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