New mode option that allows for either running the default fusion kind that happens today or doing either of producer-consumer or sibling fusion. This will also be helpful to minimize the compile-time of the fusion tests.
Reviewed By: bondhugula, dcaballe
Differential Revision: https://reviews.llvm.org/D110102
* Rename ids to values in FlatAffineValueConstraints.
* Overall cleanup of comments in FlatAffineConstraints and FlatAffineValueConstraints.
Differential Revision: https://reviews.llvm.org/D107947
* Extract "value" functionality of `FlatAffineConstraints` into a new derived `FlatAffineValueConstraints` class. Current users of `FlatAffineConstraints` can use `FlatAffineValueConstraints` without additional code changes, thus NFC.
* `FlatAffineConstraints` no longer associates dimensions with SSA Values. All functionality that requires this, is moved to `FlatAffineValueConstraints`.
* `FlatAffineConstraints` no longer makes assumptions about where Values associated with dimensions are coming from.
Differential Revision: https://reviews.llvm.org/D107725
The presence of AffineIfOp inside AffineFor prevents fusion of the other loops to happen. For example:
```
affine.for %i0 = 0 to 10 {
affine.store %cf7, %a[%i0] : memref<10xf32>
}
affine.for %i1 = 0 to 10 {
%v0 = affine.load %a[%i1] : memref<10xf32>
affine.store %v0, %b[%i1] : memref<10xf32>
}
affine.for %i2 = 0 to 10 {
affine.if #set(%i2) {
%v0 = affine.load %b[%i2] : memref<10xf32>
}
}
```
The first two loops were not be fused because of `affine.if` inside the last `affine.for`.
The issue seems to come from a conservative constraint that does not allow fusion if there are ops whose number of regions != 0 (affine.if is one of them).
This patch just removes such a constraint when`affine.if` is inside `affine.for`. The existing `canFuseLoops` method is able to handle `affine.if` correctly.
Reviewed By: bondhugula, vinayaka-polymage
Differential Revision: https://reviews.llvm.org/D105963
Changes include the following:
1. Single iteration reduction loops being sibling fused at innermost insertion level
are skipped from being considered as sequential loops.
Otherwise, the slice bounds of these loops is reset.
2. Promote loops that are skipped in previous step into outer loops.
3. Two utility function - buildSliceTripCountMap, getSliceIterationCount - are moved from
mlir/lib/Transforms/Utils/LoopFusionUtils.cpp to mlir/lib/Analysis/Utils.cpp
Reviewed By: bondhugula, vinayaka-polymage
Differential Revision: https://reviews.llvm.org/D104249
During affine loop fusion, create private memrefs for escaping memrefs
too under the conditions that:
-- the source is not removed after fusion, and
-- the destination does not write to the memref.
This creates more fusion opportunities as illustrated in the test case.
Reviewed By: bondhugula, ayzhuang
Differential Revision: https://reviews.llvm.org/D102604
Just a pure method renaming.
It is a preparation step for replacing "memory space as raw integer"
with more generic "memory space as attribute", which will be done in
separate commit.
The `MemRefType::getMemorySpace` method will return `Attribute` and
become the main API, while `getMemorySpaceAsInt` will be declared as
deprecated and will be replaced in all in-tree dialects (also in separate
commits).
Reviewed By: mehdi_amini, rriddle
Differential Revision: https://reviews.llvm.org/D97476
Fixes a bug in affine fusion pipeline where an incorrect fusion is performed
despite a Call Op that potentially modifies memrefs under consideration
exists between source and target.
Fixes part of https://bugs.llvm.org/show_bug.cgi?id=49220
Reviewed By: bondhugula, dcaballe
Differential Revision: https://reviews.llvm.org/D97252
This patch handles defining ops between the source and dest loop nests, and prevents loop nests with `iter_args` from being fused.
If there is any SSA value in the dest loop nest whose defining op has dependence from the source loop nest, we cannot fuse the loop nests.
If there is a `affine.for` with `iter_args`, prevent it from being fused.
Reviewed By: dcaballe, bondhugula
Differential Revision: https://reviews.llvm.org/D97030
This commit fixes a bug in affine fusion pipeline where an
incorrect fusion is performed despite a dealloc op is present
between a producer and a consumer. This is done by creating a
node for dealloc op in the MDG.
Reviewed By: bondhugula, dcaballe
Differential Revision: https://reviews.llvm.org/D97032
This commit introduced a cyclic dependency:
Memref dialect depends on Standard because it used ConstantIndexOp.
Std depends on the MemRef dialect in its EDSC/Intrinsics.h
Working on a fix.
This reverts commit 8aa6c3765b.
Create the memref dialect and move several dialect-specific ops without
dependencies to other ops from std dialect to this dialect.
Moved ops:
AllocOp -> MemRef_AllocOp
AllocaOp -> MemRef_AllocaOp
DeallocOp -> MemRef_DeallocOp
MemRefCastOp -> MemRef_CastOp
GetGlobalMemRefOp -> MemRef_GetGlobalOp
GlobalMemRefOp -> MemRef_GlobalOp
PrefetchOp -> MemRef_PrefetchOp
ReshapeOp -> MemRef_ReshapeOp
StoreOp -> MemRef_StoreOp
TransposeOp -> MemRef_TransposeOp
ViewOp -> MemRef_ViewOp
The roadmap to split the memref dialect from std is discussed here:
https://llvm.discourse.group/t/rfc-split-the-memref-dialect-from-std/2667
Differential Revision: https://reviews.llvm.org/D96425
Separating the AffineMapAccessInterface from AffineRead/WriteOp interface so that dialects which extend Affine capabilities (e.g. PlaidML PXA = parallel extensions for Affine) can utilize relevant passes (e.g. MemRef normalization).
Reviewed By: bondhugula
Differential Revision: https://reviews.llvm.org/D96284
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
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
Given that OpState already implicit converts to Operator*, this seems reasonable.
The alternative would be to add more functions to OpState which forward to Operation.
Reviewed By: rriddle, ftynse
Differential Revision: https://reviews.llvm.org/D92266
Refactoring/clean-up step needed to add support for producer-consumer fusion
with multi-store producer loops and, in general, to implement more general
loop fusion strategies in Affine. It introduces the following changes:
- AffineLoopFusion pass now uses loop fusion utilities more broadly to compute
fusion legality (canFuseLoops utility) and perform the fusion transformation
(fuseLoops utility).
- Loop fusion utilities have been extended to deal with AffineLoopFusion
requirements and assumptions while preserving both loop fusion utilities and
AffineLoopFusion current functionality within a unified implementation.
'FusionStrategy' has been introduced for this purpose and, in the future, it
will allow us to have a single loop fusion core implementation that will produce
different fusion outputs depending on the strategy used.
- Improve separation of concerns for legality and profitability analysis:
'isFusionProfitable' no longer filters out illegal scenarios that 'canFuse'
didn't detect, or the other way around. 'canFuse' now takes loop dependences
into account to determine the fusion loop depth (producer-consumer fusion only).
- As a result, maximal fusion now doesn't require any profitability analysis.
- Slices are now computed only once and reused across the legality, profitability
and fusion transformation steps (producer-consumer).
- Refactor some utilities and remove redundant copies of them.
This patch is NFCI and should preserve the existing functionality of both the
AffineLoopFusion pass and the affine fusion utilities.
Reviewed By: andydavis1, bondhugula
Differential Revision: https://reviews.llvm.org/D90798
Always define a remapping for the memref replacement (`indexRemap`)
with the proper number of inputs, including all the `outerIVs`, so that
the number of inputs and the operands provided for the map don't mismatch.
Reviewed By: bondhugula, andydavis1
Differential Revision: https://reviews.llvm.org/D85177
When there is a mix of affine load/store and non-affine operations (e.g. std.load, std.store),
affine-loop-fusion ignores the present of non-affine ops, thus changing the program semantics.
E.g. we have a program of three affine loops operating on the same memref in which one of them uses std.load and std.store, as follows.
```
affine.for
affine.store %1
affine.for
std.load %1
std.store %1
affine.for
affine.load %1
affine.store %1
```
affine-loop-fusion will produce the following result which changed the program semantics:
```
affine.for
std.load %1
std.store %1
affine.for
affine.store %1
affine.load %1
affine.store %1
```
This patch is to fix the above problem by checking non-affine users of the memref that are between the source and destination nodes of interest.
Differential Revision: https://reviews.llvm.org/D82158
This patch changes the fusion algorithm so that after fusing two loop nests
we revisit previously visited nodes so that they are considered again for
fusion in the context of the new fused loop nest.
Reviewed By: bondhugula
Differential Revision: https://reviews.llvm.org/D81609
This patch introduces interfaces for read and write ops with affine
restrictions. I used `read`/`write` intead of `load`/`store` for the
interfaces so that they can also be implemented by dma ops.
For now, they are only implemented by affine.load, affine.store,
affine.vector_load and affine.vector_store.
For testing purposes, this patch also migrates affine loop fusion and
required analysis to use the new interfaces. No other changes are made
beyond that.
Co-authored-by: Alex Zinenko <zinenko@google.com>
Reviewed By: bondhugula, ftynse
Differential Revision: https://reviews.llvm.org/D79829
The list of destination load ops while evaluating producer-consumer
fusion wasn't being maintained as a set, and as such, duplicate load ops
were being added to it. Although this is harmless correctness-wise, it's
a killer efficiency-wise and it prevents interesting/useful fusions
(including for eg. reshapes into a matmul). The reason the latter
fusions would be missed is that a slice union would be unnecessarily
needed due to the duplicate load ops on a memref added to the 'dst
loads' list. Since slice union is unimplemented for the local var case,
a single destination load op that leads to local vars (like a floordiv /
mod producing fusion), a common case, would not get fused due to an
unnecessary union being tried with itself. (The union would actually be
the same thing but we would bail out.)
Besides the above, this would also significantly speed up fusion as all
the unnecessary slice computations / unions, checks, etc. due to the
duplicates go away.
Differential Revision: https://reviews.llvm.org/D79547
Summary:
Modified AffineMap::get to remove support for the overload which allowed
an ArrayRef of AffineExpr but no context (and gathered the context from a
presumed first entry, resulting in bugs when there were 0 results).
Instead, we support only a ArrayRef and a context, and a version which
takes a single AffineExpr.
Additionally, removed some now needless case logic which previously
special cased which call to AffineMap::get to use.
Reviewers: flaub, bondhugula, rriddle!, nicolasvasilache, ftynse, ulysseB, mravishankar, antiagainst, aartbik
Subscribers: mehdi_amini, jpienaar, burmako, shauheen, antiagainst, arpith-jacob, mgester, lucyrfox, liufengdb, Joonsoo, bader, grosul1, frgossen, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D78226
Summary: Pass options are a better choice for various reasons and avoid the need for static constructors.
Differential Revision: https://reviews.llvm.org/D77707
Summary:
This is much cleaner, and fits the same structure as many other tablegen backends. This was not done originally as the CRTP in the pass classes made it overly verbose/complex.
Differential Revision: https://reviews.llvm.org/D77367
This revision removes all of the CRTP from the pass hierarchy in preparation for using the tablegen backend instead. This creates a much cleaner interface in the C++ code, and naturally fits with the rest of the infrastructure. A new utility class, PassWrapper, is added to replicate the existing behavior for passes not suitable for using the tablegen backend.
Differential Revision: https://reviews.llvm.org/D77350
This revision adds support for generating utilities for passes such as options/statistics/etc. that can be inferred from the tablegen definition. This removes additional boilerplate from the pass, and also makes it easier to remove the reliance on the pass registry to provide certain things(e.g. the pass argument).
Differential Revision: https://reviews.llvm.org/D76659
This will greatly simplify a number of things related to passes:
* Enables generation of pass registration
* Enables generation of boiler plate pass utilities
* Enables generation of pass documentation
This revision focuses on adding the basic structure and adds support for generating the registration for passes in the Transforms/ directory. Future revisions will add more support and move more passes over.
Differential Revision: https://reviews.llvm.org/D76656
Summary:
Change AffineOps Dialect structure to better group both IR and Tranforms. This included extracting transforms directly related to AffineOps. Also move AffineOps to Affine.
Differential Revision: https://reviews.llvm.org/D76161
Summary: A number of transform import StandardOps despite not being dependent on it. Cleaned it up to better understand what dialects each of these transforms depend on.
Differential Revision: https://reviews.llvm.org/D76112
Summary: For example, DenseElementsAttr currently does not properly round-trip unsigned integer values.
Differential Revision: https://reviews.llvm.org/D75374
Summary:
NFC - Moved StandardOps/Ops.h to a StandardOps/IR dir to better match surrounding
directories. This is to match other dialects, and prepare for moving StandardOps
related transforms in out for Transforms and into StandardOps/Transforms.
Differential Revision: https://reviews.llvm.org/D74940
Thus far IntegerType has been signless: a value of IntegerType does
not have a sign intrinsically and it's up to the specific operation
to decide how to interpret those bits. For example, std.addi does
two's complement arithmetic, and std.divis/std.diviu treats the first
bit as a sign.
This design choice was made some time ago when we did't have lots
of dialects and dialects were more rigid. Today we have much more
extensible infrastructure and different dialect may want different
modelling over integer signedness. So while we can say we want
signless integers in the standard dialect, we cannot dictate for
others. Requiring each dialect to model the signedness semantics
with another set of custom types is duplicating the functionality
everywhere, considering the fundamental role integer types play.
This CL extends the IntegerType with a signedness semantics bit.
This gives each dialect an option to opt in signedness semantics
if that's what they want and helps code sharing. The parser is
modified to recognize `si[1-9][0-9]*` and `ui[1-9][0-9]*` as
signed and unsigned integer types, respectively, leaving the
original `i[1-9][0-9]*` to continue to mean no indication over
signedness semantics. All existing dialects are not affected (yet)
as this is a feature to opt in.
More discussions can be found at:
https://groups.google.com/a/tensorflow.org/d/msg/mlir/XmkV8HOPWpo/7O4X0Nb_AQAJ
Differential Revision: https://reviews.llvm.org/D72533
Sumesh Udayakumaran