Per the discussion in https://reviews.llvm.org/D116345 it makes sense
to move AtomicRMWOp out of the standard dialect. This was accentuated by the
need to add a fold op with a memref::cast. The only dialect
that would permit this is the memref dialect (keeping it in the standard dialect
or moving it to the arithmetic dialect would require those dialects to have a
dependency on the memref dialect, which breaks linking).
As the AtomicRMWKind enum is used throughout, this has been moved to Arith.
Reviewed By: Mogball
Differential Revision: https://reviews.llvm.org/D116392
LLVM (dialect and IR) have atomics for and/or. This patch enables atomic_rmw ops in the standard dialect for and/or that lower to these (in addition to the existing atomics such as addi, etc).
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D116345
This patch reorders mergeLocalIds usage to merge locals only after number of
dimensions and symbols are same. This does not change any functionality
because it does not matter in what order identifiers are merged, since
the reason to do it is to ensure that two FACs are aligned.
The order ensured in this patch simplifies a subsequent patch to improve
mergeLocalIds which requires dimensions and symbols to be aligned.
Reviewed By: bondhugula
Differential Revision: https://reviews.llvm.org/D112841
1.Combining kind min/max of Vector reduction op has been changed to
minf/maxf, minsi/maxsi, and minui/maxui. Modify getVectorReductionOp
accordingly.
2.Add min/max to supported reductions.
Reviewed By: dcaballe, nicolasvasilache
Differential Revision: https://reviews.llvm.org/D112246
This patch removes code very specific to affine dependence analysis and
refactors it as a FlatAfffineRelation.
A FlatAffineRelation represents a set of ordered pairs (domain -> range) where
"domain" and "range" are tuples of identifiers. These relations are used to
represent an "access relation" for memory access on a memref. An access
relation maps elements of an iteration domain to the element(s) of an array
domain accessed by that iteration of the associated statement through some
array reference. The dependence relation representing the dependence
constraints between two memory accesses can be built by composing the access
relation of the destination access by the inverse of the access relation of
source access.
This patch does not change the functionality of the existing dependence
analysis in checkMemrefAccessDependence, but refactors it to use
FlatAffineRelations to deduplicate code and enable code reuse for future
development of features like scheduling, value-based dependence analysis, etc.
Reviewed By: bondhugula
Differential Revision: https://reviews.llvm.org/D110563
Precursor: https://reviews.llvm.org/D110200
Removed redundant ops from the standard dialect that were moved to the
`arith` or `math` dialects.
Renamed all instances of operations in the codebase and in tests.
Reviewed By: rriddle, jpienaar
Differential Revision: https://reviews.llvm.org/D110797
Unroll-and-jam currently doesn't work when the loop being unroll-and-jammed
or any of its inner loops has iter_args. This patch modifies the
unroll-and-jam utility to support loops with iter_args.
Reviewed By: bondhugula
Differential Revision: https://reviews.llvm.org/D110085
This patch introduces a generic reduction detection utility that works
across different dialecs. It is mostly a generalization of the reduction
detection algorithm in Affine. The reduction detection logic in Affine,
Linalg and SCFToOpenMP have been replaced with this new generic utility.
The utility takes some basic components of the potential reduction and
returns: 1) the reduced value, and 2) a list with the combiner operations.
The logic to match reductions involving multiple combiner operations disabled
until we can properly test it.
Reviewed By: ftynse, bondhugula, nicolasvasilache, pifon2a
Differential Revision: https://reviews.llvm.org/D110303
* Add batched version of all `addId` variants, so that multiple IDs can be added at a time.
* Rename `addId` and variants to `insertId` and `appendId`. Most external users call `appendId`. Splitting `addId` into two functions also makes it possible to provide batched version for both. (Otherwise, the overloads are ambigious when calling `addId`.)
Differential Revision: https://reviews.llvm.org/D108532
* 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
This patch adds support for vectorizing loops with 'iter_args'
implementing known reductions along the vector dimension. Comparing to
the non-vector-dimension case, two additional things are done during
vectorization of such loops:
- The resulting vector returned from the loop is reduced to a scalar
using `vector.reduce`.
- In some cases a mask is applied to the vector yielded at the end of
the loop to prevent garbage values from being written to the
accumulator.
Vectorization of reduction loops is disabled by default. To enable it, a
map from loops to array of reduction descriptors should be explicitly passed to
`vectorizeAffineLoops`, or `vectorize-reductions=true` should be passed
to the SuperVectorize pass.
Current limitations:
- Loops with a non-unit step size are not supported.
- n-D vectorization with n > 1 is not supported.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D100694
Introduce a basic support for parallelizing affine loops with reductions
expressed using iteration arguments. Affine parallelism detector now has a flag
to assume such reductions are parallel. The transformation handles a subset of
parallel reductions that are can be expressed using affine.parallel:
integer/float addition and multiplication. This requires to detect the
reduction operation since affine.parallel only supports a fixed set of
reduction operators.
Reviewed By: chelini, kumasento, bondhugula
Differential Revision: https://reviews.llvm.org/D101171
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
These includes have been deprecated in favor of BuiltinDialect.h, which contains the definitions of ModuleOp and FuncOp.
Differential Revision: https://reviews.llvm.org/D91572
This diff attempts to resolve the TODO in `getOpIndexSet` (formerly
known as `getInstIndexSet`), which states "Add support to handle IfInsts
surronding `op`".
Major changes in this diff:
1. Overload `getIndexSet`. The overloaded version considers both
`AffineForOp` and `AffineIfOp`.
2. The `getInstIndexSet` is updated accordingly: its name is changed to
`getOpIndexSet` and its implementation is based on a new API `getIVs`
instead of `getLoopIVs`.
3. Add `addAffineIfOpDomain` to `FlatAffineConstraints`, which extracts
new constraints from the integer set of `AffineIfOp` and merges it to
the current constraint system.
4. Update how a `Value` is determined as dim or symbol for
`ValuePositionMap` in `buildDimAndSymbolPositionMaps`.
Differential Revision: https://reviews.llvm.org/D84698
This revision aims to provide a new API, `checkTilingLegality`, to
verify that the loop tiling result still satisifes the dependence
constraints of the original loop nest.
Previously, there was no check for the validity of tiling. For instance:
```
func @diagonal_dependence() {
%A = alloc() : memref<64x64xf32>
affine.for %i = 0 to 64 {
affine.for %j = 0 to 64 {
%0 = affine.load %A[%j, %i] : memref<64x64xf32>
%1 = affine.load %A[%i, %j - 1] : memref<64x64xf32>
%2 = addf %0, %1 : f32
affine.store %2, %A[%i, %j] : memref<64x64xf32>
}
}
return
}
```
You can find more information about this example from the Section 3.11
of [1].
In general, there are three types of dependences here: two flow
dependences, one in direction `(i, j) = (0, 1)` (notation that depicts a
vector in the 2D iteration space), one in `(i, j) = (1, -1)`; and one
anti dependence in the direction `(-1, 1)`.
Since two of them are along the diagonal in opposite directions, the
default tiling method in `affine`, which tiles the iteration space into
rectangles, will violate the legality condition proposed by Irigoin and
Triolet [2]. [2] implies two tiles cannot depend on each other, while in
the `affine` tiling case, two rectangles along the same diagonal are
indeed dependent, which simply violates the rule.
This diff attempts to put together a validator that checks whether the
rule from [2] is violated or not when applying the default tiling method
in `affine`.
The canonical way to perform such validation is by examining the effect
from adding the constraint from Irigoin and Triolet to the existing
dependence constraints.
Since we already have the prior knowlegde that `affine` tiles in a
hyper-rectangular way, and the resulting tiles will be scheduled in the
same order as their respective loop indices, we can simplify the
solution to just checking whether all dependence components are
non-negative along the tiling dimensions.
We put this algorithm into a new API called `checkTilingLegality` under
`LoopTiling.cpp`. This function iterates every `load`/`store` pair, and
if there is any dependence between them, we get the dependence component
and check whether it has any negative component. This function returns
`failure` if the legality condition is violated.
[1]. Bondhugula, Uday. Effective Automatic parallelization and locality optimization using the Polyhedral model. https://dl.acm.org/doi/book/10.5555/1559029
[2]. Irigoin, F. and Triolet, R. Supernode Partitioning. https://dl.acm.org/doi/10.1145/73560.73588
Differential Revision: https://reviews.llvm.org/D84882
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
Summary:
This makes a common pattern of
`dyn_cast_or_null<OpTy>(v.getDefiningOp())` more concise.
Differential Revision: https://reviews.llvm.org/D79681
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:
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
This is an initial step to refactoring the representation of OpResult as proposed in: https://groups.google.com/a/tensorflow.org/g/mlir/c/XXzzKhqqF_0/m/v6bKb08WCgAJ
This change will make it much simpler to incrementally transition all of the existing code to use value-typed semantics.
PiperOrigin-RevId: 286844725
There are currently several different terms used to refer to a parent IR unit in 'get' methods: getParent/getEnclosing/getContaining. This cl standardizes all of these methods to use 'getParent*'.
PiperOrigin-RevId: 262680287
This allows for the attribute to hold symbolic references to other operations than FuncOp. This also allows for removing the dependence on FuncOp from the base Builder.
PiperOrigin-RevId: 257650017
In most places, this is just a name change (with the exception of affine.dma_start swapping the operand positions of its tag memref and num_elements operands).
Significant code changes occur here:
*) Vectorization: LoopAnalysis.cpp, Vectorize.cpp
*) Affine Transforms: Transforms/Utils/Utils.cpp
PiperOrigin-RevId: 256395088
