* py-minkowskiengine: new package (sparse tensor autodiff by Nvidia)
This python package (with cuda support) provides torch support for sparse
tensors. The `pybind11` headers are not found without the patch to `setup.py`.
* [@spackbot] updating style on behalf of wdconinc
* py-minkowskiengine: depends_on numpy, pybind11 type=link; no patch
* [@spackbot] updating style on behalf of wdconinc
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Co-authored-by: wdconinc <wdconinc@users.noreply.github.com>
The fastqc script was using the system perl. This PR sets the script to
use the spack built/provided perl. This PR also removes the code that
adds the java path. That should be handled by module loading as far as I
know.
* Add HDF5 version 1.13.3.
* Remove maintainers no longer with The HDFGroup.
* Add version hdf5-vol-async@1.4
* Add HDF5 version 1.14.0, develop-1.14, develop-1.15.
Add missing conflicts for api version and develop versions.
* Add conflicts statement to hdf5/package.py to avoid building hdf5 with
MPICH 4.0.x versions with bug that causes testphdf5 test to fail.
* Add patch to call find_package(MPI) for dependent packages not finding
it, not having called it themselves.
* Remove language components from find_package(MPI) in
hdf5_1_14_0_config_find_mpi.patch.
* Add HDF5 version 1.14.0, develop-1.14, develop-1.15.
Add missing conflicts for api version and develop versions.
* Add conflicts statement to hdf5/package.py to avoid building hdf5 with
MPICH 4.0.x versions with bug that causes testphdf5 test to fail.
* Add patch to call find_package(MPI) for dependent packages not finding
it, not having called it themselves.
* Remove language components from find_package(MPI) in
hdf5_1_14_0_config_find_mpi.patch.
* Don't guard ParaView patch on HDF5 variant
ParaView always needsd HDF5 and ignores the variant.
* py-h5py: Newer versions of HDF5 introduce breaking API changes
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Co-authored-by: Tamara Dahlgren <35777542+tldahlgren@users.noreply.github.com>
Co-authored-by: Ryan Krattiger <ryan.krattiger@kitware.com>
* Add trilinos-solvers variant to nalu-wind package.
This allows nalu-wind to be built against a trilinos installation
which doesn't have amesos2, belos, ifpack2, or muelu enabled, if
the nalu-wind user provides the spec 'nalu-wind@master~trilinos-solvers'
Support for these solver-packages remains on by default.
* Fixed a style issue reported by CI.
* Incorporate change in wording suggested from review comments.
... to clarify that at least one, or both, of hypre and/or
trilinos-solvers must be enabled. The error condition is if
both are disabled.
* That style checker is picky...
* It really did want a trailing comma...
* py-jinja2-cli: new package
* Update var/spack/repos/builtin/packages/py-jinja2-cli/package.py
Co-authored-by: Adam J. Stewart <ajstewart426@gmail.com>
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Co-authored-by: Adam J. Stewart <ajstewart426@gmail.com>
* Add py-docker@5:
* [@spackbot] updating style on behalf of spoutn1k
* Ignore `tls` variant
* Update var/spack/repos/builtin/packages/py-docker/package.py
Co-authored-by: Adam J. Stewart <ajstewart426@gmail.com>
* `py-docker`: `py-paramiko` version fix
---------
Co-authored-by: spoutn1k <spoutn1k@users.noreply.github.com>
Co-authored-by: Adam J. Stewart <ajstewart426@gmail.com>
The gfx906:xnack- and gfx908:xnack- targets were introduced in ROCm 4.1
and replaced gfx906 and gfx908 as default build targets, but the library
can still be built for gfx906 and gfx908 if requested.
