This patch introduces a class LexSimplex that can currently be used to find the
lexicographically minimal rational point in an IntegerPolyhedron. This is a
series of patches leading to computing the lexicographically minimal integer
lattice point as well parametric lexicographic minimization.
Reviewed By: Groverkss
Differential Revision: https://reviews.llvm.org/D117437
Initialize some variables to zero to avoid a warning about them possibly being
used uninitialized. In actuality, they will never be used before initialization.
This patch replaces usage of FlatAffineConstraints in Simplex with
IntegerPolyhedron. This removes dependency of Simplex on FlatAffineConstraints
and puts it on IntegerPolyhedron, which is part of Presburger library.
Reviewed By: arjunp
Differential Revision: https://reviews.llvm.org/D116287
This is a purely mechanical patch moving some functionality out from the
`Simplex` class out into a `SimplexBase` class. This pavees the way for
a future patch adding support for lexicographic optimization with a class
`LexSimplex`, which will inherit from `SimplexBase`. Inheriting directly
from `Simplex` would bring many additional functions that would not work in
`LexSimplex` because it operates slighty differently from `Simplex`. So We
split out only the basic functionality it needs to inherit into `SimplexBase`.
Reviewed By: Groverkss
Differential Revision: https://reviews.llvm.org/D115831
Previously, the LogicalResult return value of restoreRow was being ignored in
places where it was expected to always be success. Instead, check the result
and go to an `llvm_unreachable` if it turns out to be failure.
The method that was previously used for computing dual variables was incorrect.
This was used in the integer emptiness check algorithm, where this bug could lead to much longer running times. (Due to the way it is used, this never results in an incorrect emptiness check result.)
This patch fixes the dual computation and adds some additional asserts that catch this bug, along with regression test cases that trigger the asserts when the incorrect dual computation is used.
Reviewed By: Groverkss
Differential Revision: https://reviews.llvm.org/D113803
This patch provides functionality for simplifying `PresburgerSet`s by checking if any `FlatAffineConstraints` in the set is contained in another, and removing such redundant FACs.
This is part of a series of patches to provide functionality for [integer set coalescing](http://impact.gforge.inria.fr/impact2015/papers/impact2015-verdoolaege.pdf) in MLIR.
Reviewed By: arjunp
Differential Revision: https://reviews.llvm.org/D110617
Previously, when adding a constraint to a Simplex that is already marked
as having no solutions (marked empty), the Simplex would be marked empty again,
and a second UnmarkEmpty entry would be pushed to the undo log. When rolling
back, Simplex should be unmarked empty only after rolling back past the
creation of the first constraint that made it empty.
Reviewed By: Groverkss
Differential Revision: https://reviews.llvm.org/D114613
Previously, the pivot function would only update the non-redundant rows when
pivoting. This is incorrect because in some cases, when rolling back past a
`detectRedundant` call, the basis being used could be different from that which
was used at the time of returning from the `detectRedundant` call. Therefore,
it is important to update the redundant rows as well during pivots. This could
also be triggered by pivots that occur when testing successive constraints for
being redundant in `detectRedundant` after some initial constraints are marked redundant.
Reviewed By: Groverkss
Differential Revision: https://reviews.llvm.org/D114614
This makes ignoring a result explicit by the user, and helps to prevent accidental errors with dropped results. Marking LogicalResult as no discard was always the intention from the beginning, but got lost along the way.
Differential Revision: https://reviews.llvm.org/D95841
With this, we have complete support for finding integer sample points in FlatAffineConstraints.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D95047
With this, we have complete support for emptiness checks. This also paves the way for future support to check if two FlatAffineConstraints are equal.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D94272
Subtraction is a foundational arithmetic operation that is often used when computing, for example, data transfer sets or cache hits. Since the result of subtraction need not be a convex polytope, a new class `PresburgerSet` is introduced to represent unions of convex polytopes.
Reviewed By: ftynse, bondhugula
Differential Revision: https://reviews.llvm.org/D87068
This patch adds the capability to perform constraint redundancy checks for `FlatAffineConstraints` using `Simplex`, via a new member function `FlatAffineConstraints::removeRedundantConstraints`. The pre-existing redundancy detection algorithm runs a full rational emptiness check for each inequality separately for checking redundancy. Leveraging the existing `Simplex` infrastructure, in this patch we have an algorithm for redundancy checks that can check each constraint by performing pivots on the tableau, which provides an alternative to running Fourier-Motzkin elimination for each constraint separately.
Differential Revision: https://reviews.llvm.org/D84935
This patch adds the capability to perform exact integer emptiness checks for FlatAffineConstraints using the General Basis Reduction algorithm (GBR). Previously, only a heuristic was available for emptiness checks, which was not guaranteed to always give a conclusive result.
This patch adds a `Simplex` class, which can be constructed using a `FlatAffineConstraints`, and can find an integer sample point (if one exists) using the GBR algorithm. Additionally, it adds two classes `Matrix` and `Fraction`, which are used by `Simplex`.
The integer emptiness check functionality can be accessed through the new `FlatAffineConstraints::isIntegerEmpty()` function, which runs the existing heuristic first and, if that proves to be inconclusive, runs the GBR algorithm to produce a conclusive result.
Differential Revision: https://reviews.llvm.org/D80860
