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When multiple loop transformation are defined in a loop's metadata, their order of execution is defined by the order of their respective passes in the pass pipeline. For instance, e.g. #pragma clang loop unroll_and_jam(enable) #pragma clang loop distribute(enable) is the same as #pragma clang loop distribute(enable) #pragma clang loop unroll_and_jam(enable) and will try to loop-distribute before Unroll-And-Jam because the LoopDistribute pass is scheduled after UnrollAndJam pass. UnrollAndJamPass only supports one inner loop, i.e. it will necessarily fail after loop distribution. It is not possible to specify another execution order. Also,t the order of passes in the pipeline is subject to change between versions of LLVM, optimization options and which pass manager is used. This patch adds 'followup' attributes to various loop transformation passes. These attributes define which attributes the resulting loop of a transformation should have. For instance, !0 = !{!0, !1, !2} !1 = !{!"llvm.loop.unroll_and_jam.enable"} !2 = !{!"llvm.loop.unroll_and_jam.followup_inner", !3} !3 = !{!"llvm.loop.distribute.enable"} defines a loop ID (!0) to be unrolled-and-jammed (!1) and then the attribute !3 to be added to the jammed inner loop, which contains the instruction to distribute the inner loop. Currently, in both pass managers, pass execution is in a fixed order and UnrollAndJamPass will not execute again after LoopDistribute. We hope to fix this in the future by allowing pass managers to run passes until a fixpoint is reached, use Polly to perform these transformations, or add a loop transformation pass which takes the order issue into account. For mandatory/forced transformations (e.g. by having been declared by #pragma omp simd), the user must be notified when a transformation could not be performed. It is not possible that the responsible pass emits such a warning because the transformation might be 'hidden' in a followup attribute when it is executed, or it is not present in the pipeline at all. For this reason, this patche introduces a WarnMissedTransformations pass, to warn about orphaned transformations. Since this changes the user-visible diagnostic message when a transformation is applied, two test cases in the clang repository need to be updated. To ensure that no other transformation is executed before the intended one, the attribute `llvm.loop.disable_nonforced` can be added which should disable transformation heuristics before the intended transformation is applied. E.g. it would be surprising if a loop is distributed before a #pragma unroll_and_jam is applied. With more supported code transformations (loop fusion, interchange, stripmining, offloading, etc.), transformations can be used as building blocks for more complex transformations (e.g. stripmining+stripmining+interchange -> tiling). Reviewed By: hfinkel, dmgreen Differential Revision: https://reviews.llvm.org/D49281 Differential Revision: https://reviews.llvm.org/D55288 git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@348944 91177308-0d34-0410-b5e6-96231b3b80d8
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.. _transformation-metadata:
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============================
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Code Transformation Metadata
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============================
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.. contents::
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:local:
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Overview
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========
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LLVM transformation passes can be controlled by attaching metadata to
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the code to transform. By default, transformation passes use heuristics
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to determine whether or not to perform transformations, and when doing
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so, other details of how the transformations are applied (e.g., which
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vectorization factor to select).
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Unless the optimizer is otherwise directed, transformations are applied
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conservatively. This conservatism generally allows the optimizer to
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avoid unprofitable transformations, but in practice, this results in the
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optimizer not applying transformations that would be highly profitable.
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Frontends can give additional hints to LLVM passes on which
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transformations they should apply. This can be additional knowledge that
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cannot be derived from the emitted IR, or directives passed from the
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user/programmer. OpenMP pragmas are an example of the latter.
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If any such metadata is dropped from the program, the code's semantics
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must not change.
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Metadata on Loops
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=================
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Attributes can be attached to loops as described in :ref:`llvm.loop`.
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Attributes can describe properties of the loop, disable transformations,
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force specific transformations and set transformation options.
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Because metadata nodes are immutable (with the exception of
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``MDNode::replaceOperandWith`` which is dangerous to use on uniqued
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metadata), in order to add or remove a loop attributes, a new ``MDNode``
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must be created and assigned as the new ``llvm.loop`` metadata. Any
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connection between the old ``MDNode`` and the loop is lost. The
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``llvm.loop`` node is also used as LoopID (``Loop::getLoopID()``), i.e.
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the loop effectively gets a new identifier. For instance,
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``llvm.mem.parallel_loop_access`` references the LoopID. Therefore, if
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the parallel access property is to be preserved after adding/removing
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loop attributes, any ``llvm.mem.parallel_loop_access`` reference must be
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updated to the new LoopID.
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Transformation Metadata Structure
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=================================
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Some attributes describe code transformations (unrolling, vectorizing,
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loop distribution, etc.). They can either be a hint to the optimizer
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that a transformation might be beneficial, instruction to use a specific
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option, , or convey a specific request from the user (such as
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``#pragma clang loop`` or ``#pragma omp simd``).
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If a transformation is forced but cannot be carried-out for any reason,
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an optimization-missed warning must be emitted. Semantic information
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such as a transformation being safe (e.g.
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``llvm.mem.parallel_loop_access``) can be unused by the optimizer
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without generating a warning.
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Unless explicitly disabled, any optimization pass may heuristically
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determine whether a transformation is beneficial and apply it. If
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metadata for another transformation was specified, applying a different
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transformation before it might be inadvertent due to being applied on a
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different loop or the loop not existing anymore. To avoid having to
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explicitly disable an unknown number of passes, the attribute
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``llvm.loop.disable_nonforced`` disables all optional, high-level,
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restructuring transformations.
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The following example avoids the loop being altered before being
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vectorized, for instance being unrolled.
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.. code-block:: llvm
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br i1 %exitcond, label %for.exit, label %for.header, !llvm.loop !0
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...
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!0 = distinct !{!0, !1, !2}
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!1 = !{!"llvm.loop.vectorize.enable", i1 true}
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!2 = !{!"llvm.loop.disable_nonforced"}
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After a transformation is applied, follow-up attributes are set on the
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transformed and/or new loop(s). This allows additional attributes
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including followup-transformations to be specified. Specifying multiple
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transformations in the same metadata node is possible for compatibility
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reasons, but their execution order is undefined. For instance, when
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``llvm.loop.vectorize.enable`` and ``llvm.loop.unroll.enable`` are
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specified at the same time, unrolling may occur either before or after
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vectorization.
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As an example, the following instructs a loop to be vectorized and only
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then unrolled.
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.. code-block:: llvm
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!0 = distinct !{!0, !1, !2, !3}
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!1 = !{!"llvm.loop.vectorize.enable", i1 true}
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!2 = !{!"llvm.loop.disable_nonforced"}
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!3 = !{!"llvm.loop.vectorize.followup_vectorized", !{"llvm.loop.unroll.enable"}}
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If, and only if, no followup is specified, the pass may add attributes itself.
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For instance, the vectorizer adds a ``llvm.loop.isvectorized`` attribute and
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all attributes from the original loop excluding its loop vectorizer
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attributes. To avoid this, an empty followup attribute can be used, e.g.
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.. code-block:: llvm
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!3 = !{!"llvm.loop.vectorize.followup_vectorized"}
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The followup attributes of a transformation that cannot be applied will
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never be added to a loop and are therefore effectively ignored. This means
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that any followup-transformation in such attributes requires that its
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prior transformations are applied before the followup-transformation.
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The user should receive a warning about the first transformation in the
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transformation chain that could not be applied if it a forced
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transformation. All following transformations are skipped.
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Pass-Specific Transformation Metadata
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=====================================
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Transformation options are specific to each transformation. In the
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following, we present the model for each LLVM loop optimization pass and
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the metadata to influence them.
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Loop Vectorization and Interleaving
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-----------------------------------
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Loop vectorization and interleaving is interpreted as a single
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transformation. It is interpreted as forced if
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``!{"llvm.loop.vectorize.enable", i1 true}`` is set.
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Assuming the pre-vectorization loop is
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.. code-block:: c
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for (int i = 0; i < n; i+=1) // original loop
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Stmt(i);
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then the code after vectorization will be approximately (assuming an
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SIMD width of 4):
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.. code-block:: c
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int i = 0;
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if (rtc) {
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for (; i + 3 < n; i+=4) // vectorized/interleaved loop
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Stmt(i:i+3);
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}
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for (; i < n; i+=1) // epilogue loop
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Stmt(i);
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where ``rtc`` is a generated runtime check.
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``llvm.loop.vectorize.followup_vectorized`` will set the attributes for
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the vectorized loop. If not specified, ``llvm.loop.isvectorized`` is
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combined with the original loop's attributes to avoid it being
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vectorized multiple times.
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``llvm.loop.vectorize.followup_epilogue`` will set the attributes for
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the remainder loop. If not specified, it will have the original loop's
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attributes combined with ``llvm.loop.isvectorized`` and
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``llvm.loop.unroll.runtime.disable`` (unless the original loop already
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has unroll metadata).
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The attributes specified by ``llvm.loop.vectorize.followup_all`` are
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added to both loops.
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When using a follow-up attribute, it replaces any automatically deduced
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attributes for the generated loop in question. Therefore it is
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recommended to add ``llvm.loop.isvectorized`` to
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``llvm.loop.vectorize.followup_all`` which avoids that the loop
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vectorizer tries to optimize the loops again.
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Loop Unrolling
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--------------
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Unrolling is interpreted as forced any ``!{!"llvm.loop.unroll.enable"}``
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metadata or option (``llvm.loop.unroll.count``, ``llvm.loop.unroll.full``)
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is present. Unrolling can be full unrolling, partial unrolling of a loop
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with constant trip count or runtime unrolling of a loop with a trip
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count unknown at compile-time.
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If the loop has been unrolled fully, there is no followup-loop. For
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partial/runtime unrolling, the original loop of
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.. code-block:: c
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for (int i = 0; i < n; i+=1) // original loop
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Stmt(i);
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is transformed into (using an unroll factor of 4):
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.. code-block:: c
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int i = 0;
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for (; i + 3 < n; i+=4) // unrolled loop
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Stmt(i);
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Stmt(i+1);
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Stmt(i+2);
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Stmt(i+3);
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}
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for (; i < n; i+=1) // remainder loop
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Stmt(i);
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``llvm.loop.unroll.followup_unrolled`` will set the loop attributes of
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the unrolled loop. If not specified, the attributes of the original loop
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without the ``llvm.loop.unroll.*`` attributes are copied and
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``llvm.loop.unroll.disable`` added to it.
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``llvm.loop.unroll.followup_remainder`` defines the attributes of the
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remainder loop. If not specified the remainder loop will have no
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attributes. The remainder loop might not be present due to being fully
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unrolled in which case this attribute has no effect.
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Attributes defined in ``llvm.loop.unroll.followup_all`` are added to the
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unrolled and remainder loops.
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To avoid that the partially unrolled loop is unrolled again, it is
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recommended to add ``llvm.loop.unroll.disable`` to
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``llvm.loop.unroll.followup_all``. If no follow-up attribute specified
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for a generated loop, it is added automatically.
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Unroll-And-Jam
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--------------
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Unroll-and-jam uses the following transformation model (here with an
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unroll factor if 2). Currently, it does not support a fallback version
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when the transformation is unsafe.
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.. code-block:: c
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for (int i = 0; i < n; i+=1) { // original outer loop
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Fore(i);
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for (int j = 0; j < m; j+=1) // original inner loop
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SubLoop(i, j);
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Aft(i);
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}
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.. code-block:: c
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int i = 0;
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for (; i + 1 < n; i+=2) { // unrolled outer loop
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Fore(i);
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Fore(i+1);
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for (int j = 0; j < m; j+=1) { // unrolled inner loop
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SubLoop(i, j);
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SubLoop(i+1, j);
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}
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Aft(i);
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Aft(i+1);
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}
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for (; i < n; i+=1) { // remainder outer loop
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Fore(i);
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for (int j = 0; j < m; j+=1) // remainder inner loop
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SubLoop(i, j);
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Aft(i);
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}
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``llvm.loop.unroll_and_jam.followup_outer`` will set the loop attributes
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of the unrolled outer loop. If not specified, the attributes of the
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original outer loop without the ``llvm.loop.unroll.*`` attributes are
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copied and ``llvm.loop.unroll.disable`` added to it.
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``llvm.loop.unroll_and_jam.followup_inner`` will set the loop attributes
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of the unrolled inner loop. If not specified, the attributes of the
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original inner loop are used unchanged.
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``llvm.loop.unroll_and_jam.followup_remainder_outer`` sets the loop
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attributes of the outer remainder loop. If not specified it will not
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have any attributes. The remainder loop might not be present due to
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being fully unrolled.
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``llvm.loop.unroll_and_jam.followup_remainder_inner`` sets the loop
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attributes of the inner remainder loop. If not specified it will have
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the attributes of the original inner loop. It the outer remainder loop
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is unrolled, the inner remainder loop might be present multiple times.
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Attributes defined in ``llvm.loop.unroll_and_jam.followup_all`` are
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added to all of the aforementioned output loops.
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To avoid that the unrolled loop is unrolled again, it is
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recommended to add ``llvm.loop.unroll.disable`` to
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``llvm.loop.unroll_and_jam.followup_all``. It suppresses unroll-and-jam
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as well as an additional inner loop unrolling. If no follow-up
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attribute specified for a generated loop, it is added automatically.
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Loop Distribution
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-----------------
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The LoopDistribution pass tries to separate vectorizable parts of a loop
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from the non-vectorizable part (which otherwise would make the entire
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loop non-vectorizable). Conceptually, it transforms a loop such as
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.. code-block:: c
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for (int i = 1; i < n; i+=1) { // original loop
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A[i] = i;
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B[i] = 2 + B[i];
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C[i] = 3 + C[i - 1];
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}
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into the following code:
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.. code-block:: c
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if (rtc) {
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for (int i = 1; i < n; i+=1) // coincident loop
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A[i] = i;
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for (int i = 1; i < n; i+=1) // coincident loop
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B[i] = 2 + B[i];
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for (int i = 1; i < n; i+=1) // sequential loop
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C[i] = 3 + C[i - 1];
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} else {
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for (int i = 1; i < n; i+=1) { // fallback loop
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A[i] = i;
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B[i] = 2 + B[i];
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C[i] = 3 + C[i - 1];
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}
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}
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where ``rtc`` is a generated runtime check.
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``llvm.loop.distribute.followup_coincident`` sets the loop attributes of
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all loops without loop-carried dependencies (i.e. vectorizable loops).
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There might be more than one such loops. If not defined, the loops will
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inherit the original loop's attributes.
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``llvm.loop.distribute.followup_sequential`` sets the loop attributes of the
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loop with potentially unsafe dependencies. There should be at most one
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such loop. If not defined, the loop will inherit the original loop's
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attributes.
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``llvm.loop.distribute.followup_fallback`` defines the loop attributes
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for the fallback loop, which is a copy of the original loop for when
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loop versioning is required. If undefined, the fallback loop inherits
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all attributes from the original loop.
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Attributes defined in ``llvm.loop.distribute.followup_all`` are added to
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all of the aforementioned output loops.
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It is recommended to add ``llvm.loop.disable_nonforced`` to
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``llvm.loop.distribute.followup_fallback``. This avoids that the
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fallback version (which is likely never executed) is further optimzed
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which would increase the code size.
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Versioning LICM
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---------------
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The pass hoists code out of loops that are only loop-invariant when
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dynamic conditions apply. For instance, it transforms the loop
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.. code-block:: c
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for (int i = 0; i < n; i+=1) // original loop
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A[i] = B[0];
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into:
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.. code-block:: c
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if (rtc) {
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auto b = B[0];
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for (int i = 0; i < n; i+=1) // versioned loop
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A[i] = b;
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} else {
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for (int i = 0; i < n; i+=1) // unversioned loop
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A[i] = B[0];
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}
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The runtime condition (``rtc``) checks that the array ``A`` and the
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element `B[0]` do not alias.
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Currently, this transformation does not support followup-attributes.
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Loop Interchange
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----------------
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Currently, the ``LoopInterchange`` pass does not use any metadata.
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Ambiguous Transformation Order
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==============================
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If there multiple transformations defined, the order in which they are
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executed depends on the order in LLVM's pass pipeline, which is subject
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to change. The default optimization pipeline (anything higher than
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``-O0``) has the following order.
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When using the legacy pass manager:
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- LoopInterchange (if enabled)
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- SimpleLoopUnroll/LoopFullUnroll (only performs full unrolling)
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- VersioningLICM (if enabled)
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- LoopDistribute
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- LoopVectorizer
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- LoopUnrollAndJam (if enabled)
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- LoopUnroll (partial and runtime unrolling)
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When using the legacy pass manager with LTO:
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- LoopInterchange (if enabled)
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- SimpleLoopUnroll/LoopFullUnroll (only performs full unrolling)
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- LoopVectorizer
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- LoopUnroll (partial and runtime unrolling)
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When using the new pass manager:
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- SimpleLoopUnroll/LoopFullUnroll (only performs full unrolling)
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- LoopDistribute
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- LoopVectorizer
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- LoopUnrollAndJam (if enabled)
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- LoopUnroll (partial and runtime unrolling)
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Leftover Transformations
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========================
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Forced transformations that have not been applied after the last
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transformation pass should be reported to the user. The transformation
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passes themselves cannot be responsible for this reporting because they
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might not be in the pipeline, there might be multiple passes able to
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apply a transformation (e.g. ``LoopInterchange`` and Polly) or a
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transformation attribute may be 'hidden' inside another passes' followup
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attribute.
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The pass ``-transform-warning`` (``WarnMissedTransformationsPass``)
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emits such warnings. It should be placed after the last transformation
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pass.
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The current pass pipeline has a fixed order in which transformations
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passes are executed. A transformation can be in the followup of a pass
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that is executed later and thus leftover. For instance, a loop nest
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cannot be distributed and then interchanged with the current pass
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pipeline. The loop distribution will execute, but there is no loop
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interchange pass following such that any loop interchange metadata will
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be ignored. The ``-transform-warning`` should emit a warning in this
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case.
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Future versions of LLVM may fix this by executing transformations using
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a dynamic ordering.
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