Concretization Settings (concretizer.yaml)

The concretizer.yaml configuration file allows to customize aspects of the algorithm used to select the dependencies you install. The default configuration is the following:

# -------------------------------------------------------------------------
# This is the default spack configuration file.
#
# Settings here are versioned with Spack and are intended to provide
# sensible defaults out of the box. Spack maintainers should edit this
# file to keep it current.
#
# Users can override these settings by editing
# `$SPACK_ROOT/etc/spack/concretizer.yaml`, `~/.spack/concretizer.yaml`,
# or by adding a `concretizer:` section to an environment.
# -------------------------------------------------------------------------
concretizer:
  # Whether to consider installed packages or packages from buildcaches when
  # concretizing specs. If `true`, we'll try to use as many installs/binaries
  # as possible, rather than building. If `false`, we'll always give you a fresh
  # concretization. If `dependencies`, we'll only reuse dependencies but
  # give you a fresh concretization for your root specs.
  reuse: dependencies
  # Options that tune which targets are considered for concretization. The
  # concretization process is very sensitive to the number targets, and the time
  # needed to reach a solution increases noticeably with the number of targets
  # considered.
  targets:
    # Determine whether we want to target specific or generic
    # microarchitectures. Valid values are: "microarchitectures" or "generic".
    # An example of "microarchitectures" would be "skylake" or "bulldozer",
    # while an example of "generic" would be "aarch64" or "x86_64_v4".
    granularity: microarchitectures
    # If "false" allow targets that are incompatible with the current host (for
    # instance concretize with target "icelake" while running on "haswell").
    # If "true" only allow targets that are compatible with the host.
    host_compatible: true
  # When "true" concretize root specs of environments together, so that each unique
  # package in an environment corresponds to one concrete spec. This ensures
  # environments can always be activated. When "false" perform concretization separately
  # on each root spec, allowing different versions and variants of the same package in
  # an environment.
  unify: true
  # Option to deal with possible duplicate nodes (i.e. different nodes from the same package) in the DAG.
  duplicates:
    # "none": allows a single node for any package in the DAG.
    # "minimal": allows the duplication of 'build-tools' nodes only (e.g. py-setuptools, cmake etc.)
    # "full" (experimental): allows separation of the entire build-tool stack (e.g. the entire "cmake" subDAG)
    strategy: minimal

Reuse already installed packages

The reuse attribute controls whether Spack will prefer to use installed packages (true), or whether it will do a “fresh” installation and prefer the latest settings from package.py files and packages.yaml (false). You can use:

% spack install --reuse <spec>

to enable reuse for a single installation, and you can use:

spack install --fresh <spec>

to do a fresh install if reuse is enabled by default. reuse: dependencies is the default.

Selection of the target microarchitectures

The options under the targets attribute control which targets are considered during a solve. Currently the options in this section are only configurable from the concretizer.yaml file and there are no corresponding command line arguments to enable them for a single solve.

The granularity option can take two possible values: microarchitectures and generic. If set to:

concretizer:
  targets:
    granularity: microarchitectures

Spack will consider all the microarchitectures known to archspec to label nodes for compatibility. If instead the option is set to:

concretizer:
  targets:
    granularity: generic

Spack will consider only generic microarchitectures. For instance, when running on an Haswell node, Spack will consider haswell as the best target in the former case and x86_64_v3 as the best target in the latter case.

The host_compatible option is a Boolean option that determines whether or not the microarchitectures considered during the solve are constrained to be compatible with the host Spack is currently running on. For instance, if this option is set to true, a user cannot concretize for target=icelake while running on an Haswell node.

Duplicate nodes

The duplicates attribute controls whether the DAG can contain multiple configurations of the same package. This is mainly relevant for build dependencies, which may have their version pinned by some nodes, and thus be required at different versions by different nodes in the same DAG.

The strategy option controls how the solver deals with duplicates. If the value is none, then a single configuration per package is allowed in the DAG. This means, for instance, that only a single cmake or a single py-setuptools version is allowed. The result would be a slightly faster concretization, at the expense of making a few specs unsolvable.

If the value is minimal Spack will allow packages tagged as build-tools to have duplicates. This allows, for instance, to concretize specs whose nodes require different, and incompatible, ranges of some build tool. For instance, in the figure below the latest py-shapely requires a newer py-setuptools, while py-numpy still needs an older version:

_images/shapely_duplicates.svg

Up to Spack v0.20 duplicates:strategy:none was the default (and only) behavior. From Spack v0.21 the default behavior is duplicates:strategy:minimal.