* py-pyfiglet:new recipe
* Update var/spack/repos/builtin/packages/py-pyfiglet/package.py
Co-authored-by: Adam J. Stewart <ajstewart426@gmail.com>
* py-pyfiglet: use pypi url
Co-authored-by: Adam J. Stewart <ajstewart426@gmail.com>
fixes#20736
Before this one line fix we were erroneously deducing
that dependency conditions hold even if a package
was external.
This may result in answer sets that contain imposed
conditions on a node without the node being present
in the DAG, hence #20736.
fixes#20611
The conflict was triggered by an invalid value of the
'scheduler' variant. This causes Spack to error when libyogrt
facts are validated by the ASP-based concretizer.
At some point in the past, the skip_patch argument was removed
from the call to package.do_install() this broke the --skip-patch
flag on the dev-build command.
There's two issues with hip where it tries to autodetect the patch
version number from git (when installed), but it does not check if it
even is inside of a git repo. The result is we end up with a shared lib
with a trailing dash in the library suffix: `libamd64.so.x.y.z-`, which
confuses GCC. The patch tries to check if the `.git` folder exists, and
if it does not, it handles version numbering the same as when git was
not installed previously.
* opencl-c-headers: add new version 2020.12.18
* opencl-clhpp: add new version 2.0.13
* opencl-headers: now supports OpenCL 3.0 with new versions of opencl-c-headers and opencl-clhpp
* ocl-icd: add new version 2.2.14 add now can provide OpenCL 3.0
PaRSEC: the Parallel Runtime Scheduler and Execution Controller for micro-tasks on distributed heterogeneous systems.
Signed-off-by: Aurelien Bouteiller <bouteill@icl.utk.edu>
* py-tensorflow: 2.4.0 and dependency updates
* minor version updates
* fix numpy dependency
* dependency rework: compatible release issues, start to clarify cuda versions
* --incompatible_no_support_tools_in_action_inputs was removed in bazel 3.6
* adjustment to versions of cuda dependency, also make sure that
patches/filters still apply to certain release trains.
* python 3.8 and tf < 2.2 have issues
* missed py-grpcio version bump
Set up environment and dependent packages properly when building
with intel-oneapi-mpi as a dependency MPI provider (e.g. point to
mpicc compiler wrapper).
