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This commit address the case of concretizing a root spec with a
transitive conditional dependency on a virtual package, provided
by an external. Before these modifications default variant values
for the dependency bringing in the virtual package were not
respected, and the external package providing the virtual was added
to the DAG.
The issue stems from two facts:
- Selecting a provider has higher precedence than selecting default variants
- To ensure that an external is preferred, we used a negative weight
To solve it we shift all the providers weight so that:
- External providers have a weight of 0
- Non external provider have a weight of 10 or more
Using a weight of zero for external providers is such that having
an external provider, if present, or not having a provider at all
has the same effect on the higher priority minimization.
Also fixed a few minor bugs in concretize.lp, that were causing
spurious entries in the final answer set.
Cleaned concretize.lp from leftover rules.
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This commit introduces a new rule:
real_node(Package) :- not external(Package), node(Package).
that permits to distinguish between an external node and a
real node that shouldn't trim dependency. It solves the
case of concretizing ninja with an external Python.
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As reported, conflicts with compiler ranges were not treated
correctly. This commit adds tests to verify the expected behavior
for the new concretizer.
The new rules to enforce a correct behavior involve:
- Adding a rule to prefer the compiler selected for
the root package, if no other preference is set
- Give a strong negative weight to compiler preferences
expressed in packages.yaml
- Maximize on compiler AND compiler version match
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If preferred variants are present, they'll
set the default value of a variant. Otherwise
the default value is what is encoded
in package.py
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updated sha256sum of download .tgz
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* clfft: Fix for aarch64
* clfft: Changed the patch application conditions.
* clfft: Changed Patch file
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* Metall: add version 0.2
* Add Metall v0.3
* Update Metall package to v0.4 and v0.5.
* Metall package: add v0.6
* Metall package: add v0.7
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As of #13100, Spack installs the dependencies of a _single_ spec in parallel.
Environments, when installed, can only get parallelism from each individual
spec, as they're installed in order. This PR makes entire environments build
in parallel by extending Spack's package installer to accept multiple root
specs. The install command and Environment class have been updated to use
the new parallel install method.
The specs and kwargs for each *uninstalled* package (when not force-replacing
installations) of an environment are collected, passed to the `PackageInstaller`,
and processed using a single build queue.
This introduces a `BuildRequest` class to track install arguments, and it
significantly cleans up the code used to track package ids during installation.
Package ids in the build queue are now just DAG hashes as you would expect,
Other tasks:
- [x] Finish updating the unit tests based on `PackageInstaller`'s use of
`BuildRequest` and the associated changes
- [x] Change `environment.py`'s `install_all` to use the `PackageInstaller` directly
- [x] Change the `install` command to leverage the new installation process for multiple specs
- [x] Change install output messages for external packages, e.g.:
`[+] /usr` -> `[+] /usr (external bzip2-1.0.8-<dag-hash>`
- [x] Fix incomplete environment install's view setup/update and not confirming all
packages are installed (?)
- [x] Ensure externally installed package dependencies are properly accounted for in
remaining build tasks
- [x] Add tests for coverage (if insufficient and can identity the appropriate, uncovered non-comment lines)
- [x] Add documentation
- [x] Resolve multi-compiler environment install issues
- [x] Fix issue with environment installation reporting (restore CDash/JUnit reports)
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* [xerces-c] add netaccessor variant, new version
* [geant4] add xerces-c netaccessor requirement
* [xerces-c] format
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* add gcc 4.8 conflict
* commit suggestion
Co-authored-by: Adam J. Stewart <ajstewart426@gmail.com>
Co-authored-by: Adam J. Stewart <ajstewart426@gmail.com>
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* Add WRF 3.9.1.1 and improve recipe robustness
* Include version 3.9.1.1 as common benchmarking workload
* Fix compilation against recent glibc (detect spack installed libtirpc)
* Detect and handle failed compilation (upstream use make -i)
* WRF: PR changes round 1
fix build jobs
fix maintainers
fix pkgconfig dependency
use Executable to run compile stage
repair some overzealous autoformatting by black
* WRF: make recipe py26 compatible
* wrf: recipe review changes round 2
* more python 26 fixes
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The unattended install using the pre-compiled binaries (tl-install)
needs a .profile file or it goes in interactive mode blocking the
install process forever
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* add new version py-wavelets@1.1.1
* also update dependencies
* Update package.py
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* [dd4hep] switch to ninja generator to avoid running out of memory while compiling ddparsers
* [dd4hep] format
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* add new version py-tifffile@2020.10.1
* also update dependencies
* Update package.py
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* py-numpy: Add Fujitsu Fortran compiler to compiler type.
py-scipy: Specify Fujitsu to fcompiler types.
* Create patches applicable to each version.
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* Added guard for setting CUB_DIR to only when cuda variant is true
* Added support for OpenMP on OSX platforms
* Updated the way that LBANN, Hydrogen, and DiHydrogen handle
apple-clang with OpenMP and Clang installed on OS X via brew.
* Fixed bug in spec resolution
* Fixed merge conflict
* Fixed typo
* Fixed flake8
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* Added cuda support
* Added cuda and nvml variants
* Refined version conflict logic.
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Since spack no longer offers NWChem 6.6, there is no need of the patch lines.
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