Summary:
Fix a broken test case in the `invalid.mlir` lit test case.
`expect` was missing its `e`.
Differential Revision: https://reviews.llvm.org/D78540
The buffer allocated by a promotion can be subject to other transformations afterward. For example it could be vectorized, in which case it is needed to ensure that this buffer is memory-aligned.
Differential Revision: https://reviews.llvm.org/D78556
This revision is the first in a set of improvements that aim at allowing
more generalized named Linalg op generation from a mathematical
specification.
This revision allows creating a new op and checks that the parser,
printer and verifier are hooked up properly.
This opened up a few design points that will be addressed in the future:
1. A named linalg op has a static region builder instead of an
explicitly parsed region. This is not currently compatible with
assemblyFormat so a custom parser / printer are needed.
2. The convention for structured ops and tensor return values needs to
evolve to allow tensor-land and buffer land specifications to agree
3. ReferenceIndexingMaps and referenceIterators will need to become
static to allow building attributes at parse time.
4. Error messages will be improved once we have 3. and we pretty print
in custom form.
Differential Revision: https://reviews.llvm.org/D78327
Unfortunately FileCheck ignores directives with whitespace between the directive and the colon (`CHECK :` for example), thus most of the directives of this test were ignored.
Differential Revision: https://reviews.llvm.org/D78548
This is possible by adding two new ControlFlowInterface additions:
- A new interface, RegionBranchOpInterface
This interface allows for region holding operations to describe how control flows between regions. This interface initially contains two methods:
* getSuccessorEntryOperands
Returns the operands of this operation used as the entry arguments when entering the region at `index`, which was specified as a successor by `getSuccessorRegions`. when entering. These operands should correspond 1-1 with the successor inputs specified in `getSuccessorRegions`, and may be a subset of the entry arguments for that region.
* getSuccessorRegions
Returns the viable successors of a region, or the possible successor when branching from the parent op. This allows for describing which regions may be executed when entering an operation, and which regions are executed after having executed another region of the parent op. For example, a structured loop operation may always enter into the loop body region. The loop body region may branch back to itself, or exit to the operation.
- A trait, ReturnLike
This trait signals that a terminator exits a region and forwards all of its operands as "exiting" values.
These additions allow for performing more general dataflow analysis in the presence of region holding operations.
Differential Revision: https://reviews.llvm.org/D78447
This revision adds the initial pass for performing SCCP generically in MLIR. SCCP is an algorithm for propagating constants across control flow, and optimistically assumes all values to be constant unless proven otherwise. It currently supports branching control, with support for regions and inter-procedural propagation being added in followups.
Differential Revision: https://reviews.llvm.org/D78397
The promotion transformation is promoting all input and output buffers of the transformed op. The user might want to only promote some of these buffers.
Differential Revision: https://reviews.llvm.org/D78498
The previous code result a mismatch between block argument types and
predecessor successor args when a type conversion was needed in a
multiblock case. It was assuming the replaced result types matched the
region result types.
Also, slighly improve the debug output from the inliner.
Differential Revision: https://reviews.llvm.org/D78415
Summary:
Generate method to generate a DictionaryAttr with attribute values of
derived attribute. If a conversion back from the derived attribute C++
type to Attribute is not defined, then attempting to materialize such an
op's derived attributes would result in runtime failure.
This allows to treat derived attributes and attributes of an op in more
uniform manner where needed. The derived attributes are not added to the
operation but returned as new attribute instead.
Differential Revision: https://reviews.llvm.org/D78302
Fix intra-tile upper bound setting in a scenario where the tile size was
larger than the trip count.
Differential Revision: https://reviews.llvm.org/D78505
memref types with dynamic dimensions do not have a compile-time
known size. They should be mapped to SPIR-V runtime array types.
Differential Revision: https://reviews.llvm.org/D78197
Summary:
Workgroup size is written into the kernel. So to properly modelling
vulkan launch, we have to skip local workgroup size for vulkan launch
call op.
Differential Revision: https://reviews.llvm.org/D78307
Summary:
The tests referred to in Chapter 3 of the tutorial were missing from the tutorial test
directory; this adds those missing tests. This also cleans up some stale directory paths and code
snippets used throughout the tutorial.
Differential Revision: https://reviews.llvm.org/D76809
Summary:
The tests referred to in Chapter 3 of the tutorial were missing from the tutorial test
directory; this adds those missing tests. This also cleans up some stale directory paths and code
snippets used throughout the tutorial.
Differential Revision: https://reviews.llvm.org/D76809
Summary:
The tests referred to in Chapter 3 of the tutorial were missing from the tutorial test
directory; this adds those missing tests. This also cleans up some stale directory paths and code
snippets used throughout the tutorial.
Subscribers: mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, aartbik, liufengdb, Joonsoo, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D76809
Summary:
Rather than having a full, recursive, lowering of vector.broadcast
to LLVM IR, it is much more elegant to have a progressive lowering
of each vector.broadcast into a lower dimensional vector.broadcast,
until only elementary vector operations remain. This results
in more elegant, step-wise code, that is easier to understand.
Also makes some optimizations in the generated code.
Reviewers: nicolasvasilache, mehdi_amini, andydavis1, grosul1
Reviewed By: nicolasvasilache
Subscribers: mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, liufengdb, Joonsoo, grosul1, frgossen, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D78071
MLIR supports operations with resizable operand lists, but this property must
be indicated during the construction of such operations. It can be done
programmatically by calling a function on OperationState. Introduce an
ODS-internal trait `ResizableOperandList` to indicate such operations are use
it when generating the bodies of various `build` functions as well as the
`parse` function when the declarative assembly format is used.
Differential Revision: https://reviews.llvm.org/D78292
There were some unused CMakeFiles for Affine/IR and Affine/EDSC.
This change builds separate MLIRAffineOps and MLIRAffineEDSC libraries
using those CMakeFiles. This combination replaces the old MLIRAffine
library.
Differential Revision: https://reviews.llvm.org/D78317
The function attribute in generic ops is not paying for itself.
A region is the more standardized way of specifying a custom computation.
If needed this region can call a function directly.
This is deemed more natural than managing a dedicated function attribute.
This also simplifies named ops generation by trimming unnecessary complexity.
Differential Revision: https://reviews.llvm.org/D78266
OpBase.td defined attributes kind for all integer types expect index. This
commit fixes that by adding an IndexAttr attribute kind. Update the
respective tests.
Differential Revision: https://reviews.llvm.org/D78195
This change makes the ModuleTranslation threadsafe by locking on the
LLVMContext. Furthermore, we now clone the llvm module into a new
context when compiling to PTX similar to what the OrcJit does.
Differential Revision: https://reviews.llvm.org/D78207
Summary:
OpBase.td defined attributes kind for all integer types expect index. This
commit fixes that by adding an IndexAttr attribute kind.
Differential Revision: https://reviews.llvm.org/D78195
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
This revision introduces a utility to unswitch affine.for/parallel loops
by hoisting affine.if operations past surrounding affine.for/parallel.
The hoisting works for both perfect/imperfect nests and in the presence
of else blocks. The hoisting is currently to as outermost a level as
possible. Uses a test pass to test the utility.
Add convenience method Operation::getParentWithTrait<Trait>.
Depends on D77487.
Differential Revision: https://reviews.llvm.org/D77870
Similarly to actual LLVM IR, and to `llvm.mlir.func`, allow the custom syntax
of `llvm.mlir.global` to omit the linkage keyword. If omitted, the linkage is
assumed to be external. This makes the modeling of globals in the LLVM dialect
more consistent, both within the dialect and with LLVM IR.
Differential Revision: https://reviews.llvm.org/D78096
Introduce mlir::applyOpPatternsAndFold which applies patterns as well as
any folding only on a specified op (in contrast to
applyPatternsAndFoldGreedily which applies patterns only on the regions
of an op isolated from above). The caller is made aware of the op being
folded away or erased.
Depends on D77485.
Differential Revision: https://reviews.llvm.org/D77487
This class implements a switch-like dispatch statement for a value of 'T' using dyn_cast functionality. Each `Case<T>` takes a callable to be invoked if the root value isa<T>, the callable is invoked with the result of dyn_cast<T>() as a parameter.
Differential Revision: https://reviews.llvm.org/D78070
These have proved incredibly useful for interleaving values between a range w.r.t to streams. After this revision, the mlir/Support/STLExtras.h is empty. A followup revision will remove it from the tree.
Differential Revision: https://reviews.llvm.org/D78067
The inversePermutation method returns a null map on failure. Update
uses of this method within Linalg to handle this. In LinalgToLoops the
null return value was used to emit scalar code. Modify that to return
failure, and emit scalar implementation when affine map is "empty",
i.e. 1 dims, 0 symbols and no result exprs.
Differential Revision: https://reviews.llvm.org/D77964
Summary:
This operation occurs during collapseParallelLoops, so we constant fold
them also to allow more situations of determining a loop invariant upper
bound when lowering to the GPU dialect from the Loop dialect.
Differential Revision: https://reviews.llvm.org/D77723
Summary: Functional.h contains many different methods that have a direct, and more efficient, equivalent in LLVM. This revision replaces all usages with the LLVM equivalent, and removes the header. This is part of larger cleanup, pr45513, merging MLIR support facilities into LLVM.
Differential Revision: https://reviews.llvm.org/D78053
The invertPermutation method does not return a nullptr anymore, but
rather returns an empty map for the scalar case. Update the check in
LinalgToLoops to reflect this.
Also add test case for generating scalar code.
The outer parallel loops of a linalg operation is lowered to
loop.parallel, with the other loops lowered to loop.for. This gets the
lowering to loop.parallel on par with the loop.for lowering. In future
the reduction loop could also be lowered to loop.parallel.
Also add a utility function that returns the loops that are
created.
Differential Revision: https://reviews.llvm.org/D77678
NFC clean up for simplify-affine-structures test cases. Rename sets
better; avoid suffix numbers; move outlined definitions close to use.
This is in preparation for other functionality updates.
Differential Revision: https://reviews.llvm.org/D78017
This commit added stride support in runtime array types. It also
adjusted the assembly form for the stride from `[N]` to `stride=N`.
This makes the IR more readable, especially for the cases where
one mix array types and struct types.
Differential Revision: https://reviews.llvm.org/D78034
Summary: This revision makes the registration of command line options for these two files manual with `registerMLIRContextCLOptions` and `registerAsmPrinterCLOptions` methods. This removes the last remaining static constructors within lib/.
Differential Revision: https://reviews.llvm.org/D77960
Summary: This revision adds support for specifying operands or results as "optional". This is a special case of variadic where the number of elements is either 0 or 1. Operands and results of this kind will have accessors generated using Value instead of the range types, making it more natural to interface with.
Differential Revision: https://reviews.llvm.org/D77863
Summary:
The string in the location is used to provide metadata for the fused location
or create a NamedLoc. This allows tagging individual locations to convey
additional rewrite information.
Differential Revision: https://reviews.llvm.org/D77840
Summary:
This revision adds a tool that generates the ODS and C++ implementation for "named" Linalg ops according to the [RFC discussion](https://llvm.discourse.group/t/rfc-declarative-named-ops-in-the-linalg-dialect/745).
While the mechanisms and language aspects are by no means set in stone, this revision allows connecting the pieces end-to-end from a mathematical-like specification.
Some implementation details and short-term decisions taken for the purpose of bootstrapping and that are not set in stone include:
1. using a "[Tensor Comprehension](https://arxiv.org/abs/1802.04730)-inspired" syntax
2. implicit and eager discovery of dims and symbols when parsing
3. using EDSC ops to specify the computation (e.g. std_addf, std_mul_f, ...)
A followup revision will connect this tool to tablegen mechanisms and allow the emission of named Linalg ops that automatically lower to various loop forms and run end to end.
For the following "Tensor Comprehension-inspired" string:
```
def batch_matmul(A: f32(Batch, M, K), B: f32(K, N)) -> (C: f32(Batch, M, N)) {
C(b, m, n) = std_addf<k>(std_mulf(A(b, m, k), B(k, n)));
}
```
With -gen-ods-decl=1, this emits (modulo formatting):
```
def batch_matmulOp : LinalgNamedStructured_Op<"batch_matmul", [
NInputs<2>,
NOutputs<1>,
NamedStructuredOpTraits]> {
let arguments = (ins Variadic<LinalgOperand>:$views);
let results = (outs Variadic<AnyRankedTensor>:$output_tensors);
let extraClassDeclaration = [{
llvm::Optional<SmallVector<StringRef, 8>> referenceIterators();
llvm::Optional<SmallVector<AffineMap, 8>> referenceIndexingMaps();
void regionBuilder(ArrayRef<BlockArgument> args);
}];
let hasFolder = 1;
}
```
With -gen-ods-impl, this emits (modulo formatting):
```
llvm::Optional<SmallVector<StringRef, 8>> batch_matmul::referenceIterators() {
return SmallVector<StringRef, 8>{ getParallelIteratorTypeName(),
getParallelIteratorTypeName(),
getParallelIteratorTypeName(),
getReductionIteratorTypeName() };
}
llvm::Optional<SmallVector<AffineMap, 8>> batch_matmul::referenceIndexingMaps()
{
MLIRContext *context = getContext();
AffineExpr d0, d1, d2, d3;
bindDims(context, d0, d1, d2, d3);
return SmallVector<AffineMap, 8>{
AffineMap::get(4, 0, {d0, d1, d3}),
AffineMap::get(4, 0, {d3, d2}),
AffineMap::get(4, 0, {d0, d1, d2}) };
}
void batch_matmul::regionBuilder(ArrayRef<BlockArgument> args) {
using namespace edsc;
using namespace intrinsics;
ValueHandle _0(args[0]), _1(args[1]), _2(args[2]);
ValueHandle _4 = std_mulf(_0, _1);
ValueHandle _5 = std_addf(_2, _4);
(linalg_yield(ValueRange{ _5 }));
}
```
Differential Revision: https://reviews.llvm.org/D77067
This patch adds support for taskwait and taskyield operations in OpenMP dialect and translation of the these constructs to LLVM IR. The OpenMP IRBuilder is used for this translation.
The patch includes code changes and a testcase modifications.
Differential Revision: https://reviews.llvm.org/D77634
Rename mlir::applyPatternsGreedily -> applyPatternsAndFoldGreedily. The
new name is a more accurate description of the method - it performs
both, application of the specified patterns and folding of all ops in
the op's region irrespective of whether any patterns have been supplied.
Differential Revision: https://reviews.llvm.org/D77478
Introduce a new operation property / trait (AutomaticAllocationScope)
for operations with regions that define a new scope for automatic allocations;
such allocations (typically realized on stack) are automatically freed when
control leaves such ops' regions. std.alloca's are freed at the closest
surrounding op that has this trait. All FunctionLike operations should normally
have this trait.
Differential Revision: https://reviews.llvm.org/D77787
Summary:
LLVM matrix intrinsics recently introduced an option to support row-major mode.
This matches the MLIR vector model, this revision switches to row-major.
A corner case related to degenerate sizes was also fixed upstream.
This revision removes the guard against this corner case.
A bug was uncovered on the output vector construction which this revision also fixes.
Lastly, this has been tested on a small size and benchmarked independently: no visible performance regression is observed.
In the future, when matrix intrinsics support per op attribute, we can more aggressively translate to that and avoid inserting MLIR-level transposes.
This has been tested independently to work on small matrices.
Differential Revision: https://reviews.llvm.org/D77761
Summary:
This revision adds support to lower 1-D vector transfers to LLVM.
A mask of the vector length is created that compares the base offset + linear index to the dim of the vector.
In each position where this does not overflow (i.e. offset + vector index < dim), the mask is set to 1.
A notable fact is that the lowering uses llvm.dialect_cast to allow writing code in the simplest form by targeting the simplest mix of vector and LLVM dialects and
letting other conversions kick in.
Differential Revision: https://reviews.llvm.org/D77703
The "cblas" lib under mlir/test is meant as a simple integration demonstration.
However it is installed and ends up conflicting with external projects who want to
define the real cblas.
Rename to avoid conflicts.
Differential revision: https://reviews.llvm.org/D76615
Summary: Some pattern rewriters, like dialect conversion, prohibit the unbounded recursion(or reapplication) of patterns on generated IR. Most patterns are not written with recursive application in mind, so will generally explode the stack if uncaught. This revision adds a hook to RewritePattern, `hasBoundedRewriteRecursion`, to signal that the pattern can safely be applied to the generated IR of a previous application of the same pattern. This allows for establishing a contract between the pattern and rewriter that the pattern knows and can handle the potential recursive application.
Differential Revision: https://reviews.llvm.org/D77782
This revision builds a simple "fused pass" consisting of 2 levels of tiling, memory promotion and vectorization using linalg transformations written as composable pattern rewrites.
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:
Update ShapeCastOp folder to use producer-consumer value forwarding.
Support is added for tracking sub-vectors through trivial shape cast operations,
where the sub-vector shape is preserved across shape cast operations and only
leading ones are added or removed.
Support is preserved for cancelling shape cast operations.
One unit test is added and two are updated.
Reviewers: aartbik, nicolasvasilache
Reviewed By: aartbik, nicolasvasilache
Subscribers: frgossen, mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, arpith-jacob, mgester, lucyrfox, liufengdb, Joonsoo, grosul1, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D77253
Support to recognize and deal with aligned_alloc was recently added to
LLVM's TLI/MemoryBuiltins and its various optimization passes. This
revision adds support for generation of aligned_alloc's when lowering
AllocOp from std to LLVM. Setting 'use-aligned_alloc=1' will lead to
aligned_alloc being used for all heap allocations. An alignment and size
that works with the constraints of aligned_alloc is chosen.
Using aligned_alloc is preferable to "using malloc and adjusting the
allocated pointer to align for indexing" because the pointer access
arithmetic done for the latter only makes it harder for LLVM passes to
deal with for analysis, optimization, attribute deduction, and rewrites.
Differential Revision: https://reviews.llvm.org/D77528
This revision removes the reliance of Promotion on `linalg.slice` which is meant
for the rank-reducing case.
Differential Revision: https://reviews.llvm.org/D77676
Invoke `keep()` on the output file of `mlir-opt` in case the invocation of `MlirOptMain` was successful, to make sure the output file is not deleted on exit from `mlir-opt`.
Fixes a similar problem in `standalone-opt` from the example for an out-of-tree, standalone MLIR dialect.
This revision also adds a missing parameter to the invocation of `MlirOptMain` in `standalone-opt`.
Differential Revision: https://reviews.llvm.org/D77643
Error messages for the custom assembly format are difficult to understand
because there are no line numbers. This happens because the assembly format
is parsed as a standalone line, separate from it's parent file, with no useful
location information. Fixing this properly probably requires quite a bit
of invasive plumbing through the SourceMgr, similar to how included files
are handled
This proposal is a less invasive short term solution. When generating an
error message we generate an additional note which at least properly describes
the operation definition the error occured in, if not the actual line number
of the assemblyFormat definition.
A typical message is like:
error: type of operand #0, named 'operand', is not buildable and a buildable type cannot be inferred
$operand type($result) attr-dict
^
/src/llvm-project/mlir/test/mlir-tblgen/op-format-spec.td:296:1: note: in custom assembly format for this operation
def ZCoverageInvalidC : TestFormat_Op<"variable_invalid_c", [{
^
note: suggest adding a type constraint to the operation or adding a 'type($operand)' directive to the custom assembly format
$operand type($result) attr-dict
^
Differential Revision: https://reviews.llvm.org/D77488
The messages are somewhat cryptic, since they are not complete sentences,
include lots of ambiguous words, like 'format' which are hard to parse,
and include names from the users code which may, or may not make sense in
the context of the message. Start to clean this up and provide some
guidance for fixes.
Also, add a test for one of the messages which didn't have a test at all.
Differential Revision: https://reviews.llvm.org/D77449
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
ModulePass doesn't provide any special utilities and thus doesn't give enough benefit to warrant a special pass class. This revision replaces all usages with the more general OperationPass.
Differential Revision: https://reviews.llvm.org/D77339
Summary:
Add directive to indicate the location to give to op being created. This
directive is optional and if unused the location will still be the fused
location of all source operations.
Currently this directive only works with other op locations, reusing an
existing op location or a fusion of op locations. But doesn't yet support
supplying metadata for the FusedLoc.
Based off initial revision by antiagainst@ and effectively mirrors GlobalIsel
debug_locations directive.
Differential Revision: https://reviews.llvm.org/D77649
Summary:
* Removal of FxpMathOps was discussed on the mailing list.
* Will send a courtesy note about also removing the Quantizer (which had some dependencies on FxpMathOps).
* These were only ever used for experimental purposes and we know how to get them back from history as needed.
* There is a new proposal for more generalized quantization tooling, so moving these older experiments out of the way helps clean things up.
Subscribers: mgorny, mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, liufengdb, Joonsoo, grosul1, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D77479
If we have two back-to-back loops with block arguments, the OpPhi
instructions generated for the second loop's block arguments should
have use the merge block of the first SPIR-V loop structure as
their incoming parent block.
Differential Revision: https://reviews.llvm.org/D77543
Introduce the alloca op for stack memory allocation. When converting to the
LLVM dialect, this is lowered to an llvm.alloca. Refactor the std to
llvm conversion for alloc op to reuse with alloca. Drop useAlloca option
with alloc op lowering.
Differential Revision: https://reviews.llvm.org/D76602
Fix point-wise copy generation to work with bounds that have max/min.
Change structure of copy loop nest to use absolute loop indices and
subtracting base from the indexes of the fast buffers. Update supporting
utilities: Fix FlatAffineConstraints::getLowerAndUpperBound to look at
equalities as well and for a missing division. Update unionBoundingBox
to not discard common constraints (leads to a tighter system). Update
MemRefRegion::getConstantBoundingSizeAndShape to add memref dimension
constraints. Run removeTrivialRedundancy at the end of
MemRefRegion::compute. Run single iteration loop promotion and
load/store canonicalization after affine data copy (in its test pass as
well).
Differential Revision: https://reviews.llvm.org/D77320
Summary:
This revision adds a tensor_reshape operation that operates on tensors.
In the tensor world the constraints are less stringent and we can allow more
arbitrary dynamic reshapes, as long as they are contractions.
The expansion of a dynamic dimension into multiple dynamic dimensions is under-specified and is punted on for now.
Differential Revision: https://reviews.llvm.org/D77360
Add a pattern rewriter utility to erase blocks (while notifying the
pattern rewriting driver of the erased ops). Use this to remove trivial
else blocks in affine.if ops.
Differential Revision: https://reviews.llvm.org/D77083
Summary: This revision adds support for marking the last region as variadic in the ODS region list with the VariadicRegion directive.
Differential Revision: https://reviews.llvm.org/D77455
Summary: The attribute grammar includes an optional trailing colon type, so for attributes without a constant buildable type this will generally lead to unexpected and undesired behavior. Given that, it's better to just error out on these cases.
Differential Revision: https://reviews.llvm.org/D77293
Summary:
A recent extension allowed the `loop.if` operation to return results yielded by
its regions. However, such operations could not be lowered to a CFG of standard
operations because it would have required to modify the argument list of a
block, which is not allowed in a conversion pattern. Now that the conversion
infrastructure supports block creation, use it to create a block with an
argument list that dominates the operations following the `loop.if` and forward
the results as arguments of this block.
Depends On D77416
Differential Revision: https://reviews.llvm.org/D77418
Summary:
Linalg makes it possible to interface codegen with externally precompiled HPC libraries. The mechanism to allow such interop uses a normalized ABI and the emission of C interface wrappers.
The mechanism controlling these C interface emission is too aggressive and makes it very easy to obtained undefined symbols for external function (e.g. the ones coming from libm).
This revision uses the newly introduced llvm.emit_c_interface function attribute which allows controlling this behavior at a function granularity. As a consequence LinalgToLLVM does not need to activate the C wrapper emission when adding the StdToLLVM patterns.
Differential Revision: https://reviews.llvm.org/D77364
PatternRewriter and derived classes provide a set of virtual methods to
manipulate blocks, which ConversionPatternRewriter overrides to keep track of
the manipulations and undo them in case the conversion fails. However, one can
currently create a block only by splitting another block into two. This not
only makes the API inconsistent (`splitBlock` is allowed in conversion
patterns, but `createBlock` is not), but it also make it impossible for one to
create blocks with argument lists different from those of already existing
blocks since in-place block updates are not supported either. Such
functionality precludes dialect conversion infrastructure from being used more
extensively on region-containing ops, for example, for value-returning "if"
operations. At the same time, ConversionPatternRewriter already allows one to
undo block creation as block creation is one of the primitive operations in
already supported region inlining.
Support block creation in conversion patterns by hooking `createBlock` on the
block action undo mechanism. This requires to make `Builder::createBlock`
virtual, similarly to Op insertion. This is a minimal change to the Builder
infrastructure that will later help support additional use cases such as block
signature changes. `createBlock` now additionally takes the types of the block
arguments that are added immediately so as to avoid in-place argument list
manipulation that would be illegal in conversion patterns.
Two back-to-back transpose operations are combined into a single transpose, which uses a combination of their permutation vectors.
Differential Revision: https://reviews.llvm.org/D77331
A certain number of EDSCs have a named form (e.g. `linalg.matmul`) and a generic form (e.g. `linalg.generic` with matmul traits).
Despite living in different namespaces, using the same name is confusiong in clients.
Rename them as `linalg_matmul` and `linalg_generic_matmul` respectively.
C interface emission is controlled by a flag and has coarse granularity.
With this coarse control, interfaces are emitted for all external functions.
This makes is easy to get undefined symbols.
This revision adds support for controlling per-function emission with an "emit_c_interface" attribute.
Summary:
LLVM IR functions can have arbitrary attributes attached to them, some of which
affect may affect code transformations. Until we can model all attributes
consistently, provide a pass-through mechanism that forwards attributes from
the LLVMFuncOp in MLIR to LLVM IR functions during translation. This mechanism
relies on LLVM IR being able to recognize string representations of the
attributes and performs some additional checking to avoid hitting assertions
within LLVM code.
Differential Revision: https://reviews.llvm.org/D77072
Add a method that given an affine map returns another with just its unique
results. Use this to drop redundant bounds in max/min for affine.for. Update
affine.for's canonicalization pattern and createCanonicalizedForOp to use
this.
Differential Revision: https://reviews.llvm.org/D77237
Summary:
This is to allow optimizations like loop invariant code motion to work
on the ParallelOp.
Additional small cleanup on the ForOp implementation of
LoopLikeInterface and the test file of loop-invariant-code-motion.
Differential Revision: https://reviews.llvm.org/D77128
Summary:
The RAW fusion happens only if the produecer block dominates the consumer block.
The WAW pattern also works with the precondition. I.e., if a producer can
dominate the consumer, they can fairly fuse together.
Since they are all tilable, we can think the pattern like this way:
Input:
```
linalg_op1 view
tile_loop
subview_2
linalg_op2 subview_2
```
Tile the first Linalg op as same as the second Linalg.
```
tile_loop
subview_1
linalg_op1 subview_1
tile_loop
subview_2
liangl_op2 subview_2
```
Since the first Linalg op is tilable in the same way and the computation are
independently, it's fair to fuse it with the second Linalg op.
```
tile_loop
subview_1
linalg_op1 subview_1
linalg_op2 subview_2
```
In short, this patch includes:
- Handling both RAW and WAW pattern.
- Adding a interface method to get input and output buffers.
- Exposing a method to get a StringRef of a dependency type.
- Fixing existing WAW tests and add one more use case: initialize the buffer
before conv op.
Differential Revision: https://reviews.llvm.org/D76897
Summary:
Performs an N-D pooling operation similarly to the description in the TF
documentation:
https://www.tensorflow.org/api_docs/python/tf/nn/pool
Different from the description, this operation doesn't perform on batch and
channel. It only takes tensors of rank `N`.
```
output[x[0], ..., x[N-1]] =
REDUCE_{z[0], ..., z[N-1]}
input[
x[0] * strides[0] - pad_before[0] + dilation_rate[0]*z[0],
...
x[N-1]*strides[N-1] - pad_before[N-1] + dilation_rate[N-1]*z[N-1]
],
```
The required optional arguments are:
- strides: an i64 array specifying the stride (i.e. step) for window
loops.
- dilations: an i64 array specifying the filter upsampling/input
downsampling rate
- padding: an i64 array of pairs (low, high) specifying the number of
elements to pad along a dimension.
If strides or dilations attributes are missing then the default value is
one for each of the input dimensions. Similarly, padding values are zero
for both low and high in each of the dimensions, if not specified.
Differential Revision: https://reviews.llvm.org/D76414
Move lower-affine.mlir from test/Transforms to
test/Conversion/AffineToStandard/. Other related NFC.
Signed-off-by: Uday Bondhugula <uday@polymagelabs.com>
Differential Revision: https://reviews.llvm.org/D77008
Existing tiling implementation of Linalg would still work for tiling
the batch dimensions of the convolution op.
Differential Revision: https://reviews.llvm.org/D76637
Summary:
Add support for TupleGetOp folding through InsertSlicesOp and ExtractSlicesOp.
Vector-to-vector transformations for unrolling and lowering to hardware vectors
can generate chains of structured vector operations (InsertSlicesOp,
ExtractSlicesOp and ShapeCastOp) between the producer of a hardware vector
value and its consumer. Because InsertSlicesOp, ExtractSlicesOp and ShapeCastOp
are structured, we can track the location (tuple index and vector offsets) of
the consumer vector value through the chain of structured operations to the
producer, enabling a much more powerful producer-consumer fowarding of values
through structured ops and tuple, which in turn enables a more powerful
TupleGetOp folding transformation.
Reviewers: nicolasvasilache, aartbik
Reviewed By: aartbik
Subscribers: grosul1, mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, arpith-jacob, mgester, lucyrfox, liufengdb, Joonsoo, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D76889
Rewrite mlir::permuteLoops (affine loop permutation utility) to fix
incorrect approach. Avoiding using sinkLoops entirely - use single move
approach. Add test pass.
This fixes https://bugs.llvm.org/show_bug.cgi?id=45328
Depends on D77003.
Signed-off-by: Uday Bondhugula <uday@polymagelabs.com>
Differential Revision: https://reviews.llvm.org/D77004
Summary: This revision updates the SourceMgrDiagnosticHandler to not print the source location of a note if it is the same location as the previously printed diagnostic. This helps avoid redundancy, and potential confusion, when looking at the diagnostic output.
Differential Revision: https://reviews.llvm.org/D76787
Move test/lib/TestDialect to test/lib/Dialect/Test - makes the dir
structure more uniform.
Signed-off-by: Uday Bondhugula <uday@polymagelabs.com>
Differential Revision: https://reviews.llvm.org/D76677
This patch introduces a utility to separate full tiles from partial
tiles when tiling affine loop nests where trip counts are unknown or
where tile sizes don't divide trip counts. A conditional guard is
generated to separate out the full tile (with constant trip count loops)
into the then block of an 'affine.if' and the partial tile to the else
block. The separation allows the 'then' block (which has constant trip
count loops) to be optimized better subsequently: for eg. for
unroll-and-jam, register tiling, vectorization without leading to
cleanup code, or to offload to accelerators. Among techniques from the
literature, the if/else based separation leads to the most compact
cleanup code for multi-dimensional cases (because a single version is
used to model all partial tiles).
INPUT
affine.for %i0 = 0 to %M {
affine.for %i1 = 0 to %N {
"foo"() : () -> ()
}
}
OUTPUT AFTER TILING W/O SEPARATION
map0 = affine_map<(d0) -> (d0)>
map1 = affine_map<(d0)[s0] -> (d0 + 32, s0)>
affine.for %arg2 = 0 to %M step 32 {
affine.for %arg3 = 0 to %N step 32 {
affine.for %arg4 = #map0(%arg2) to min #map1(%arg2)[%M] {
affine.for %arg5 = #map0(%arg3) to min #map1(%arg3)[%N] {
"foo"() : () -> ()
}
}
}
}
OUTPUT AFTER TILING WITH SEPARATION
map0 = affine_map<(d0) -> (d0)>
map1 = affine_map<(d0) -> (d0 + 32)>
map2 = affine_map<(d0)[s0] -> (d0 + 32, s0)>
#set0 = affine_set<(d0, d1)[s0, s1] : (-d0 + s0 - 32 >= 0, -d1 + s1 - 32 >= 0)>
affine.for %arg2 = 0 to %M step 32 {
affine.for %arg3 = 0 to %N step 32 {
affine.if #set0(%arg2, %arg3)[%M, %N] {
// Full tile.
affine.for %arg4 = #map0(%arg2) to #map1(%arg2) {
affine.for %arg5 = #map0(%arg3) to #map1(%arg3) {
"foo"() : () -> ()
}
}
} else {
// Partial tile.
affine.for %arg4 = #map0(%arg2) to min #map2(%arg2)[%M] {
affine.for %arg5 = #map0(%arg3) to min #map2(%arg3)[%N] {
"foo"() : () -> ()
}
}
}
}
}
The separation is tested via a cmd line flag on the loop tiling pass.
The utility itself allows one to pass in any band of contiguously nested
loops, and can be used by other transforms/utilities. The current
implementation works for hyperrectangular loop nests.
Signed-off-by: Uday Bondhugula <uday@polymagelabs.com>
Differential Revision: https://reviews.llvm.org/D76700
The Dominance analysis currently misses a utility function to find the nearest common dominator of two given blocks. This is required for a huge variety of different control-flow analyses and transformations. This commit adds this function and moves the getNode function from DominanceInfo to DominanceInfoBase, as it also works for post dominators.
Differential Revision: https://reviews.llvm.org/D75507
This change adds a new option to the StandardToLLVM lowering to configure
the bitwidth of the index type independently of the target architecture's
pointer size.
Differential revision: https://reviews.llvm.org/D76353
It's common in many dialects to use tensors to themselves hold tensor shapes (for example, the shape is itself the result of some non-trivial calculation). Currently, such dialects have to use `tensor<?xi64>` or worse (like allowing either i32 or i64 tensors to represent shapes). `tensor<?xindex>` is the natural type to represent this, but is currently disallowed. This patch allows it.
Differential Revision: https://reviews.llvm.org/D76726
This allows conversion of a ParallelLoop from N induction variables to
some nuber of induction variables less than N.
The first intended use of this is for the GPUDialect to convert
ParallelLoops to iterate over 3 dimensions so they can be launched as
GPU Kernels.
To implement this:
- Normalize each iteration space of the ParallelLoop
- Use the same induction variable in a new ParallelLoop for multiple
original iterations.
- Split the new induction variable back into the original set of values
inside the body of the ParallelLoop.
Subscribers: mgorny, mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, aartbik, liufengdb, Joonsoo, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D76363
- add method to get back an integer set from flat affine constraints;
this allows a round trip
- use this to complete the simplification of integer sets in
-simplify-affine-structures
- update FlatAffineConstraints::removeTrivialRedundancy to also do GCD
tightening and normalize by GCD (while still keeping it linear time).
Signed-off-by: Uday Bondhugula <uday@polymagelabs.com>
Summary:
The test performs add on vector<16384xf32> with
number of workgroups = (128, 1, 1)
local workgroup size = (128, 1, 1)
On a NVIDIA Quadro P1000, I see the following results:
Command buffer submit time: 13us
Compute shader execution time: 19.616us
Differential Revision: https://reviews.llvm.org/D76799
Summary:
The attribute parser fails to correctly parse unsigned 64 bit
attributes as the check `isNegative ? (int64_t)-val.getValue() >= 0
: (int64_t)val.getValue() < 0` will falsely detect an overflow for
unsigned values larger than 2^63-1.
This patch reworks the overflow logic to instead of doing arithmetic
on int64_t use APInt::isSignBitSet() and knowledge of the attribute
type.
Test-cases which verify the de-facto behavior of the parser and
triggered the previous faulty handing of unsigned 64 bit attrbutes are
also added.
Differential Revision: https://reviews.llvm.org/D76493
Summary: The current ConvertStandardToLLVM phase lowers the standard TanHOp to function calls to external tanh symbols. However, this leads to misunderstandings since these external symbols are not defined anywhere. This commit removes the TanHOp lowering functionality from ConvertStandardToLLVM, adapts the LowerGpuOpsToNVVMOps and LowerGpuOpsToROCDLOps passes and adjusts the affected test cases.
Reviewers: mravishankar, herhut
Subscribers: jholewinski, mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, nicolasvasilache, csigg, arpith-jacob, mgester, lucyrfox, aartbik, liufengdb, Joonsoo, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D75509
gpu.launch
Current implementation of lowering from loop.parallel to gpu.launch
uses a DictionaryAttr to specify the mapping. Moving this attribute to
be auto-generated from specification as a StructAttr. This simplifies
a lot the logic of looking up and creating this attribute.
Differential Revision: https://reviews.llvm.org/D76165
Summary:
While here, simplify the lexer a bit by eliminating the unneeded 'operator'
classification of certain sigils, they can just be treated as 'punctuation'.
Reviewers: rriddle!
Subscribers: mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, liufengdb, Joonsoo, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D76647
Summary:
This allows the custom parser/printer hooks to do interesting things with
the SSA names. This patch:
- Adds a new 'getResultName' method to OpAsmParser that allows a parser
implementation to get information about its result names, along with
a getNumResults() method that allows op parser impls to know how many
results are expected.
- Adds a OpAsmPrinter::printOperand overload that takes an explicit stream.
- Adds a test.string_attr_pretty_name operation that uses these hooks to
do fancy things with the result name.
Reviewers: rriddle!
Subscribers: mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, liufengdb, Joonsoo, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D76205
Move some of the affine transforms and their test cases to their
respective dialect directory. This patch does not complete the move, but
takes care of a good part.
Renames: prefix 'affine' to affine loop tiling cl options,
vectorize -> super-vectorize
Signed-off-by: Uday Bondhugula <uday@polymagelabs.com>
Differential Revision: https://reviews.llvm.org/D76565
Summary:
This removes the static pass registration, and also cleans up some lingering technical debt.
Differential Revision: https://reviews.llvm.org/D76554
Summary:
This file only contains references to test passes, and was never removed when the test passes were moved to the test/ directory.
Differential Revision: https://reviews.llvm.org/D76553
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
The Vector Dialect [document](https://mlir.llvm.org/docs/Dialects/Vector/) discusses the vector abstractions that MLIR supports and the various tradeoffs involved.
One of the layer that is missing in OSS atm is the Hardware Vector Ops (HWV) level.
This revision proposes an AVX512-specific to add a new Dialect/Targets/AVX512 Dialect that would directly target AVX512-specific intrinsics.
Atm, we rely too much on LLVM’s peephole optimizer to do a good job from small insertelement/extractelement/shufflevector. In the future, when possible, generic abstractions such as VP intrinsics should be preferred.
The revision will allow trading off HW-specific vs generic abstractions in MLIR.
Differential Revision: https://reviews.llvm.org/D75987
Summary: This patch add tests when lowering multiple `gpu.all_reduce` operations in the same kernel. This was previously failing.
Differential Revision: https://reviews.llvm.org/D75930
Summary:
These are not supported by any of the code using `type_cast`. In the general
case, such casting would require memrefs to handle a non-contiguous vector
representation or misaligned vectors (e.g., if the offset of the source memref
is not divisible by vector size, since offset in the target memref is expressed
in the number of elements).
Differential Revision: https://reviews.llvm.org/D76349
Summary:
Utility to perform CallOp Dialect conversion, specifically handling cases where
an argument type has changed and the corresponding CallOp needs to be updated.
Differential Revision: https://reviews.llvm.org/D76326
This commit merges the DRR pattern for std.constant to spv.constant
conversion into the C++ OpConversionPattern. This allows us to have
remove the DRR pattern file. Along the way, this commit enhanced
std.constant to spv.constant conversion to consider type conversions,
which means converting the underlying attributes if necessary.
Differential Revision: https://reviews.llvm.org/D76246
Previously we have a few patterns that were written with DRR. DRR
at the moment does not work nicely with dialect conversion framework.
It generates normal RewritePatterns, while the dialect conversion
framework requires ConversionPatterns to take into consideration
the type conversion. So this commit starts to change existing DRR
patterns for standard ops to OpConversionPattern to incorporate the
SPIR-V type conversion. All patterns are converted except the one
for constant ops, which will happen in a subsequent commit.
Differential Revision: https://reviews.llvm.org/D76245
Non-32-bit scalar types requires special hardware support that may
not exist on all Vulkan-capable GPUs. This is reflected as non-32-bit
scalar types require special capabilities or extensions to be used.
This commit makes SPIRVTypeConverter target environment aware so
that it can properly convert standard types to what is accepted on
the target environment.
Right now if a scalar type bitwidth is not supported in the target
environment, we use 32-bit unconditionally. This requires Vulkan
runtime to also feed in data with a matched bitwidth and layout,
especially for interface types. The Vulkan runtime can do that by
inspecting the SPIR-V module. Longer term, we might want to introduce
a way to control how such case are handled and explicitly fail
if wanted.
Differential Revision: https://reviews.llvm.org/D76244
This commit unifies target environment queries into a new wrapper
class spirv::TargetEnv and shares across various places needing
the functionality. We still create multiple instances of TargetEnv
though given the parent components (type converters, passes,
conversion targets) have different lifetimes.
In the meantime, LowerABIAttributesPass is updated to take into
consideration the target environment, which requires updates to
tests to provide that.
Differential Revision: https://reviews.llvm.org/D76242
Previously we only consider the version/extension/capability requirement
on the op itself. This commit updates SPIRVConversionTarget to also
take into consideration the values' types when deciding op legality.
Differential Revision: https://reviews.llvm.org/D75876
Previously in SPIRVTypeConverter, we always convert memref types
to StorageBuffer regardless of their memory spaces. This commit
fixes that to let the conversion to look into memory space
properly. For this purpose, a mapping between SPIR-V storage class
and memref memory space is introduced. The mapping is arbitary
decided at the moment and the hope is that we can leverage
string memory space later to be more clear.
Now spv.interface_var_abi cannot contain storage class unless it's
attached to a scalar value, where we need the storage class as side
channel information. Verifications and tests are properly adjusted.
Differential Revision: https://reviews.llvm.org/D76241
Summary: This is somewhat complex(annoying) as it involves directly tracking the uses within each of the callgraph nodes, and updating them as needed during inlining. The benefit of this is that we can have a more exact cost model, enable inlining some otherwise non-inlinable cases, and also ensure that newly dead callables are properly disposed of.
Differential Revision: https://reviews.llvm.org/D75476
Summary:
This revision restructures the calling of vector transforms to make it more flexible to ask for lowering through LLVM matrix intrinsics.
This also makes sure we bail out in degenerate cases (i.e. 1) in which LLVM complains about not being able to scalarize.
Differential Revision: https://reviews.llvm.org/D76266
Summary:
Renamed QuantOps to Quant to avoid the Ops suffix. All dialects will contain
ops, so the Ops suffix is redundant.
Differential Revision: https://reviews.llvm.org/D76318
Summary:
This revision adds a new hook, `notifyMatchFailure`, that allows for notifying the rewriter that a match failure is coming with the provided reason. This hook takes as a parameter a callback that fills a `Diagnostic` instance with the reason why the match failed. This allows for the rewriter to decide how this information can be displayed to the end-user, and may completely ignore it if desired(opt mode). For now, DialectConversion is updated to include this information in the debug output.
Differential Revision: https://reviews.llvm.org/D76203
MLIR supports terminators that have the same successor block with different
block operands, which cannot be expressed in the LLVM's phi-notation as the
block identifier is used to tell apart the predecessors. This limitation can be
worked around by branching to a new block instead, with this new block
unconditionally branching to the original successor and forwarding the
argument. Until now, this transformation was performed during the conversion
from the Standard to the LLVM dialect. This does not scale well to multiple
dialects targeting the LLVM dialect as all of them would have to be aware of
this limitation and perform the preparatory transformation. Instead, do it as a
separate pass and run it immediately before the translation.
Differential Revision: https://reviews.llvm.org/D75619
A memref argument is converted into a pointer-to-struct argument
of type `{T*, T*, i64, i64[N], i64[N]}*` in the wrapper function,
where T is the converted element type and N is the memref rank.
Differential Revision: https://reviews.llvm.org/D76059
Summary: This adds bitfields that map to the dialect attribute verifier hooks. This also moves over the Test dialect to have its declaration generated.
Differential Revision: https://reviews.llvm.org/D76254
- rename vars that had inst suffixes (due to ops earlier being
known as insts); other renames for better readability
- drop unnecessary matches in test cases
- iterate without block terminator
- comment/doc updates
- instBodySkew -> affineForOpBodySkew
Signed-off-by: Uday Bondhugula <uday@polymagelabs.com>
Differential Revision: https://reviews.llvm.org/D76214
Summary:
This regional op in the QuantOps dialect will be used to wrap
high-precision ops into atomic units for quantization. All the values
used by the internal ops are captured explicitly by the op inputs. The
quantization parameters of the inputs and outputs are stored in the
attributes.
Subscribers: jfb, mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, aartbik, Joonsoo, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D75972
Summary:
To enable this, two changes are needed:
1) Add an optional attribute `padding` to linalg.conv.
2) Compute if the indices accessing is out of bound in the loops. If so, use the
padding value `0`. Otherwise, use the value derived from load.
In the patch, the padding only works for lowering without other transformations,
e.g., tiling, fusion, etc.
Differential Revision: https://reviews.llvm.org/D75722
Summary:
This revision adds lowering of vector.contract to llvm.intr.matrix_multiply.
Note that there is currently a mismatch between the MLIR vector dialect which
expects row-major layout and the LLVM matrix intrinsics which expect column
major layout.
As a consequence, we currently only match a vector.contract with indexing maps
that express column-major matrix multiplication.
Other cases would require additional transposes and it is better to wait for
LLVM intrinsics to provide a per-operation attribute that would specify which
layout is expected.
A separate integration test, not submitted to MLIR core, has independently
verified that correct execution occurs on a 2x2x2 matrix multiplication.
Differential Revision: https://reviews.llvm.org/D76014
Summary:
The direct lowering of vector.broadcast into LLVM has been replaced by
progressive lowering into elementary vector ops. This also required a
small refactoring of a llvm.mlir test that used a direct vector.broadcast
operator (just to define a matmul).
Reviewers: nicolasvasilache, andydavis1, rriddle
Reviewed By: nicolasvasilache
Subscribers: mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, liufengdb, Joonsoo, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D76143
Previously we only consider the version/capability/extension requirements
on ops themselves. Some types in SPIR-V also require special extensions
or capabilities to be used. For example, non-32-bit integers/floats
will require different capabilities and/or extensions depending on
where they are used because it may mean special hardware abilities.
This commit adds query methods to SPIR-V type class hierarchy to support
querying extensions and capabilities. We don't go through ODS for
auto-generating such information given that we don't have them in
SPIR-V machine readable grammar and there are just a few types.
Differential Revision: https://reviews.llvm.org/D75875
This commits changes the definition of spv.module to use the #spv.vce
attribute for specifying (version, capabilities, extensions) triple
so that we can have better API and custom assembly form. Since now
we have proper modelling of the triple, (de)serialization is wired up
to use them.
With the new UpdateVCEPass, we don't need to manually specify the
required extensions and capabilities anymore when creating a spv.module.
One just need to call UpdateVCEPass before serialization to get the
needed version/extensions/capabilities.
Differential Revision: https://reviews.llvm.org/D75872
Creates an operation pass that deduces and attaches the minimal version/
capabilities/extensions requirements for spv.module ops.
For each spv.module op, this pass requires a `spv.target_env` attribute on
it or an enclosing module-like op to drive the deduction. The reason is
that an op can be enabled by multiple extensions/capabilities. So we need
to know which one to pick. `spv.target_env` gives the hard limit as for
what the target environment can support; this pass deduces what are
actually needed for a specific spv.module op.
Differential Revision: https://reviews.llvm.org/D75870
We also need the (version, capabilities, extensions) triple on the
spv.module op. Thus far we have been using separate 'extensions'
and 'capabilities' attributes there and 'version' is missing. Creating
a separate attribute for the trip allows us to reuse the assembly
form and verification.
Differential Revision: https://reviews.llvm.org/D75868
HasNoSideEffect can now be implemented using the MemoryEffectInterface, removing the need to check multiple things for the same information. This also removes an easy foot-gun for users as 'Operation::hasNoSideEffect' would ignore operations that dynamically, or recursively, have no side effects. This also leads to an immediate improvement in some of the existing users, such as DCE, now that they have access to more information.
Differential Revision: https://reviews.llvm.org/D76036
The current mechanism for identifying is a bit hacky and extremely adhoc, i.e. we explicit check 1-result, 0-operand, no side-effect, and always foldable and then assume that this is a constant. Adding a trait adds structure to this, and makes checking for a constant much more efficient as we can guarantee that all of these things have already been verified.
Differential Revision: https://reviews.llvm.org/D76020
Summary:
This replaces the direct lowering of vector.outerproduct to LLVM with progressive lowering into elementary vectors ops to avoid having the similar lowering logic at several places.
NOTE1: with the new progressive rule, the lowered llvm is slightly more elaborate than with the direct lowering, but the generated assembly is just as optimized; still if we want to stay closer to the original, we should add a "broadcast on extract" to shuffle rewrite (rather than special cases all the lowering steps)
NOTE2: the original outerproduct lowering code should now be removed but some linalg test work directly on vector and contain some dead code, so this requires another CL
Reviewers: nicolasvasilache, andydavis1
Reviewed By: nicolasvasilache, andydavis1
Subscribers: mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, liufengdb, Joonsoo, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D75956
Summary:
affineDataCopyGenerate is a monolithinc function that
combines several steps for good reasons, but it makes customizing
the behaivor even harder. The major two steps by affineDataCopyGenerate are:
a) Identify interesting memrefs and collect their uses.
b) Create new buffers to forward these uses.
Step (a) actually has requires tremendous customization options. One could see
that from the recently added filterMemRef parameter.
This patch adds a function that only does (b), in the hope that (a)
can be directly implemented by the callers. In fact, (a) is quite
simple if the caller has only one buffer to consider, or even one use.
Differential Revision: https://reviews.llvm.org/D75965
Summary: In some situations the name of the attribute is not representable as a bare-identifier, this revision adds support for those cases by formatting the name as a string instead. This has the added benefit of removing the identifier regex from the verifier.
Differential Revision: https://reviews.llvm.org/D75973
Summary:
This patch add some builtin operation for the gpu.all_reduce ops.
- for Integer only: `and`, `or`, `xor`
- for Float and Integer: `min`, `max`
This is useful for higher level dialect like OpenACC or OpenMP that can lower to the GPU dialect.
Differential Revision: https://reviews.llvm.org/D75766
Summary:
1-bit integer is tricky in different dialects sometimes. E.g., there is no
arithmetic instructions on 1-bit integer in SPIR-V, i.e., `spv.IMul %0, %1 : i1`
is not valid. Instead, `spv.LogicalAnd %0, %1 : i1` is valid. Creating the op
directly makes lowering easier because we don't need to match a complicated
pattern like `!(!lhs && !rhs)`. Also, this matches the semantic better.
Also add assertions on inputs.
Differential Revision: https://reviews.llvm.org/D75764
Summary:
This patch add some builtin operation for the gpu.all_reduce ops.
- for Integer only: `and`, `or`, `xor`
- for Float and Integer: `min`, `max`
This is useful for higher level dialect like OpenACC or OpenMP that can lower to the GPU dialect.
Differential Revision: https://reviews.llvm.org/D75766
* Adds GpuLaunchFuncToVulkanLaunchFunc conversion pass.
* Moves a serialization of the `spirv::Module` from LaunchFuncToVulkanCalls pass to newly created pass.
* Updates LaunchFuncToVulkanCalls instrumentation pass, adds `initVulkan` and `deinitVulkan` runtime calls.
* Adds `bindResource` call to bind specifc resource by the given descriptor set and descriptor binding.
* Eliminates static construction and desctruction of `VulkanRuntimeManager`.
Differential Revision: https://reviews.llvm.org/D75192
Summary:
Interfaces/ is the designated directory for these types of interfaces, and also removes the need for including them directly in IR/.
Differential Revision: https://reviews.llvm.org/D75886
The interfaces themselves aren't really analyses, they may be used by analyses though. Having them in Analysis can also create cyclic dependencies if an analysis depends on a specific dialect, that also provides one of the interfaces.
Differential Revision: https://reviews.llvm.org/D75867
This revision takes advantage of the empty AffineMap to specify the
0-D edge case. This allows removing a bunch of annoying corner cases
that ended up impacting users of Linalg.
Differential Revision: https://reviews.llvm.org/D75831
Summary:
The old interface was a temporary stopgap to allow for implementing simple LICM that took side effects of region operations into account. Now that MLIR has proper support for specifying memory effects, this interface can be deleted.
Differential Revision: https://reviews.llvm.org/D74441
Summary: This op mirrors the llvm.intr counterpart and allows lowering + type conversions in a progressive fashion.
Differential Revision: https://reviews.llvm.org/D75775
Summary:
This revision adds intrinsics for transpose, columnwise.load and columnwise.store
achieving full coverage of the llvm.matrix intrinsics.
Differential Revision: https://reviews.llvm.org/D75852
add convenience method for affine data copy generation for a loop body
Signed-off-by: Uday Bondhugula <uday@polymagelabs.com>
Differential Revision: https://reviews.llvm.org/D75822
Summary:
New classes are added to ODS to enable specifying additional information on the arguments and results of an operation. These classes, `Arg` and `Res` allow for adding a description and a set of 'decorators' along with the constraint. This enables specifying the side effects of an operation directly on the arguments and results themselves.
Example:
```
def LoadOp : Std_Op<"load"> {
let arguments = (ins Arg<AnyMemRef, "the MemRef to load from",
[MemRead]>:$memref,
Variadic<Index>:$indices);
}
```
Differential Revision: https://reviews.llvm.org/D74440
This revision introduces the infrastructure for defining side-effects and attaching them to operations. This infrastructure allows for defining different types of side effects, that don't interact with each other, but use the same internal mechanisms. At the base of this is an interface that allows operations to specify the different effect instances that are exhibited by a specific operation instance. An effect instance is comprised of the following:
* Effect: The specific effect being applied.
For memory related effects this may be reading from memory, storing to memory, etc.
* Value: A specific value, either operand/result/region argument, the effect pertains to.
* Resource: This is a global entity that represents the domain within which the effect is being applied.
MLIR serves many different abstractions, which cover many different domains. Simple effects are may have very different context, for example writing to an in-memory buffer vs a database. This revision defines uses this infrastructure to define a set of initial MemoryEffects. The are effects that generally correspond to memory of some kind; Allocate, Free, Read, Write.
This set of memory effects will be used in follow revisions to generalize various parts of the compiler, and make others more powerful(e.g. DCE).
This infrastructure was originally proposed here:
https://groups.google.com/a/tensorflow.org/g/mlir/c/v2mNl4vFCUM
Differential Revision: https://reviews.llvm.org/D74439
add_llvm_library and add_llvm_executable may need to create new targets with
appropriate dependencies. As a result, it is not sufficient in some
configurations (namely LLVM_BUILD_LLVM_DYLIB=on) to only call
add_dependencies(). Instead, the explicit TableGen dependencies must
be passed to add_llvm_library() or add_llvm_executable() using the DEPENDS
keyword.
Differential Revision: https://reviews.llvm.org/D74930
In cmake, it is redundant to have a target list under target_link_libraries()
and add_dependency(). This patch removes the redundant dependency from
add_dependency().
Differential Revision: https://reviews.llvm.org/D74929
CMake allows calling target_link_libraries() without a keyword,
but this usage is not preferred when also called with a keyword,
and has surprising behavior. This patch explicitly specifies a
keyword when using target_link_libraries().
Differential Revision: https://reviews.llvm.org/D75725
This revision adds the first intrinsic for llvm.matrix.multiply.
This uses the more general `LLVM_OneResultOp` for now since the goal is
to use the
specific Matrix builders that @fhahn has created recently.
When piped through:
```
opt -O3 -enable-matrix | llc -O3 -march=x86-64 -mcpu=skylake-avx512
```
this has been verified to generate ymm instructions.
Additional function attribute support will be needed to generate proper
zmm instructions but at least things run end to end.
Benchmarking will be provided separately with the experimental
metaprogramming
[ModelBuilder](https://github.com/google/iree/tree/master/experimental/ModelBuilder)
tool when ready.
Summary:
Paying off some technical debt in VectorOps, where I introduced a special
op for a fused accumulator into reduction to avoid some issues around
printing and parsing an optional accumulator. This CL merges the two
into one op again and does things the right way (still would be nice
to have "assemblyFormat" for optional operands though....).
Reviewers: nicolasvasilache, andydavis1, ftynse, rriddle
Reviewed By: nicolasvasilache
Subscribers: mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, liufengdb, Joonsoo, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D75699
Summary:
This revision removes all of the functionality related to successor operands on the core Operation class. This greatly simplifies a lot of handling of operands, as well as successors. For example, DialectConversion no longer needs a special "matchAndRewrite" for branching terminator operations.(Note, the existing method was also broken for operations with variadic successors!!)
This also enables terminator operations to define their own relationships with successor arguments, instead of the hardcoded "pass-through" behavior that exists today.
Differential Revision: https://reviews.llvm.org/D75318
This greatly simplifies the requirements for builders using this mechanism for managing variadic operands.
Differential Revision: https://reviews.llvm.org/D75317
The existing API for successor operands on operations is in the process of being removed. This revision simplifies a later one that completely removes the existing API.
Differential Revision: https://reviews.llvm.org/D75316
This attribute details the segment sizes for operand groups within the operation. This revision add support for automatically populating this attribute in the declarative parser.
Differential Revision: https://reviews.llvm.org/D75315
This interface contains the necessary components to provide the same builtin behavior that terminators have. This will be used in future revisions to remove many of the hardcoded constraints placed on successors and successor operands. The interface initially contains three methods:
```c++
// Return a set of values corresponding to the operands for successor 'index', or None if the operands do not correspond to materialized values.
Optional<OperandRange> getSuccessorOperands(unsigned index);
// Return true if this terminator can have it's successor operands erased.
bool canEraseSuccessorOperand();
// Erase the operand of a successor. This is only valid to call if 'canEraseSuccessorOperand' returns true.
void eraseSuccessorOperand(unsigned succIdx, unsigned opIdx);
```
Differential Revision: https://reviews.llvm.org/D75314
This allows for simplifying OpDefGen, as well providing specializing accessors for the different successor counts. This mirrors the existing traits for operands and results.
Differential Revision: https://reviews.llvm.org/D75313
The current setup of the GPU dialect is to model both the host and
device side codegen. For cases (like IREE) the host side modeling
might not directly fit its use case, but device-side codegen is still
valuable. First step in accessing just the device-side functionality
of the GPU dialect is to allow just creating a gpu.func operation from
a gpu.launch operation. In addition this change also "inlines"
operations into the gpu.func op at time of creation instead of this
being a later step.
Differential Revision: https://reviews.llvm.org/D75287
Summary:
This patch adds support for translation of the OpenMP barrier construct to LLVM
IR. The OpenMP IRBuilder is used for this translation. In this patch the code
for translation is added to the existing LLVM dialect translation to LLVM IR.
The patch includes code changes and a testcase.
Reviewers: jdoerfert, nicolasvasilache, ftynse, rriddle, mehdi_amini
Reviewed By: ftynse, rriddle, mehdi_amini
Differential Revision: https://reviews.llvm.org/D72962
output has zero rank.
While lowering to loops, no indices should be used in the load/store
operation if the buffer is zero-rank.
Differential Revision: https://reviews.llvm.org/D75391
This commit updates SPIR-V dialect to support integer signedness
by relaxing various checks for signless to just normal integers.
The hack for spv.Bitcast can now be removed.
Differential Revision: https://reviews.llvm.org/D75611
A previous commit added support for integer signedness in C++
IntegerType. This change introduces ODS definitions for
integer types and integer (element) attributes w.r.t. signedness.
This commit also updates various existing definitions' descriptions
to mention signless where suitable to make it more clear.
Positive and non-negative integer attributes are removed to avoid
the explosion of subclasses. Instead, one should use more atmoic
constraints together with Confined to model that. For example,
`Confined<..., [IntPositive]>`.
Differential Revision: https://reviews.llvm.org/D75610
Recently introduced support for converting sequential reduction loops to
CFG of basic blocks in the Standard dialect makes it possible to perform
a staged conversion of parallel reduction loops into a similar CFG by
using sequential loops as an intermediate step. This is already the case
for parallel loops without reduction, so extend the pattern to support
an additional use case.
Differential Revision: https://reviews.llvm.org/D75599
Summary:
This adds an rsqrt op to the standard dialect, and lowers
it as 1 / sqrt to the LLVM dialect.
Differential Revision: https://reviews.llvm.org/D75353
Summary:
Previously, we would, for an empty file, print the somewhat confusing
Assertion `tok == curTok [...]' failed.
With this change, we now print
Parse error [...]: expected 'def' [...]
This only affects the parser from chapters 1-6, since the more advanced
chapter 7 parser is actually able to generate an empty module from an
empty file. Nonetheless, this commit also adds the additional check to
the chapter 7 parser, for consistency.
Differential Revision: https://reviews.llvm.org/D75534
Summary: This allows for attaching the attribute to CmpF as a proper argument, and thus enables the removal of a bunch of c++ code.
Differential Revision: https://reviews.llvm.org/D75539
For ODS generated operations enable querying whether there is a derived
attribute with a given name.
Rollforward of commit 5aa57c2 without using llvm::is_contained.
Summary:
Introduce support for converting loop.for operations with loop-carried values
to a CFG in the standard dialect. This is achieved by passing loop-carried
values as block arguments to the loop condition block. This block dominates
both the loop body and the block immediately following the loop, so the
arguments of this block are remain visible there.
Differential Revision: https://reviews.llvm.org/D75513
Some attribute kinds are not supported as "value" attributes of
`llvm.mlir.constant` when translating to LLVM IR. We were correctly reporting
an error, but continuing the translation using an "undef" value instead,
leading to a surprising mix of error messages and output IR. Abort the
translation after the error is reported.
Differential Revision: https://reviews.llvm.org/D75450
This reverts commit 5aa57c2812.
The source code generated due to this ods change does not compile,
as it passes to few arguments to llvm::is_contained.
Summary: For example, DenseElementsAttr currently does not properly round-trip unsigned integer values.
Differential Revision: https://reviews.llvm.org/D75374
Summary: Added brackets to fix the loop trip count computation.
The brackets ensure the bounds are subtracted before we divide
the result by the step of the loop.
Differential Revision: https://reviews.llvm.org/D75449
add_llvm_library and add_llvm_executable may need to create new targets with
appropriate dependencies. As a result, it is not sufficient in some
configurations (namely LLVM_BUILD_LLVM_DYLIB=on) to only call
add_dependencies(). Instead, the explicit TableGen dependencies must
be passed to add_llvm_library() or add_llvm_executable() using the DEPENDS
keyword.
Differential Revision: https://reviews.llvm.org/D74930
In cmake, it is redundant to have a target list under target_link_libraries()
and add_dependency(). This patch removes the redundant dependency from
add_dependency().
Differential Revision: https://reviews.llvm.org/D74929
When compiling libLLVM.so, add_llvm_library() manipulates the link libraries
being used. This means that when using add_llvm_library(), we need to pass
the list of libraries to be linked (using the LINK_LIBS keyword) instead of
using the standard target_link_libraries call. This is preparation for
properly dealing with creating libMLIR.so as well.
Differential Revision: https://reviews.llvm.org/D74864
add_llvm_library and add_llvm_executable may need to create new targets with
appropriate dependencies. As a result, it is not sufficient in some
configurations (namely LLVM_BUILD_LLVM_DYLIB=on) to only call
add_dependencies(). Instead, the explicit TableGen dependencies must
be passed to add_llvm_library() or add_llvm_executable() using the DEPENDS
keyword.
Differential Revision: https://reviews.llvm.org/D74930
In cmake, it is redundant to have a target list under target_link_libraries()
and add_dependency(). This patch removes the redundant dependency from
add_dependency().
Differential Revision: https://reviews.llvm.org/D74929
When compiling libLLVM.so, add_llvm_library() manipulates the link libraries
being used. This means that when using add_llvm_library(), we need to pass
the list of libraries to be linked (using the LINK_LIBS keyword) instead of
using the standard target_link_libraries call. This is preparation for
properly dealing with creating libMLIR.so as well.
Differential Revision: https://reviews.llvm.org/D74864
This matches loops with a affine.min upper bound, limiting the trip
count to a constant, and rewrites them into two loops, one with constant
upper bound and one with variable upper bound. The assumption is that
the constant upper bound loop will be unrolled and vectorized, which is
preferable if this is the hot path.
Differential Revision: https://reviews.llvm.org/D75240
Summary:
This revision split out a new CRunnerUtils library that supports
MLIR execution on targets without a C++ runtime.
Differential Revision: https://reviews.llvm.org/D75257
Display the list of dialects known to mlir-opt. This is useful
for ensuring that linkage has happened correctly, for instance.
Differential Revision: https://reviews.llvm.org/D74865
Summary:
AffineApplyNormalizer provides common logic for folding affine maps that appear
in affine.apply into other affine operations that use the result of said
affine.apply. In the process, affine maps of both operations are composed.
During the composition `A.compose(B)` the symbols from the map A are placed
before those of the map B in a single concatenated symbol list. However,
AffineApplyNormalizer was ordering the operands of the operation being
normalized by iteratively appending the symbols into a single list accoridng to
the operand order, regardless of whether these operands are symbols of the
current operation or of the map that is being folded into it. This could lead
to wrong order of symbols and, when the symbols were bound to constant values,
to visibly incorrect folding of constants into affine maps as reported in
PR45031. Make sure symbols operands to the current operation are always placed
before symbols coming from the folded maps.
Update the test that was exercising the incorrect folder behavior. For some
reason, the order of symbol operands was swapped in the test input compared to
the previous operations, making it easy to assume the correct maps were
produced whereas they were swapping the symbols back due to the problem
described above.
Closes https://bugs.llvm.org/show_bug.cgi?id=45031
Differential Revision: https://reviews.llvm.org/D75247
This commit handles folding spv.LogicalAnd/spv.LogicalOr when
one of the operands is constant true/false.
Differential Revision: https://reviews.llvm.org/D75195
Summary: bfloat16 is stored internally as a double, so we can't direct use Type::getIntOrFloatBitWidth.
Differential Revision: https://reviews.llvm.org/D75133
Summary:
The original patch had TODOs to add support for step computations,
which this commit addresses. The computations are expressed using
affine expressions so that the affine canonicalizers can simplify
the full bound and index computations.
Also cleans up the code a little and exposes the pass in the
header file.
Differential Revision: https://reviews.llvm.org/D75052
Affine dialect already has a map+operand simplification infrastructure in
place. Plug the recently added affine.min/max operations into this
infrastructure and add a simple test. More complex behavior of the simplifier
is already tested by other ops.
Addresses https://bugs.llvm.org/show_bug.cgi?id=45008.
Differential Revision: https://reviews.llvm.org/D75058
Originally, intrinsics generator for the LLVM dialect has been producing
customized code fragments for the translation of MLIR operations to LLVM IR
intrinsics. LLVM dialect ODS now provides a generalized version of the
translation code, parameterizable with the properties of the operation.
Generate ODS that uses this version of the translation code instead of
generating a new version of it for each intrinsic.
Differential Revision: https://reviews.llvm.org/D74893
Summary:
The mapper assigns annotations to loop.parallel operations that
are compatible with the loop to gpu mapping pass. The outermost
loop uses the grid dimensions, followed by block dimensions. All
remaining loops are mapped to sequential loops.
Differential Revision: https://reviews.llvm.org/D74963
Summary:
The RFC for this op is here: https://llvm.discourse.group/t/rfc-add-std-atomic-rmw-op/489
The std.atmomic_rmw op provides a way to support read-modify-write
sequences with data race freedom. It is intended to be used in the lowering
of an upcoming affine.atomic_rmw op which can be used for reductions.
A lowering to LLVM is provided with 2 paths:
- Simple patterns: llvm.atomicrmw
- Everything else: llvm.cmpxchg
Differential Revision: https://reviews.llvm.org/D74401
Previously C++ test passes for SPIR-V were put under
test/Dialect/SPIRV. Move them to test/lib/Dialect/SPIRV
to create a better structure.
Also fixed one of the test pass to use new
PassRegistration mechanism.
Differential Revision: https://reviews.llvm.org/D75066
This exploits the fact that the iterations of parallel loops are
independent so tiling becomes just an index transformation. This pass
only tiles the innermost loop of a loop nest.
The ultimate goal is to allow vectorization of the tiled loops, but I
don't think we're there yet with the current rewriting, as the tiled
loops don't have a constant trip count.
Differential Revision: https://reviews.llvm.org/D74954
Summary:
This details the C++ format as well as the new declarative format. This has been one of the major missing pieces from the toy tutorial.
Differential Revision: https://reviews.llvm.org/D74938
This revision add support for formatting successor variables in a similar way to operands, attributes, etc.
Differential Revision: https://reviews.llvm.org/D74789
This revision add support in ODS for specifying the successors of an operation. Successors are specified via the `successors` list:
```
let successors = (successor AnySuccessor:$target, AnySuccessor:$otherTarget);
```
Differential Revision: https://reviews.llvm.org/D74783
This matches the '(print|parse)OptionalAttrDictWithKeyword' functionality provided by the assembly parser/printer.
Differential Revision: https://reviews.llvm.org/D74682
When operations have optional attributes, or optional operands(i.e. empty variadic operands), the assembly format often has an optional section to represent these arguments. This revision adds basic support for defining an "optional group" in the assembly format to support this. An optional group is defined by wrapping a set of elements in `()` followed by `?` and requires the following:
* The first element of the group must be either a literal or an operand argument.
- This is because the first element must be optionally parsable.
* There must be exactly one argument variable within the group that is marked as the anchor of the group. The anchor is the element whose presence controls whether the group should be printed/parsed. An element is marked as the anchor by adding a trailing `^`.
* The group must only contain literals, variables, and type directives.
- Any attribute variables may be used, but only optional attributes can be marked as the anchor.
- Only variadic, i.e. optional, operand arguments can be used.
- The elements of a type directive must be defined within the same optional group.
An example of this can be seen with the assembly format for ReturnOp, which has a variadic number of operands.
```
def ReturnOp : ... {
let arguments = (ins Variadic<AnyType>:$operands);
// We only print the operands+types if there are a non-zero number
// of operands.
let assemblyFormat = "attr-dict ($operands^ `:` type($operands))?";
}
```
Differential Revision: https://reviews.llvm.org/D74681
This allows for injecting type constraints that are not direct 1-1 mappings, for example when one type is equal to the element type of another. This allows for moving over several more parsers to the declarative form.
Differential Revision: https://reviews.llvm.org/D74648
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 patch implements the RFCs proposed here:
https://llvm.discourse.group/t/rfc-modify-ifop-in-loop-dialect-to-yield-values/463https://llvm.discourse.group/t/rfc-adding-operands-and-results-to-loop-for/459/19.
It introduces the following changes:
- All Loop Ops region, except for ReduceOp, terminate with a YieldOp.
- YieldOp can have variadice operands that is used to return values out of IfOp and ForOp regions.
- Change IfOp and ForOp syntax and representation to define values.
- Add unit-tests and update .td documentation.
- YieldOp is a terminator to loop.for/if/parallel
- YieldOp custom parser and printer
Lowering is not supported at the moment, and will be in a follow-up PR.
Thanks.
Reviewed By: bondhugula, nicolasvasilache, rriddle
Differential Revision: https://reviews.llvm.org/D74174
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
Summary: DenseElementsAttr is used to store tensor data, which in some cases can become extremely large(100s of mb). In these cases it is much more efficient to format the data as a string of hex values instead.
Differential Revision: https://reviews.llvm.org/D74922
Summary:
This implements the last step for lowering vector.contract progressively
to LLVM IR (except for masks). Multi-dimensional reductions that remain
after expanding all parallel dimensions are lowered into into simpler
vector.contract operations until a trivial 1-dim reduction remains.
Reviewers: nicolasvasilache, andydavis1
Reviewed By: andydavis1
Subscribers: mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, liufengdb, Joonsoo, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D74880
Summary:
Lowers all free/batch dimensions in a vector.contract progressively
into simpler vector.contract operations until a direct vector.reduction
operation is reached. Then lowers 1-D reductions into vector.reduce.
Still TBD:
multi-dimensional contractions that remain after removing all the parallel dims
Reviewers: nicolasvasilache, andydavis1, rriddle
Reviewed By: andydavis1
Subscribers: mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, liufengdb, Joonsoo, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D74797
It replaces DenseMap output with a SmallVector and it
removes empty loop levels from the output.
Reviewed By: andydavis1, mehdi_amini
Differential Revision: https://reviews.llvm.org/D74658
Summary:
This trait takes three arguments: lhs, rhs, transformer. It verifies that the type of 'rhs' matches the type of 'lhs' when the given 'transformer' is applied to 'lhs'. This allows for adding constraints like: "the type of 'a' must match the element type of 'b'". A followup revision will add support in the declarative parser for using these equality constraints to port more c++ parsers to the declarative form.
Differential Revision: https://reviews.llvm.org/D74647
In some dialects, attributes may have default values that may be
determined only after shape inference. For example, attributes that
are dependent on the rank of the input cannot be assigned a default
value until the rank of the tensor is inferred.
While we can set attributes without explicit setters, referring to
the attributes via accessors instead of having to use the string
interface is better for compile time verification.
The proposed patch add one method per operation attribute that let us
set its value. The code is a very small modification of the existing
getter methods.
Differential Revision: https://reviews.llvm.org/D74143
Add an initial version of mlir-vulkan-runner execution driver.
A command line utility that executes a MLIR file on the Vulkan by
translating MLIR GPU module to SPIR-V and host part to LLVM IR before
JIT-compiling and executing the latter.
Differential Revision: https://reviews.llvm.org/D72696
Summary:
the .row.col variant turns out to be the popular one, contrary to what I
thought as .row.row. Since .row.col is so prevailing (as I inspect
cuDNN's behavior), I'm going to remove the .row.row support here, which
makes the patch a little bit easier.
Reviewers: ftynse
Subscribers: jholewinski, bixia, sanjoy.google, mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, liufengdb, Joonsoo, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D74655
Summary:
This revision refactors the TypeConverter class to not use inheritance to add type conversions. It instead moves to a registration based system, where conversion callbacks are added to the converter with `addConversion`. This method takes a conversion callback, which must be convertible to any of the following forms(where `T` is a class derived from `Type`:
* Optional<Type> (T type)
- This form represents a 1-1 type conversion. It should return nullptr
or `llvm::None` to signify failure. If `llvm::None` is returned, the
converter is allowed to try another conversion function to perform
the conversion.
* Optional<LogicalResult>(T type, SmallVectorImpl<Type> &results)
- This form represents a 1-N type conversion. It should return
`failure` or `llvm::None` to signify a failed conversion. If the new
set of types is empty, the type is removed and any usages of the
existing value are expected to be removed during conversion. If
`llvm::None` is returned, the converter is allowed to try another
conversion function to perform the conversion.
When attempting to convert a type, the TypeConverter walks each of the registered converters starting with the one registered most recently.
Differential Revision: https://reviews.llvm.org/D74584
Fixing a bug where using a zero-rank shaped type operand to
linalg.generic ops hit an unrelated assert. This also meant that
lowering the operation to loops was not supported. Adding roundtrip
tests and lowering to loops test for zero-rank shaped type operand
with fixes to make the test pass.
Differential Revision: https://reviews.llvm.org/D74638
Summary:
Linalg's promotion pass was only supporting f32 buffers due to how the
zero value was build for the `fill` operation.
Moreover, `promoteSubViewOperands` was returning a vector with one entry
per float subview while omitting integer subviews. For a program
with only integer subviews the return vector would be of size 0.
However, `promoteSubViewsOperands` would try to access a non zero
number of entries of this vector, resulting in a sefgault.
Reviewers: nicolasvasilache, ftynse
Reviewed By: ftynse
Subscribers: mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, liufengdb, Joonsoo, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D74532
This patch extends affine data copy optimization utility with an
optional memref filter argument. When the memref filter is used, data
copy optimization will only generate copies for such a memref.
Note: this patch is just porting the memref filter feature from Uday's
'hop' branch: https://github.com/bondhugula/llvm-project/tree/hop.
Reviewed By: bondhugula
Differential Revision: https://reviews.llvm.org/D74342
The commit switching the calling convention for memrefs (5a1778057)
inadvertently introduced a bug in the function argument attribute conversion:
due to incorrect indexing of function arguments it was not assigning the
attributes to the arguments beyond those generated from the first original
argument. This was not caught in the commit since the test suite does have a
test for converting multi-argument functions with argument attributes. Fix the
bug and add relevant tests.
Summary: This revision adds support to the declarative parser for formatting enum attributes in the symbolized form. It uses this new functionality to port several of the SPIRV parsers over to the declarative form.
Differential Revision: https://reviews.llvm.org/D74525
Summary:
This sets the basic framework for lowering vector.contract progressively
into simpler vector.contract operations until a direct vector.reduction
operation is reached. More details will be filled out progressively as well.
Reviewers: nicolasvasilache
Reviewed By: nicolasvasilache
Subscribers: mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, liufengdb, Joonsoo, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D74520
Implement a pass to convert gpu.launch_func op into a sequence of
Vulkan runtime calls. The Vulkan runtime API surface is huge so currently we
don't expose separate external functions in IR for each of them, instead we
expose a few external functions to wrapper libraries which manages
Vulkan runtime.
Differential Revision: https://reviews.llvm.org/D74549
Summary:
To unblock other work, this implements basic lowering based on mapping
attributes that have to be provided on all loop.parallel. The lowering
does not yet support reduce.
Differential Revision: https://reviews.llvm.org/D73893
In code generators, one can automate the translation of typed ArrayAttrs
if element attribute translators are already implemented. However, the
type of the element attribute is lost at the construction of
TypedArrayAttrBase. With this change one can inspect the element type
and generate the translation logic automatically, which will reduce the
code repetition.
Differential Revision: https://reviews.llvm.org/D73579
Summary:
As discussed in https://llvm.discourse.group/t/rfc-add-affine-parallel/350, this is the first in a series of patches to bring in support for the `affine.parallel` operation.
This first patch adds the IR representation along with custom printer/parser implementations.
Reviewers: bondhugula, herhut, mehdi_amini, nicolasvasilache, rriddle, earhart, jbruestle
Reviewed By: bondhugula, nicolasvasilache, rriddle, earhart, jbruestle
Subscribers: jpienaar, burmako, shauheen, antiagainst, arpith-jacob, mgester, lucyrfox, aartbik, liufengdb, Joonsoo, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D74288
This patch adapts the method MemRefDescriptor::fromStaticShape to
support static non-zero offsets. The updated method uses the
getStridesAndOffset method to extract strides and offset. The patch also
adapts the test cases since sizes and strides are now set in forward
instead of reverse order.
Differential Revision: https://reviews.llvm.org/D74474
Summary:
This revision allows model builder to create a linalg_matmul whose body
is a vector.contract. This shows the abstractions compose nicely.
Differential Revision: https://reviews.llvm.org/D74457
Summary: This was a missed case when ValueRange was originally added, and allows for constructing a ValueRange from the arguments of a block.
Differential Revision: https://reviews.llvm.org/D74363
A memref_cast casting to a memref with a non identity map can't be
lowered to llvm. Take the following case:
```
func @invalid_memref_cast(%arg0: memref<?x?xf64>) {
%c1 = constant 1 : index
%c0 = constant 0 : index
%5 = memref_cast %arg0 : memref<?x?xf64> to memref<?x?xf64, #map1>
%25 = std.subview %5[%c0, %c0][%c1, %c1][] : memref<?x?xf64, #map1> to memref<?x?xf64, #map1>
return
}
```
When lowering the subview mlir was assuming `%5` to have an llvm type
(which is not the case as mlir failed to lower the memref_cast).
Differential Revision: https://reviews.llvm.org/D74466
Thus far we have been using builtin func op to model SPIR-V functions.
It was because builtin func op used to have special treatment in
various parts of the core codebase (e.g., pass pipelines, etc.) and
it's easy to bootstrap the development of the SPIR-V dialect. But
nowadays with general op concepts and region support we don't have
such limitations and it's time to tighten the SPIR-V dialect for
completeness.
This commits introduces a spv.func op to properly model SPIR-V
functions. Compared to builtin func op, it can provide the following
benefits:
* We can control the full op so we can integrate SPIR-V information
bits (e.g., function control) in a more integrated way and define
our own assembly form and enforcing better verification.
* We can have a better dialect and library boundary. At the current
moment only functions are modelled with an external op. With this
change, all ops modelling SPIR-V concpets will be spv.* ops and
registered to the SPIR-V dialect.
* We don't need to special-case func op anymore when creating
ConversionTarget declaring SPIR-V dialect as legal. This is quite
important given we'll see more and more conversions in the future.
In the process, bumps a few FuncOp methods to the FunctionLike trait.
Differential Revision: https://reviews.llvm.org/D74226
In the previous state, we were relying on forcing the linker to include
all libraries in the final binary and the global initializer to self-register
every piece of the system. This change help moving away from this model, and
allow users to compose pieces more freely. The current change is only "fixing"
the dialect registration and avoiding relying on "whole link" for the passes.
The translation is still relying on the global registry, and some refactoring
is needed to make this all more convenient.
Differential Revision: https://reviews.llvm.org/D74461
Summary:
Adds affine loop fusion transformation function to LoopFusionUtils.
Updates TestLoopFusion utility to run loop fusion transformation until a fixed point is reached.
Adds unit tests to test the transformation.
Includes ASAN bug fix for D73190.
Reviewers: bondhugula, dcaballe
Reviewed By: bondhugula, dcaballe
Subscribers: mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, aartbik, liufengdb, Joonsoo, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D74330
Follow-up on D72802. Turn -convert-std-to-llvm-use-alloca and
-convert-std-to-llvm-bare-ptr-memref-call-conv into pass flags
of LLVMLoweringPass.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D73912
Defines a tablegen class RankedIntElementsAttr. This is an integer
version of RankedFloatElementsAttr.
Differential Revision: https://reviews.llvm.org/D73764
We have spv.entry_point_abi for specifying the local workgroup size.
It should be decorated onto input gpu.func ops to drive the SPIR-V
CodeGen to generate the proper SPIR-V module execution mode. Compared
to using command-line options for specifying the configuration, using
attributes also has the benefits that 1) we are now able to use
different local workgroup for different entry points and 2) the
tests contains the configuration directly.
Differential Revision: https://reviews.llvm.org/D74012
Summary:
After D72555 has been landed, `linalg.indexed_generic` also accepts ranked
tensor as input and output. Add a test for it.
Differential Revision: https://reviews.llvm.org/D74267
Summary:
This revision adds EDSC support for VectorOps to enable the creation of a `vector_matmul` declaratively. The `vector_matmul` is a simple configuration
of the `vector.contract` op that follows the StructuredOps abstraction.
Differential Revision: https://reviews.llvm.org/D74284
This CL refactors EDSCs to layer them better and break unnecessary
dependencies. After this refactoring, the top-level EDSC target only
depends on IR but not on Dialects anymore and each dialect has its
own EDSC directory.
This simplifies the layering and breaks cyclic dependencies.
In particular, the declarative builder + folder are made explicit and
are now confined to Linalg.
As the refactoring occurred, certain classes and abstractions that were not
paying for themselves have been removed.
Differential Revision: https://reviews.llvm.org/D74302
The current standard to llvm conversion pass lowers subview ops only if
dynamic offsets are provided. This commit extends the lowering with a
code path that uses the constant offset of the target memref for the
subview op lowering (see Example 3 of the subview op definition for an
example) if no dynamic offsets are provided.
Differential Revision: https://reviews.llvm.org/D74280
The existing (default) calling convention for memrefs in standard-to-LLVM
conversion was motivated by interfacing with LLVM IR produced from C sources.
In particular, it passes a pointer to the memref descriptor structure when
calling the function. Therefore, the descriptor is allocated on stack before
the call. This convention leads to several problems. PR44644 indicates a
problem with stack exhaustion when calling functions with memref-typed
arguments in a loop. Allocating outside of the loop may lead to concurrent
access problems in case the loop is parallel. When targeting GPUs, the contents
of the stack-allocated memory for the descriptor (passed by pointer) needs to
be explicitly copied to the device. Using an aggregate type makes it impossible
to attach pointer-specific argument attributes pertaining to alignment and
aliasing in the LLVM dialect.
Change the default calling convention for memrefs in standard-to-LLVM
conversion to transform a memref into a list of arguments, each of primitive
type, that are comprised in the memref descriptor. This avoids stack allocation
for ranked memrefs (and thus stack exhaustion and potential concurrent access
problems) and simplifies the device function invocation on GPUs.
Provide an option in the standard-to-LLVM conversion to generate auxiliary
wrapper function with the same interface as the previous calling convention,
compatible with LLVM IR porduced from C sources. These auxiliary functions
pack the individual values into a descriptor structure or unpack it. They also
handle descriptor stack allocation if necessary, serving as an allocation
scope: the memory reserved by `alloca` will be freed on exiting the auxiliary
function.
The effect of this change on MLIR-generated only LLVM IR is minimal. When
interfacing MLIR-generated LLVM IR with C-generated LLVM IR, the integration
only needs to require auxiliary functions and change the function name to call
the wrapper function instead of the original function.
This also opens the door to forwarding aliasing and alignment information from
memrefs to LLVM IR pointers in the standrd-to-LLVM conversion.
The existing lowering of gpu.block_dim added a global variable with
the WorkGroupSize decoration. This raises an error within
Vulkan/SPIR-V validation since Vulkan requires this to have a constant
initializer. This is not yet supported in SPIR-V dialect. Changing the
lowering to return the workgroup size as a constant value instead,
obtained from spv.entry_point_abi attribute gets around the issue for
now. The validation goes through since the workgroup size is specified
using spv.execution_mode operation.
Summary:
This revision adds a utility to generate debug locations from the IR during compilation, by snapshotting to a output stream and using the locations that operations were dumped in that stream. The new locations may either;
* Replace the original location of the operation.
old:
loc("original_source.cpp":1:1)
new:
loc("snapshot_source.mlir":10:10)
* Fuse with the original locations as NamedLocs with a specific tag.
old:
loc("original_source.cpp":1:1)
new:
loc(fused["original_source.cpp":1:1, "snapshot"("snapshot_source.mlir":10:10)])
This feature may be used by a debugger to display the code at various different levels of the IR. It would also be able to show the different levels of IR attached to a specific source line in the original source file.
This feature may also be used to generate locations for operations generated during compilation, that don't necessarily have a user source location to attach to.
This requires changes in the printer to track the locations of operations emitted in the stream. Moving forward we need to properly(and efficiently) track the number of newlines emitted to the stream during printing.
Differential Revision: https://reviews.llvm.org/D74019
Summary:
The `vector.fma` operation is portable enough across targets that we do not want
to keep it wrapped under `vector.outerproduct` and `llvm.intrin.fmuladd`.
This revision lifts the op into the vector dialect and implements the lowering to LLVM by using two patterns:
1. a pattern that lowers from n-D to (n-1)-D by unrolling when n > 2
2. a pattern that converts from 1-D to the proper LLVM representation
Reviewers: ftynse, stellaraccident, aartbik, dcaballe, jsetoain, tetuante
Reviewed By: aartbik
Subscribers: fhahn, dcaballe, merge_guards_bot, mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, arpith-jacob, mgester, lucyrfox, aartbik, liufengdb, Joonsoo, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D74075
Summary:
This revision exposes the portable `llvm.fma` intrinsic in LLVMOps and uses it
in lieu of `llvm.fmuladd` when lowering the `vector.outerproduct` op to LLVM.
This guarantees proper `fma` instructions will be emitted if the target ISA
supports it.
`llvm.fmuladd` does not have this guarantee in its semantics, despite evidence
that the proper x86 instructions are emitted.
For more details, see https://llvm.org/docs/LangRef.html#llvm-fmuladd-intrinsic.
Reviewers: ftynse, aartbik, dcaballe, fhahn
Reviewed By: aartbik
Subscribers: mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, arpith-jacob, mgester, lucyrfox, liufengdb, Joonsoo, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D74219
The initial implementation of the fusion operation exposes a method to
fuse a consumer with its producer, when
- both the producer and consumer operate on tensors
- the producer has only a single result value
- the producer has only "parallel" iterator types
A new interface method hasTensorSemantics is added to verify that an
operation has all operands and results of type RankedTensorType.
Differential Revision: https://reviews.llvm.org/D74172
Summary: In some edge cases the default APFloat printer will generate something that we can't parse back in. In these cases, fallback to using hex instead.
Differential Revision: https://reviews.llvm.org/D74181
This reverts commit 64871f778d.
ASAN indicates a use-after-free in in mlir::canFuseLoops(mlir::AffineForOp, mlir::AffineForOp, unsigned int, mlir::ComputationSliceState*) lib/Transforms/Utils/LoopFusionUtils.cpp:202:41
Summary:
This revision adds basic support for emitting line table information when exporting to LLVMIR. We don't yet have a story for supporting all of the LLVM debug metadata, so this revision stubs some features(like subprograms) to enable emitting line tables.
Differential Revision: https://reviews.llvm.org/D73934
Summary:
Previously, vector.contract did not allow an empty set of
free or batch dimensions (K = 0) which defines a basic
reduction into a scalar (like a dot product). This CL
relaxes that restriction. Also adds constraints on
element type of operands and results. With tests.
Reviewers: nicolasvasilache, andydavis1, rriddle
Reviewed By: andydavis1
Subscribers: merge_guards_bot, mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, liufengdb, Joonsoo, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D74014
Summary:
[mlir][VectorOps] Support vector transfer_read/write unrolling for memrefs with vector element type. When unrolling vector transfer read/write on memrefs with vector element type, the indices used to index the memref argument must be updated to reflect the unrolled operation. However, in the case of memrefs with vector element type, we need to be careful to only update the relevant memref indices.
For example, a vector transfer read with the following source/result types, memref<6x2x1xvector<2x4xf32>>, vector<2x1x2x4xf32>, should only update memref indices 1 and 2 during unrolling.
Reviewers: nicolasvasilache, aartbik
Reviewed By: nicolasvasilache, aartbik
Subscribers: lebedev.ri, Joonsoo, merge_guards_bot, mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, arpith-jacob, mgester, lucyrfox, liufengdb, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D72965
Summary:
Adds affine loop fusion transformation function to LoopFusionUtils.
Updates TestLoopFusion utility to run loop fusion transformation until a fixed point is reached.
Adds unit tests to test the transformation.
Reviewers: bondhugula, dcaballe, nicolasvasilache
Reviewed By: bondhugula, dcaballe
Subscribers: Joonsoo, merge_guards_bot, mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, arpith-jacob, mgester, lucyrfox, aartbik, liufengdb, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D73190
Frederik Gossen