* NETCDF: Remove maxdims maxvars variant
I'm not sure of the correct protocol to do this, so decided to make a stab and hopefully it works or I'm told the correct way...
The `maxdims` and `maxvars` variants for the NetCDF package were, to the best of my knowledge, only ever used for the Exodus library in the SEACAS package. In versions of NetCDF prior to 4.4.0, Exodus required that the `NC_MAX_DIMS` and `NC_MAX_VARS` be increased over the default values. This requirement was removed in 4.4.0 and later.
I do not know of any way to make a variant depend on the version and since the `maxdims` and `maxvars` variants are integer values and not boolean, then every build of NetCDF will have these variants. Typically `maxdims=1024 maxvars=8192` and the build will patch the `netcdf.h` include file for every build even though it is (almost) never needed.
The SEACAS package has a NetCDF version requirement of >4.6.2, so it no longer specifies the `maxdims` or `maxvars` variant and I could find no other package in spack that uses this variant either, so removal should not break anything *in* spack. However, there is no guarantee that some other external package doesn't use the variant, so I'm not sure of the correct way to remove the variant.
For this PR, I simply removed the variants. If there is a way to specify use of the variant tied to a specific version, I couldn't find it anywhere...
* Address review comment
Removed `is_integral` and `import numbers` since `is_integral` was only place it was used.
* Add blank line for flake8
* magma now extends CudaPackage class, taking care of the gcc conflicts
* enforce +cuda; thus cuda is dependency via CudaPackage class
* add conflict
* use cuda_arch to set GPU_TARGET build option
* get rid of unnecessary constraint
* flake8
* impose cuda version dependency found empirically
* add variant description
* add conflict
Co-authored-by: Sinan81 <Sinan81@github>
Co-authored-by: Sinan81 <sbulut@3vgeomatics.com>
* build python bindings within qscintilla package via extend_path trick
* add todo
* reflect new setup also in py-pyqt4 package
* get rid of qscintilla dependency
* also tweak qgis for the new setup
* generalize the building of python bindings
* generalize building of pythong bindings to all qt versions
* add qsci_api variant
* add qsci_variant for pyqt4 package as well; add comment
* pyqt dependency should build with +qsci_api variant enabled
* fix bugs
* improve style
* reflect recent changes
* flake8
* improve style
* more flake8
* more flake8
Co-authored-by: Sinan81 <sbulut@3vgeomatics.com>
* Add some comments explaining the choice of flag_handler.
* Fix QMCPACK install method.
* Add support for ppconvert. This requires a custom build method.
* Fix QMCPACK setup_run_environment. Nexus should be properly supported now.
* Cleaner way to check for intel-mkl in spec.
* Remove build method and use build_targets property instead.
* Additional fixed for install method. Effectively restoring the original install method.
* Add the missing backslash to fix directory names.
* Update var/spack/repos/builtin/packages/qmcpack/package.py
Co-Authored-By: Adam J. Stewart <ajstewart426@gmail.com>
* Update var/spack/repos/builtin/packages/qmcpack/package.py
Co-Authored-By: Adam J. Stewart <ajstewart426@gmail.com>
* Update var/spack/repos/builtin/packages/qmcpack/package.py
Co-Authored-By: Adam J. Stewart <ajstewart426@gmail.com>
* Omit these conflicts on mkl variants for now, will hopefully be supportted with new concretizer in a couple of months.
Co-authored-by: Adam J. Stewart <ajstewart426@gmail.com>
intel moved the repository around.
github changes the prefix inside the tar according to the
repository name.
So all sha256 have changed!
I verified that the tar contents for 2019.4 did not change
except for the prefix.
* TensorFlow: Clean up/simplify the installation, make sure the headers are
installed so that horovod can find them successfully. Fix the 2.0.* builds.
* Backport of 837c8b6b upstream
"Remove contrib cloud bigtable and storage ops/kernels."
Allows 2.0.* releases to build with '--config=nogcp'
* comment regarding tensorflow issue #31187
Co-authored-by: Andrew W Elble <aweits@skl-a-00.rc.rit.edu>
## Summary
This PR updates and improves the Spack package for [UPC++](https://upcxx.lbl.gov).
I'm an LBL employee and developer on the UPC++ team, as well as the maintainer of this Spack package.
### Key Improvements:
* Adding new 2020.3.0 release and support for use of develop/master branches
- Our build infrastructure underwent a major change in this release, switching from a hand-rolled Python2 script to a bash-based autoconf work-alike.
- The new build system is NOT using autotools (nor does it support some of the more esoteric autoconf options), but the user interface for common builds is similar.
* Add explicit support for an MPI optional dependency
- New `mpi` variant enables use of the MPI-based spawner (most relevant on loosely coupled clusters), and the (unofficial) mpi-conduit backend
- This variant is OFF by default, since UPC++ works fine without MPI on many systems, increasing the likelihood first-time Spack users get a working build without needing to correctly setup MPI
* Add support for post-install testing using the test support deployed in the new build infrastructure
* Fix or workaround a few bugs observed during testing
### Status
The new package has been validated with a variety of specs across over seven different systems, including: NERSC cori, ALCF Theta, OLCF Summit, an in-house Linux cluster, and macOS laptops (Mojave and Catalina).
Expose serial/parallel build (MPI), CUDA/OpenMP backends, Clang, and
Ascent bindings.
Interestingly, `warpx +ascent` currently leads to an infinite loop in
the Spack concretizer.
Removed provider_index use of 'import from' and refactored a few routines to a further subclassing of _IndexBase for implementing user defined bindings of provider specs.
