Commit Graph

549 Commits

Author SHA1 Message Date
Tung D. Le
05c6c648ec [MLIR] [affine-loop-fusion] Fix a bug about non-result ops in affine-loop-fusion
This patch fixes the following bug when calling --affine-loop-fusion

Input program:
 ```mlir
func @should_not_fuse_since_top_level_non_affine_non_result_users(
    %in0 : memref<32xf32>, %in1 : memref<32xf32>) {
  %c0 = constant 0 : index
  %cst_0 = constant 0.000000e+00 : f32

  affine.for %d = 0 to 32 {
    %lhs = affine.load %in0[%d] : memref<32xf32>
    %rhs = affine.load %in1[%d] : memref<32xf32>
    %add = addf %lhs, %rhs : f32
    affine.store %add, %in0[%d] : memref<32xf32>
  }
  store %cst_0, %in0[%c0] : memref<32xf32>
  affine.for %d = 0 to 32 {
    %lhs = affine.load %in0[%d] : memref<32xf32>
    %rhs = affine.load %in1[%d] : memref<32xf32>
    %add = addf %lhs, %rhs: f32
    affine.store %add, %in0[%d] : memref<32xf32>
  }
  return
}
```

call --affine-loop-fusion, we got an incorrect output:

```mlir
func @should_not_fuse_since_top_level_non_affine_non_result_users(%arg0: memref<32xf32>, %arg1: memref<32xf32>) {
  %c0 = constant 0 : index
  %cst = constant 0.000000e+00 : f32
  store %cst, %arg0[%c0] : memref<32xf32>
  affine.for %arg2 = 0 to 32 {
    %0 = affine.load %arg0[%arg2] : memref<32xf32>
    %1 = affine.load %arg1[%arg2] : memref<32xf32>
    %2 = addf %0, %1 : f32
    affine.store %2, %arg0[%arg2] : memref<32xf32>
    %3 = affine.load %arg0[%arg2] : memref<32xf32>
    %4 = affine.load %arg1[%arg2] : memref<32xf32>
    %5 = addf %3, %4 : f32
    affine.store %5, %arg0[%arg2] : memref<32xf32>
  }
  return
}
```

This happened because when analyzing the source and destination nodes,
affine loop fusion ignored non-result ops sandwitched between them. In
other words, the MemRefDependencyGraph in the affine loop fusion ignored
these non-result ops.

This patch solves the issue by adding these non-result ops to the
MemRefDependencyGraph.

Reviewed By: bondhugula

Differential Revision: https://reviews.llvm.org/D95668
2021-02-06 13:30:16 +05:30
Alex Zinenko
5b91060dcc [mlir] Apply source materialization in case of transitive conversion
In dialect conversion infrastructure, source materialization applies as part of
the finalization procedure to results of the newly produced operations that
replace previously existing values with values having a different type.
However, such operations may be created to replace operations created in other
patterns. At this point, it is possible that the results of the _original_
operation are still in use and have mismatching types, but the results of the
_intermediate_ operation that performed the type change are not in use leading
to the absence of source materialization. For example,

  %0 = dialect.produce : !dialect.A
  dialect.use %0 : !dialect.A

can be replaced with

  %0 = dialect.other : !dialect.A
  %1 = dialect.produce : !dialect.A  // replaced, scheduled for removal
  dialect.use %1 : !dialect.A

and then with

  %0 = dialect.final : !dialect.B
  %1 = dialect.other : !dialect.A    // replaced, scheduled for removal
  %2 = dialect.produce : !dialect.A  // replaced, scheduled for removal
  dialect.use %2 : !dialect.A

in the same rewriting, but only the %1->%0 replacement is currently considered.

Change the logic in dialect conversion to look up all values that were replaced
by the given value and performing source materialization if any of those values
is still in use with mismatching types. This is performed by computing the
inverse value replacement mapping. This arguably expensive manipulation is
performed only if there were some type-changing replacements. An alternative
could be to consider all replaced operations and not only those that resulted
in type changes, but it would harm pattern-level composability: the pattern
that performed the non-type-changing replacement would have to be made aware of
the type converter in order to call the materialization hook.

Reviewed By: rriddle

Differential Revision: https://reviews.llvm.org/D95626
2021-02-04 11:15:11 +01:00
Mehdi Amini
a1d5bdf819 Make the folder more robust against op fold() methods that generate a type mismatch
We could extend this with an interface to allow dialect to perform a type
conversion, but that would make the folder creating operation which isn't
the case at the moment, and isn't necessarily always desirable.

Reviewed By: rriddle

Differential Revision: https://reviews.llvm.org/D95991
2021-02-04 01:58:56 +00:00
Alex Zinenko
0409eb2874 [mlir] Keep track of region signature conversions as argument replacements
In dialect conversion, signature conversions essentially perform block argument
replacement and are added to the general value remapping. However, the replaced
values were not tracked, so if a signature conversion was rolled back, the
construction of operand lists for the following patterns could have obtained
block arguments from the mapping and give them to the pattern leading to
use-after-free. Keep track of signature conversions similarly to normal block
argument replacement, and erase such replacements from the general mapping when
the conversion is rolled back.

Reviewed By: rriddle

Differential Revision: https://reviews.llvm.org/D95688
2021-02-02 10:38:31 +01:00
Alexander Belyaev
8d7cbcf582 [mlir] Preserve lexicographic order after loop collapsing.
Currently, for a scf.parallel (i,j,k) after the loop collapsing to 1D is done, the
IVs would be traversed as for an scf.parallel(k,j,i).

Differential Revision: https://reviews.llvm.org/D95693
2021-01-29 21:32:36 +01:00
Diego Caballero
c8fc5c0385 [mlir][Affine] Add support for multi-store producer fusion
This patch adds support for producer-consumer fusion scenarios with
multiple producer stores to the AffineLoopFusion pass. The patch
introduces some changes to the producer-consumer algorithm, including:

* For a given consumer loop, producer-consumer fusion iterates over its
producer candidates until a fixed point is reached.

* Producer candidates are gathered beforehand for each iteration of the
consumer loop and visited in reverse program order (not strictly guaranteed)
to maximize the number of loops fused per iteration.

In general, these changes were needed to simplify the multi-store producer
support and remove some of the workarounds that were introduced in the past
to support more fusion cases under the single-store producer limitation.

This patch also preserves the existing functionality of AffineLoopFusion with
one minor change in behavior. Producer-consumer fusion didn't fuse scenarios
with escaping memrefs and multiple outgoing edges (from a single store).
Multi-store producer scenarios will usually (always?) have multiple outgoing
edges so we couldn't fuse any with escaping memrefs, which would greatly limit
the applicability of this new feature. Therefore, the patch enables fusion for
these scenarios. Please, see modified tests for specific details.

Reviewed By: andydavis1, bondhugula

Differential Revision: https://reviews.llvm.org/D92876
2021-01-25 20:31:17 +02:00
Diego Caballero
735a07f047 Revert "[mlir][Affine] Add support for multi-store producer fusion"
This reverts commit 7dd198852b.

ASAN issue.
2021-01-21 00:37:23 +02:00
Diego Caballero
7dd198852b [mlir][Affine] Add support for multi-store producer fusion
This patch adds support for producer-consumer fusion scenarios with
multiple producer stores to the AffineLoopFusion pass. The patch
introduces some changes to the producer-consumer algorithm, including:

* For a given consumer loop, producer-consumer fusion iterates over its
producer candidates until a fixed point is reached.

* Producer candidates are gathered beforehand for each iteration of the
consumer loop and visited in reverse program order (not strictly guaranteed)
to maximize the number of loops fused per iteration.

In general, these changes were needed to simplify the multi-store producer
support and remove some of the workarounds that were introduced in the past
to support more fusion cases under the single-store producer limitation.

This patch also preserves the existing functionality of AffineLoopFusion with
one minor change in behavior. Producer-consumer fusion didn't fuse scenarios
with escaping memrefs and multiple outgoing edges (from a single store).
Multi-store producer scenarios will usually (always?) have multiple outgoing
edges so we couldn't fuse any with escaping memrefs, which would greatly limit
the applicability of this new feature. Therefore, the patch enables fusion for
these scenarios. Please, see modified tests for specific details.

Reviewed By: andydavis1, bondhugula

Differential Revision: https://reviews.llvm.org/D92876
2021-01-20 19:03:07 +02:00
Julian Gross
43f34f5834 Added check if there are regions that do not implement the RegionBranchOpInterface.
Add a check if regions do not implement the RegionBranchOpInterface. This is not
allowed in the current deallocation steps. Furthermore, we handle edge-cases,
where a single region is attached and the parent operation has no results.

This fixes: https://bugs.llvm.org/show_bug.cgi?id=48575

Differential Revision: https://reviews.llvm.org/D94586
2021-01-20 12:15:28 +01:00
Sean Silva
be7352c00d [mlir][splitting std] move 2 more ops to tensor
- DynamicTensorFromElementsOp
- TensorFromElements

Differential Revision: https://reviews.llvm.org/D94994
2021-01-19 13:49:25 -08:00
Andrew Young
a55a0a3056 [mlir] Remove over specified memory effects
The standard and gpu dialect both have `alloc` operations which use the
memory effect `MemAlloc`.  In both cases, it is specified on both  the
operation itself and on the result.  This results in two memory effects
being created for these operations.  When `MemAlloc` is defined on an
operation, it represents some background effect which the compiler
cannot reason about, and  inhibits the ability of the compiler to
remove dead `std.alloc` operations.  This change removes the uneeded
`MemAlloc` effect from these operations and leaves the effect on the
result, which allows dead allocs to be erased.

There is the same problem, but to a lesser extent, with MemFree, MemRead
and MemWrite. Over-specifying these traits is not currently inhibiting
any optimization.

Differential Revision: https://reviews.llvm.org/D94662
2021-01-14 14:49:41 -08:00
River Riddle
c8fb6ee341 [mlir][PatternRewriter] Add a new hook to selectively replace uses of an operation
This revision adds a new `replaceOpWithIf` hook that replaces uses of an operation that satisfy a given functor. If all uses are replaced, the operation gets erased in a similar manner to `replaceOp`. DialectConversion support will be added in a followup as this requires adjusting how replacements are tracked there.

Differential Revision: https://reviews.llvm.org/D94632
2021-01-14 11:58:21 -08:00
River Riddle
93592b726c [mlir][OpFormatGen] Format enum attribute cases as keywords when possible
In the overwhelmingly common case, enum attribute case strings represent valid identifiers in MLIR syntax. This revision updates the format generator to format as a keyword in these cases, removing the need to wrap values in a string. The parser still retains the ability to parse the string form, but the printer will use the keyword form when applicable.

Differential Revision: https://reviews.llvm.org/D94575
2021-01-14 11:35:49 -08:00
Alex Zinenko
2230bf99c7 [mlir] replace LLVMIntegerType with built-in integer type
The LLVM dialect type system has been closed until now, i.e. did not support
types from other dialects inside containers. While this has had obvious
benefits of deriving from a common base class, it has led to some simple types
being almost identical with the built-in types, namely integer and floating
point types. This in turn has led to a lot of larger-scale complexity: simple
types must still be converted, numerous operations that correspond to LLVM IR
intrinsics are replicated to produce versions operating on either LLVM dialect
or built-in types leading to quasi-duplicate dialects, lowering to the LLVM
dialect is essentially required to be one-shot because of type conversion, etc.
In this light, it is reasonable to trade off some local complexity in the
internal implementation of LLVM dialect types for removing larger-scale system
complexity. Previous commits to the LLVM dialect type system have adapted the
API to support types from other dialects.

Replace LLVMIntegerType with the built-in IntegerType plus additional checks
that such types are signless (these are isolated in a utility function that
replaced `isa<LLVMType>` and in the parser). Temporarily keep the possibility
to parse `!llvm.i32` as a synonym for `i32`, but add a deprecation notice.

Reviewed By: mehdi_amini, silvas, antiagainst

Differential Revision: https://reviews.llvm.org/D94178
2021-01-07 19:48:31 +01:00
Kazuaki Ishizaki
2b638ed5a1 [mlir] NFC: fix trivial typos
fix typos under docs, test, and tools directories

Reviewed By: ftynse

Differential Revision: https://reviews.llvm.org/D94158
2021-01-07 02:36:02 +09:00
Sean Silva
129d6e554e [mlir] Move std.tensor_cast -> tensor.cast.
This is almost entirely mechanical.

Differential Revision: https://reviews.llvm.org/D93357
2020-12-17 16:06:56 -08:00
River Riddle
d7eba20052 [mlir][Inliner] Refactor the inliner to use nested pass pipelines instead of just canonicalization
Now that passes have support for running nested pipelines, the inliner can now allow for users to provide proper nested pipelines to use for optimization during inlining. This revision also changes the behavior of optimization during inlining to optimize before attempting to inline, which should lead to a more accurate cost model and prevents the need for users to schedule additional duplicate cleanup passes before/after the inliner that would already be run during inlining.

Differential Revision: https://reviews.llvm.org/D91211
2020-12-14 18:09:47 -08:00
Sean Silva
444822d77a Revert "Revert "[mlir] Start splitting the tensor dialect out of std.""
This reverts commit 0d48d265db.

This reapplies the following commit, with a fix for CAPI/ir.c:

[mlir] Start splitting the `tensor` dialect out of `std`.

This starts by moving `std.extract_element` to `tensor.extract` (this
mirrors the naming of `vector.extract`).

Curiously, `std.extract_element` supposedly works on vectors as well,
and this patch removes that functionality. I would tend to do that in
separate patch, but I couldn't find any downstream users relying on
this, and the fact that we have `vector.extract` made it seem safe
enough to lump in here.

This also sets up the `tensor` dialect as a dependency of the `std`
dialect, as some ops that currently live in `std` depend on
`tensor.extract` via their canonicalization patterns.

Part of RFC: https://llvm.discourse.group/t/rfc-split-the-tensor-dialect-from-std/2347/2

Differential Revision: https://reviews.llvm.org/D92991
2020-12-11 14:30:50 -08:00
Sean Silva
0d48d265db Revert "[mlir] Start splitting the tensor dialect out of std."
This reverts commit cab8dda90f.

I mistakenly thought that CAPI/ir.c failure was unrelated to this
change. Need to debug it.
2020-12-11 14:15:41 -08:00
Sean Silva
cab8dda90f [mlir] Start splitting the tensor dialect out of std.
This starts by moving `std.extract_element` to `tensor.extract` (this
mirrors the naming of `vector.extract`).

Curiously, `std.extract_element` supposedly works on vectors as well,
and this patch removes that functionality. I would tend to do that in
separate patch, but I couldn't find any downstream users relying on
this, and the fact that we have `vector.extract` made it seem safe
enough to lump in here.

This also sets up the `tensor` dialect as a dependency of the `std`
dialect, as some ops that currently live in `std` depend on
`tensor.extract` via their canonicalization patterns.

Part of RFC: https://llvm.discourse.group/t/rfc-split-the-tensor-dialect-from-std/2347/2

Differential Revision: https://reviews.llvm.org/D92991
2020-12-11 13:50:55 -08:00
River Riddle
c24f88b4db [mlir][SCCP] Don't visit private callables unless they are used when tracking interprocedural arguments/results
This fixes a subtle bug where SCCP could incorrectly optimize a private callable while waiting for its arguments to be resolved.

Fixes PR#48457

Differential Revision: https://reviews.llvm.org/D92976
2020-12-10 12:53:27 -08:00
Haruki Imai
b2391d5f0d [MLIR] Normalize the results of normalizable operations
Memrefs with affine_map in the results of normalizable operation were
not normalized by `--normalize-memrefs` option. This patch normalizes
them.

Differential Revision: https://reviews.llvm.org/D88719
2020-12-03 19:34:07 +05:30
Julian Gross
8aeca73702 [MLIR] Added support for dynamic shaped allocas to promote-buffers-to-stack pass.
Extended promote buffers to stack pass to support dynamically shaped allocas.
The conversion is limited by the rank of the underlying tensor.
An option is added to the pass to adjust the given rank.

Differential Revision: https://reviews.llvm.org/D91969
2020-12-03 11:47:49 +01:00
Sean Silva
774f1d3ffd [mlir] Small cleanups to func-bufferize/finalizing-bufferize
- Address TODO in scf-bufferize: the argument materialization issue is
  now fixed and the code is now in Transforms/Bufferize.cpp
- Tighten up finalizing-bufferize to avoid creating invalid IR when
  operand types potentially change
- Tidy up the testing of func-bufferize, and move appropriate tests
  to a new finalizing-bufferize.mlir
- The new stricter checking in finalizing-bufferize revealed that we
  needed a DimOp conversion pattern (found when integrating into npcomp).
  Previously, the converion infrastructure was blindly changing the
  operand type during finalization, which happened to work due to
  DimOp's tensor/memref polymorphism, but is generally not encouraged
  (the new pattern is the way to tell the conversion infrastructure that
  it is legal to change that type).
2020-11-30 17:04:14 -08:00
Stephan Herhut
20c926e079 [mlir][DialectConversion] Do not prematurely drop unused cast operations
The rewrite logic has an optimization to drop a cast operation after
rewriting block arguments if the cast operation has no users. This is
unsafe as there might be a pending rewrite that replaced the cast operation
itself and hence would trigger a second free.

Instead, do not remove the casts and leave it up to a later canonicalization
to do so.

Differential Revision: https://reviews.llvm.org/D92184
2020-11-26 17:39:14 +01:00
William S. Moses
f5c5fd1c50 [MLIR] Correct block merge bug
Block merging in MLIR will incorrectly merge blocks with operations whose values are used outside of that block. This change forbids this behavior and provides a test where it is illegal to perform such a merge.

Reviewed By: rriddle

Differential Revision: https://reviews.llvm.org/D91745
2020-11-20 19:12:59 +01:00
Tres Popp
b0750e2df6 Fix rollback of first block erasure in a region.
Differential Revision: https://reviews.llvm.org/D91788
2020-11-19 21:24:10 +01:00
Stephan Herhut
c4472f8b4c [mlir][std] Canonicalize extract_element(tensor_cast).
Canonicalize extract_element(tensor_cast(v)) to just extract_element(v).

Differential Revision: https://reviews.llvm.org/D91621
2020-11-17 14:41:39 +01:00
Rahul Joshi
b7382ed3fe [MLIR] Extend Symbol verification to reject public symbol declarations.
- Extend the Symbol interface with `isDeclaration` to identify operations that declare
  a symbol as opposed to define it.
- Extend verification to disallow public declarations as per the discussion in
   https://llvm.discourse.group/t/rfc-symbol-definition-declaration-x-visibility-checks/2140
- Adopt the new interface for `FuncOp` and fix test and code to not have/create public
  function declarations.

Differential Revision: https://reviews.llvm.org/D91456
2020-11-16 16:05:32 -08:00
Sean Silva
7c62c6313b [mlir] Add DecomposeCallGraphTypes pass.
This replaces the old type decomposition logic that was previously mixed
into bufferization, and makes it easily accessible.

This also deletes TestFinalizingBufferize, because after we remove the type
decomposition, it doesn't do anything that is not already provided by
func-bufferize.

Differential Revision: https://reviews.llvm.org/D90899
2020-11-16 12:25:35 -08:00
Stephan Herhut
4a771108ac [mlir][bufferize] Fix buffer promotion to stack for index types
The index type does not have a bitsize and hence the size of corresponding allocations cannot be computed.  Instead, the promotion pass now has an explicit option to specify the size of index.

Differential Revision: https://reviews.llvm.org/D91360
2020-11-13 09:23:36 +01:00
Tres Popp
cc5b4a8603 [mlir] Rework DialectConversion inlineRegionBefore
The previous logic for inlining a region A with N blocks into region B
would produce incorrect results on rollback for N greater than 1. This
rollback logic would leave blocks 1..N in region B and only move block 0
to region A.

The new inlining action recording stores the block move actions from N-1
to 0. Now on roll back, block 0 is moved to region A and then 1..N is
appended to the list of blocks in region A.

Differential Revision: https://reviews.llvm.org/D91185
2020-11-11 10:42:33 +01:00
River Riddle
892605b449 [mlir][Asm] Add support for using an alias for trailing operation locations
Locations often get very long and clutter up operations when printed inline with them. This revision adds support for using aliases with trailing operation locations, and makes printing with aliases the default behavior. Aliases in the trailing location take the form `loc(<alias>)`, such as `loc(#loc0)`. As with all aliases, using `mlir-print-local-scope` can be used to disable them and get the inline behavior.

Differential Revision: https://reviews.llvm.org/D90652
2020-11-09 21:54:47 -08:00
River Riddle
ebcc022507 [mlir][AsmPrinter] Refactor printing to only print aliases for attributes/types that will exist in the output.
This revision refactors the way that attributes/types are considered when generating aliases. Instead of considering all of the attributes/types of every operation, we perform a "fake" print step that prints the operations using a dummy printer to collect the attributes and types that would actually be printed during the real process. This removes a lot of attributes/types from consideration that generally won't end up in the final output, e.g. affine map attributes in an `affine.apply`/`affine.for`.

This resolves a long standing TODO w.r.t aliases, and helps to have a much cleaner textual output format. As a datapoint to the latter, as part of this change several tests were identified as testing for the presence of attributes aliases that weren't actually referenced by the custom form of any operation.

To ensure that this wouldn't cause a large degradation in compile time due to the second full print, I benchmarked this change on a very large module with a lot of operations(The file is ~673M/~4.7 million lines long). This file before this change take ~6.9 seconds to print in the custom form, and ~7 seconds after this change. In the custom assembly case, this added an average of a little over ~100 miliseconds to the compile time. This increase was due to the way that argument attributes on functions are structured and how they get printed; i.e. with a better representation the negative impact here can be greatly decreased. When printing in the generic form, this revision had no observable impact on the compile time. This benchmarking leads me to believe that the impact of this change on compile time w.r.t printing is closely related to `print` methods that perform a lot of additional/complex processing outside of the OpAsmPrinter.

Differential Revision: https://reviews.llvm.org/D90512
2020-11-09 21:54:47 -08:00
Rahul Joshi
8b5a3e4632 [MLIR] Change FuncOp assembly syntax to print visibility inline instead of in attrib dict.
- Change syntax for FuncOp to be `func <visibility>? @name` instead of printing the
  visibility in the attribute dictionary.
- Since printFunctionLikeOp() and parseFunctionLikeOp() are also used by other
  operations, make the "inline visibility" an opt-in feature.
- Updated unit test to use and check the new syntax.

Differential Revision: https://reviews.llvm.org/D90859
2020-11-09 11:08:08 -08:00
Alex Zinenko
0c782c214b [mlir] Add folding of memref_cast inside another memref_cast
There exists a generic folding facility that folds the operand of a memref_cast
into users of memref_cast that support this. However, it was not used for the
memref_cast itself. Fix it to enable elimination of memref_cast chains such as

  %1 = memref_cast %0 : A to B
  %2 = memref_cast %1 : B to A

that is achieved by combining the folding with the existing "A to A" cast
elimination.

Reviewed By: nicolasvasilache

Differential Revision: https://reviews.llvm.org/D90910
2020-11-06 10:42:40 +01:00
Sean Silva
f7bc568266 [mlir] Remove AppendToArgumentsList functionality from BufferizeTypeConverter.
This functionality is superceded by BufferResultsToOutParams pass (see
https://reviews.llvm.org/D90071) for users the require buffers to be
out-params. That pass should be run immediately after all tensors are gone from
the program (before buffer optimizations and deallocation insertion), such as
immediately after a "finalizing" bufferize pass.

The -test-finalizing-bufferize pass now defaults to what used to be the
`allowMemrefFunctionResults=true` flag. and the
finalizing-bufferize-allowed-memref-results.mlir file is moved
to test/Transforms/finalizing-bufferize.mlir.

Differential Revision: https://reviews.llvm.org/D90778
2020-11-05 11:20:09 -08:00
Nicolas Vasilache
ecca7852d9 [mlir][Linalg] Side effects interface for Linalg ops
The LinalgDependenceGraph and alias analysis provide the necessary analysis for the Linalg fusion on buffers case.

However this is not enough for linalg on tensors which require proper memory effects to play nicely with DCE and other transformations.
This revision adds side effects to Linalg ops that were previously missing and has 2 consequences:
1. one example in the copy removal pass now fails since the linalg.generic op has side effects and the pass does not perform alias analysis / distinguish between reads and writes.
2. a few examples in fusion-tensor.mlir need to return the resulting tensor otherwise DCE automatically kicks in as part of greedy pattern application.

Differential Revision: https://reviews.llvm.org/D90762
2020-11-05 09:00:28 +00:00
Alexandre Eichenberger
0795715616 [mlir][std] Add SignedCeilDivIOp and SignedFloorDivIOp with std to std lowering triggered by -std-expand-divs option. The new operations support positive/negative nominator/denominator numbers.
Differential Revision: https://reviews.llvm.org/D89726

Signed-off-by: Alexandre Eichenberger <alexe@us.ibm.com>
2020-11-04 14:16:23 -05:00
Alexander Bosch
5452fa6a59 [MLIR] Added test operations to replace linalg dependency for
BufferizeTests.

Summary:
Added test operations to replace the LinalgDialect dependency in tests
which use the buffer-deallocation, buffer-hoisting,
buffer-loop-hoisting, promote-buffers-to-stack,
buffer-placement-preparation-allowed-memref-resutls and
buffer-placement-preparation pass. Adapted the corresponding tests cases
and TestBufferPlacement.cpp.

Differential Revision: https://reviews.llvm.org/D90037
2020-11-03 12:18:49 +01:00
Sean Silva
773ad135a3 [mlir][Bufferize] Rename TestBufferPlacement to TestFinalizingBufferize
BufferPlacement is no longer part of bufferization. However, this test
is an important test of "finalizing" bufferize passes.
A "finalizing" bufferize conversion is one that performs a "full"
conversion and expects all tensors to be gone from the program. This in
particular involves rewriting funcs (including block arguments of the
contained region), calls, and returns. The unique property of finalizing
bufferization passes is that they cannot be done via a local
transformation with suitable materializations to ensure composability
(as other bufferization passes do). For example, if a call is
rewritten, the callee needs to be rewritten otherwise the IR will end up
invalid. Thus, finalizing bufferization passes require an atomic change
to the entire program (e.g. the whole module).

This new designation makes it clear also that it shouldn't be testing
bufferization of linalg ops, so the tests have been updated to not use
linalg.generic ops. (linalg.copy is still used as the "copy" op for
copying into out-params)

Differential Revision: https://reviews.llvm.org/D89979
2020-11-02 12:42:32 -08:00
Sean Silva
b866574246 [mlir] Add BufferResultsToOutParams pass.
This pass allows removing getResultConversionKind from
BufferizeTypeConverter. This pass replaces the AppendToArgumentsList
functionality. As far as I could tell, the only use of this functionlity
is to perform the transformation that is implemented in this pass.

Future patches will remove the getResultConversionKind machinery from
BufferizeTypeConverter, but sending this patch for individual review for
clarity.

Differential Revision: https://reviews.llvm.org/D90071
2020-10-30 14:06:14 -07:00
River Riddle
a463ea50a4 [mlir][ASM] Refactor how attribute/type aliases are specified.
Previously they were separated into "instance" and "kind" aliases, and also required that the dialect know ahead of time all of the instances that would have a corresponding alias. This approach was very clunky and not ergonomic to interact with. The new approach is to provide the dialect with an instance  of an attribute/type to provide an alias for, fully replacing the original split approach.

Differential Revision: https://reviews.llvm.org/D89354
2020-10-30 00:39:46 -07:00
River Riddle
501fda0167 [mlir][Inliner] Add a new hook for checking if it is legal to inline a callable into a call
In certain situations it isn't legal to inline a call operation, but this isn't something that is possible(at least not easily) to prevent with the current hooks. This revision adds a new hook so that dialects with call operations that shouldn't be inlined can prevent it.

Differential Revision: https://reviews.llvm.org/D90359
2020-10-28 21:49:28 -07:00
Kazuaki Ishizaki
41b09f4eff [mlir] NFC: fix trivial typos
fix typos in comments and documents

Reviewed By: jpienaar

Differential Revision: https://reviews.llvm.org/D90089
2020-10-29 04:05:22 +09:00
Julian Gross
0d1d363c51 [MLIR] Added PromoteBuffersToStackPass to convert heap- to stack-based allocations.
Added optimization pass to convert heap-based allocs to stack-based allocas in
buffer placement. Added the corresponding test file.

Differential Revision: https://reviews.llvm.org/D89688
2020-10-23 12:02:25 +02:00
Marcel Koester
1b1c61ff47 [mlir] Refactored BufferPlacement transformation.
The current BufferPlacement transformation contains several concepts for
hoisting allocations. However, more advanced hoisting techniques should not be
integrated into the BufferPlacement transformation. Hence, this CL refactors the
current BufferPlacement pass into three separate pieces: BufferDeallocation and
BufferAllocation(Loop)Hoisting. Moreover, it extends the hoisting functionality
by allowing to move allocations out of loops.

Differential Revision: https://reviews.llvm.org/D87756
2020-10-19 12:52:16 +02:00
River Riddle
a8feeee15f [mlir] Add canonicalization for cond_br that feed into a cond_br on the same condition
```
   ...
   cond_br %cond, ^bb1(...), ^bb2(...)
 ...
 ^bb1: // has single predecessor
   ...
   cond_br %cond, ^bb3(...), ^bb4(...)
```

 ->

```
   ...
   cond_br %cond, ^bb1(...), ^bb2(...)
 ...
 ^bb1: // has single predecessor
   ...
   br ^bb3(...)
```

Differential Revision: https://reviews.llvm.org/D89604
2020-10-18 13:51:02 -07:00
Stephan Herhut
307124535f [mlir][standard] Fix parsing of scalar subview and canonicalize
Parsing of a scalar subview did not create the required static_offsets attribute.
This also adds support for folding scalar subviews away.

Differential Revision: https://reviews.llvm.org/D89467
2020-10-15 16:41:54 +02:00
Sean Silva
9a14cb53cb [mlir][bufferize] Rename BufferAssignment* to Bufferize*
Part of the refactor discussed in:
https://llvm.discourse.group/t/what-is-the-strategy-for-tensor-memref-conversion-bufferization/1938/17

Differential Revision: https://reviews.llvm.org/D89271
2020-10-14 12:39:16 -07:00