Since #27185, the cuda_arch variant values are conditional on +cuda. This means that for -cuda specs, the installation fails with:
```
==> acts: Executing phase: 'cmake'
==> Error: KeyError: 'cuda_arch'
/home/wdconinc/git/spack/var/spack/repos/builtin/packages/acts/package.py:222, in cmake_args:
219 log_failure_threshold = spec.variants['log_failure_threshold'].value
220 args.append("-DACTS_LOG_FAILURE_THRESHOLD={0}".format(log_failure_threshold))
221
>> 222 cuda_arch = spec.variants['cuda_arch'].value
223 if cuda_arch != 'none':
224 args.append('-DCUDA_FLAGS=-arch=sm_{0}'.format(cuda_arch[0]))
225
```
* new package: py-tensorflow-datasets
- includes new dependency package: py-tensorflow-metadata
* Update var/spack/repos/builtin/packages/py-tensorflow-datasets/package.py
Co-authored-by: Adam J. Stewart <ajstewart426@gmail.com>
* Update var/spack/repos/builtin/packages/py-tensorflow-metadata/package.py
Co-authored-by: Adam J. Stewart <ajstewart426@gmail.com>
Co-authored-by: Adam J. Stewart <ajstewart426@gmail.com>
* Added gdb Dependency
When using spack to install cgdb, a spack-built gdb is necessary to
avoid dynamic link errors.
- Added maintainer: tuxfan
- Set preferred to 'master' (best version for spack currently)
* Update: The gdb dependency added by this PR is for runtime
Co-authored-by: Bernhard Kaindl <43588962+bernhardkaindl@users.noreply.github.com>
This adds support in spack for both build/install tests (spack install
--run-tests) and post-install smoke tests (spack test run).
Hpctoolkit itself only recently added tests, so for now, this only
applies to branch master.
To use this, you can "spack install intel-oneapi-compilers" and then
"spack compiler add" the new compiler. You would need to install with
"spack install ginkgo+oneapi%dpcpp"
- Use .tar.gz archive
- Update 2.3.3 to use .tar.gz archive (and update checksum)
- autoreconf dependency is no-longer required
- The new version depends on gperf
