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- [x] spec.py can call out to the new concretizer
- [x] config.yaml now has an option to choose a concretizer (original, clingo)
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There are now three parts:
- `SpackSolverSetup`
- Spack-specific logic for generating constraints. Calls methods on
`AspTextGenerator` to set up the solver with a Spack problem. This
shouln't change much from solver backend to solver backend.
- ClingoDriver
- The solver driver provides methods for SolverSetup to generates an ASP
program, send it to `clingo` (run as an external tool), and parse the
output into function tuples suitable for `SpecBuilder`.
- The interface is generic and should not have to change much for a
driver for, say, the Clingo Python interface.
- SpecBuilder
- Builds Spack specs from function tuples parsed by the solver driver.
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The original implementation was difficult to read, as it only had
single-letter variable names. This converts all of them to descriptive
names, e.g., P -> Package, V -> Virtual/Version/Variant, etc.
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To handle unknown compilers propely in tests (and elsewhere), we need to
add unknown compilers from the spec to the list of possible compilers.
Rework how the compiler list is generated and includes compilers from
specs if the existence check is disabled.
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Specs like hdf5 ^mpi were unsatisfiable because we added a requierment
for `node("mpi").`. This can't be resolved because "mpi" is not a
package.
- [x] Introduce `virtual_node()`, which says *some* provider must be in
the DAG.
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This adds compiler flags to the ASP solve so that we can have conditions
based on them in the solve. But, it keeps order out of the solve to
avoid unneeded complexity and combinatorial explosions.
The solver determines which flags are on a spec, but the order is
determined by DAG precedence (childrens' flags take precedence over
parents' and are added on the right) and order (order flags were
specified on the command line is respected).
The solver is responsible for determining when to propagate flags, when
to inheit them from other nodes, when to take them from compiler
preferences, etc.
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Weight microarchitectures and prefers more rercent ones. Also disallow
nodes where the compiler does not support the selected target.
We should revisit this at some point as it seems like if I play around
with the compiler support for different architectures, the solver runs
very slowly. See notes in comments -- the bad case was gcc supporting
broadwell and skylake with clang maxing out at haswell.
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We didn't have a cardinality constraint for multi-valued variants, so the
solver wasn't filling them in.
- [x] add a requirement for at least one value for multi-valued variants
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Variants like `cpu_target` on `openblas` don't have defineed values, but
they have a default. Ensure that the default is always a possible value
for the solver.
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Spack was generating the same dependency connstraints twice in the output ASP:
```
declared_dependency("abinit", "hdf5", "link")
:- node("abinit"),
variant_value("abinit", "mpi", "True"),
variant_value("abinit", "mpi", "True").
```
This was because `AspFunction` was modifying itself when called.
- [x] fix `AspFunction` so that every call returns a new object
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- [x] Add support for packages.yaml and command-line compiler preferences.
- [x] Rework compiler version propagation to use optimization rather than
hard logic constraints
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Technically the ASP output order does not matter, but it's hard to diff
two different solve fomulations unless we order it.
- [x] make sure ASP output is emitted in a deterministic order (by
sorting all hash keys)
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This needs more thought, as I am pretty sure the weights are not correct.
Or, at least, I'm not convinced that they do what we want in all cases.
See note in concretize.lp.
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Solver now prefers newer versions like the old concretizer. Prefer
package preferences from packages.yaml, preferred=True, package
definition, and finally each version itself.
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Competition output only prints out one model, so we do not have to
unnecessarily parse all the non-optimal models. We'll just look at the
best model and bring that in.
In practice, this saves a lot of JSON parsing and spec construction time.
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Clingo actually has an option to output JSON -- use that instead of
parsing the raw otuput ourselves.
This also allows us to pick the best answer -- modify the parser to
*only* construct a spec for that one rather than building all of them
like we did before.
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- Instead of using default logic, handle variant defaults by minimizing
the number of non-default variants in the solution.
- This actually seems to be pretty fast, and it fixes the long-standing
issue that writing this:
spack install hdf5 ^mpich
will fail if you don't specify hdf5+mpi. With optimization and
allowing enums to be enumerated, the solver seems to be able to quickly
discover that +mpi is the only way hdf5 can depend on mpich, and it
forces the switch to be thrown.
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Add initial support for virtual dependencies. Solver now knows about all
virtuals and can choose one to resolve a dependency.
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Use '1 { version(x); version(y); version(z) } 1.' instead of declaring
conflicts for non-matching versions. This keeps the sense of version
clauses positive, which will allow them to be used more easily in
conditionals later.
Also refactor `spec_clauses()` method to return clauses that can be used
in conditions, etc. instead of just printing out facts.
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- single_value_variant may not be defined by the generated program. Mark
it to avoid warnings.
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- This handles setting the compiler and falling back to a default
compiler, as well as providing default values for compilers/compiler
versions.
- Versions still aren't quite right -- you can't properly override
versions on compiler specs.
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- Model architecture default settings and propagation off of variants
- Leverage ASP default logic to set architecture to default if it's not
set otherwise.
- Move logic out of Python and into concretize.lp as first-order rules.
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We are relying on default logic in the variant handling in that we set a
default value if we never see `variant_set(P, V, X)`.
- Move the logic for this into `concretize.lp` instead of generating it
for every package.
- For programs that don't have explicit variant settings, clingo warns
that variant_set(P, V, X) doesn't appear in any rule head, because a
setting is never generated.
- Specifically suppress this warning.
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- Add `concretize.lp` and `display.lp` as independent files
- Dump them instead of embedded strings
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