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This could be simplified further, but Hal has a specific feature for
ignoring TTI, and so I preserved that.
Also, I needed to use it because a number of tests fail when switching
from a null TTI to the NoTTI nonce implementation. That seems suspicious
to me and so may be something that you need to look into Hal. I worked
it by preserving the old behavior for these tests with the flag that
ignores all target info.
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longer would violate any dependency layering and it is in fact an
analysis. =]
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interface.
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into their new header subdirectory: include/llvm/IR. This matches the
directory structure of lib, and begins to correct a long standing point
of file layout clutter in LLVM.
There are still more header files to move here, but I wanted to handle
them in separate commits to make tracking what files make sense at each
layer easier.
The only really questionable files here are the target intrinsic
tablegen files. But that's a battle I'd rather not fight today.
I've updated both CMake and Makefile build systems (I think, and my
tests think, but I may have missed something).
I've also re-sorted the includes throughout the project. I'll be
committing updates to Clang, DragonEgg, and Polly momentarily.
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For the time being this includes only some dummy test cases. Once the
generic implementation of the intrinsics cost function does something other
than assuming scalarization in all cases, or some target specializes the
interface, some real test cases can be added.
Also, for consistency, I changed the type of IID from unsigned to Intrinsic::ID
in a few other places.
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and not the return type, which is void. A number of test
cases fail after adding the assertion in TTImpl.
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Sooooo many of these had incorrect or strange main module includes.
I have manually inspected all of these, and fixed the main module
include to be the nearest plausible thing I could find. If you own or
care about any of these source files, I encourage you to take some time
and check that these edits were sensible. I can't have broken anything
(I strictly added headers, and reordered them, never removed), but they
may not be the headers you'd really like to identify as containing the
API being implemented.
Many forward declarations and missing includes were added to a header
files to allow them to parse cleanly when included first. The main
module rule does in fact have its merits. =]
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When two instructions are combined into a vector instruction,
the resulting instruction must have the most-conservative flags.
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For now, this uses 8 on-stack elements. I'll need to do some profiling
to see if this is the best number.
Pointed out by Jakob in post-commit review.
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Iterating over the children of each node in the potential vectorization
plan must happen in a deterministic order (because it affects which children
are erased when two children conflict). There was no need for this data
structure to be a map in the first place, so replacing it with a vector
is a small change.
I believe that this was the last remaining instance if iterating over the
elements of a Dense* container where the iteration order could matter.
There are some remaining iterations over std::*map containers where the order
might matter, but so long as the Value* for instructions in a block increase
with the order of the instructions in the block (or decrease) monotonically,
then this will appear to be deterministic.
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Don't choose a vectorization plan containing only shuffles and
vector inserts/extracts. Due to inperfections in the cost model,
these can lead to infinite recusion.
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This fixes another infinite recursion case when using target costs.
We can only replace insert element input chains that are pure (end
with inserting into an undef).
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The old checking code, which assumed that input shuffles and insert-elements
could always be folded (and thus were free) is too simple.
This can only happen in special circumstances.
Using the simple check caused infinite recursion.
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The pass would previously assert when trying to compute the cost of
compare instructions with illegal vector types (like struct pointers).
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This fixes a bug where shuffles were being fused such that the
resulting input types were not legal on the target. This would
occur only when both inputs and dependencies were also foldable
operations (such as other shuffles) and there were other connected
pairs in the same block.
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the depth heuristic.
When target cost information is available, compute explicit costs of inserting and
extracting values from vectors. At this point, all costs are estimated using the
target information, and the chain-depth heuristic is not needed. As a result, it is now, by
default, disabled when using target costs.
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When target costs are available, use them to account for the costs of
shuffles on internal edges of the DAG of candidate pairs.
Because the shuffle costs here are currently for only the internal edges,
the current target cost model is trivial, and the chain depth requirement
is still in place, I don't yet have an easy test
case. Nevertheless, by looking at the debug output, it does seem to do the right
think to the effective "size" of each DAG of candidate pairs.
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BBVectorize would, except for loads and stores, always fuse instructions
so that the first instruction (in the current source order) would always
represent the low part of the input vectors and the second instruction
would always represent the high part. This lead to too many shuffles
being produced because sometimes the opposite order produces fewer of them.
With this change, BBVectorize tracks the kind of pair connections that form
the DAG of candidate pairs, and uses that information to reorder the pairs to
avoid excess shuffles. Using this information, a future commit will be able
to add VTTI-based shuffle costs to the pair selection procedure. Importantly,
the number of remaining shuffles can now be estimated during pair selection.
There are some trivial instruction reorderings in the test cases, and one
simple additional test where we certainly want to do a reordering to
avoid an unnecessary shuffle.
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Instead of recomputing relative pointer information just prior to fusing,
cache this information (which also needs to be computed during the
candidate-pair selection process). This cuts down on the total number of
SE queries made, and also is a necessary intermediate step on the road toward
including shuffle costs in the pair selection procedure.
No functionality change is intended.
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We need to make sure that we take the correct load/store alignment
when the inputs are flipped.
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Stop propagating the FlipMemInputs variable into the routines that
create the replacement instructions. Instead, just flip the arguments
of those routines. This allows for some associated cleanup (not all
of which is done here). No functionality change is intended.
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SE was being called during the instruction-fusion process (when the result
is unreliable, and thus ignored). No functionality change is intended.
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The monolithic interface for instruction costs has been split into
several functions. This is the corresponding change. No functionality
change is intended.
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This change reflects VTTI refactoring; no functionality change intended.
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Once vector-of-pointer support works, then this can be reverted.
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This is needed so that perl's SHA can be compiled (otherwise
BBVectorize takes far too long to find its fixed point).
I'll try to come up with a reduced test case.
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This is the first of several steps to incorporate information from the new
TargetTransformInfo infrastructure into BBVectorize. Two things are done here:
1. Target information is used to determine if it is profitable to fuse two
instructions. This means that the cost of the vector operation must not
be more expensive than the cost of the two original operations. Pairs that
are not profitable are no longer considered (because current cost information
is incomplete, for intrinsics for example, equal-cost pairs are still
considered).
2. The 'cost savings' computed for the profitability check are also used to
rank the DAGs that represent the potential vectorization plans. Specifically,
for nodes of non-trivial depth, the cost savings is used as the node
weight.
The next step will be to incorporate the shuffle costs into the DAG weighting;
this will give the edges of the DAG weights as well. Once that is done, when
target information is available, we should be able to dispense with the
depth heuristic.
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Unreachable blocks can have invalid instructions. For example,
jump threading can produce self-referential instructions in
unreachable blocks. Also, we should not be spending time
optimizing unreachable code. Fixes PR14133.
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See: http://en.wikipedia.org/wiki/If_and_only_if Commit 164767
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This disables malloc-specific optimization when -fno-builtin (or -ffreestanding)
is specified. This has been a problem for a long time but became more severe
with the recent memory builtin improvements.
Since the memory builtin functions are used everywhere, this required passing
TLI in many places. This means that functions that now have an optional TLI
argument, like RecursivelyDeleteTriviallyDeadFunctions, won't remove dead
mallocs anymore if the TLI argument is missing. I've updated most passes to do
the right thing.
Fixes PR13694 and probably others.
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When both a load/store and its address computation are being vectorized, it can
happen that the address-computation vectorization destroys SCEV's ability
to analyize the relative pointer offsets. As a result (like with the aliasing
analysis info), we need to precompute the necessary information prior to
instruction fusing.
This was found during stress testing (running through the test suite with a very
low required chain length); unfortunately, I don't have a small test case.
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A shuffle mask will always be a constant, but I did not realize that
when I originally wrote the code.
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The original algorithm only used recursive pair fusion of equal-length
types. This is now extended to allow pairing of any types that share
the same underlying scalar type. Because we would still generally
prefer the 2^n-length types, those are formed first. Then a second
set of iterations form the non-2^n-length types.
Also, a call to SimplifyInstructionsInBlock has been added after each
pairing iteration. This takes care of DCE (and a few other things)
that make the following iterations execute somewhat faster. For the
same reason, some of the simple shuffle-combination cases are now
handled internally.
There is some additional refactoring work to be done, but I've had
many requests for this feature, so additional refactoring will come
soon in future commits (as will additional test cases).
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Instruction::isSameOperationAs.
Maintaining this kind of checking in different places is dangerous, extending
Instruction::isSameOperationAs consolidates this logic into one place. Here
I've added an optional flags parameter and two flags that are important for
vectorization: CompareIgnoringAlignment and CompareUsingScalarTypes.
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integer types.
These are used as the result of comparisons, and often handled differently from larger integer types.
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instructions.
The present implementation handles only TBAA and FP metadata, discarding everything else.
For debug metadata, the current behavior is maintained (the debug metadata associated with
one of the instructions will be kept, discarding that attached to the other).
This should address PR 13040.
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Target specific types should not be vectorized. As a practical matter,
these types are already register matched (at least in the x86 case),
and codegen does not always work correctly (at least in the ppc case,
and this is not worth fixing because ppc_fp128 is currently broken and
will probably go away soon).
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suggested by Duncan).
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When vectorizing pointer types it is important to realize that potential
pairs cannot be connected via the address pointer argument of a load or store.
This is because even after vectorization, the address is still a scalar because
the address of the higher half of the pair is implicit from the address of the
lower half (it need not be, and should not be, explicitly computed).
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modify it.
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of the BBVectorizePass without using command line option. As pointed out
by Hal, we can ask the TargetLoweringInfo for the architecture specific
VectorizeConfig to perform vectorizing with architecture specific
information.
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