda-forge
# List packages depending on `dal`:
mamba repoquery whoneeds dal --channel conda-forge
# List dependencies of `dal`:
mamba repoquery depends dal --channel 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 Azure, GitHub, CircleCI, AppVeyor, Drone, and TravisCI it is possible to build and upload installable packages to the conda-forge anaconda.org 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.
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)
If you would like to improve the intel_repack 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/intel_repack-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/numberback to 0.