We hit an llvm_unreachable related to unranked memrefs for call ops
with scalar types. Removing the llvm_unreachable since the conversion
should gracefully bail out in the presence of unranked memrefs. Adding
tests to verify that.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D88709
This patch adds support for the 'return' and 'call' ops to the bare-ptr
calling convention. These changes also align the bare-ptr calling
convention code with the latest changes in the default calling convention
and reduce the amount of customization code needed.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D87724
- Use TypeRange instead of ArrayRef<Type> where possible.
- Change some of the custom builders to also use TypeRange
Differential Revision: https://reviews.llvm.org/D87944
When packing function results into a structure during the standard-to-llvm
dialect conversion, do not assume the conversion was successful and propagate
nullptr as error state.
Fixes PR45184.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D87605
Type converter may fail and return nullptr on unconvertible types. The function
conversion did not include a check and was attempting to use a nullptr type to
construct an LLVM function, leading to a crash. Add a check and return early.
The rest of the call stack propagates errors properly.
Fixes PR47403.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D87075
Vector to SCF conversion still had issues due to the interaction with the natural alignment derived by the LLVM data layout. One traditional workaround is to allocate aligned. However, this does not always work for vector sizes that are non-powers of 2.
This revision implements a more portable mechanism where the intermediate allocation is always a memref of elemental vector type. AllocOp is extended to use the natural LLVM DataLayout alignment for non-scalar types, when the alignment is not specified in the first place.
An integration test is added that exercises the transfer to scf.for + scalar lowering with a 5x5 transposition.
Differential Revision: https://reviews.llvm.org/D87150
Unsigned and Signless attributes use uintN_t and signed attributes use intN_t, where N is the fixed width. The 1-bit variants use bool.
Differential Revision: https://reviews.llvm.org/D86739
Add the unsigned complements to the existing FPToSI and SIToFP operations in the
standard dialect, with one-to-one lowerings to the corresponding LLVM operations.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D85557
This changes the behavior of constructing MLIRContext to no longer load globally
registered dialects on construction. Instead Dialects are only loaded explicitly
on demand:
- the Parser is lazily loading Dialects in the context as it encounters them
during parsing. This is the only purpose for registering dialects and not load
them in the context.
- Passes are expected to declare the dialects they will create entity from
(Operations, Attributes, or Types), and the PassManager is loading Dialects into
the Context when starting a pipeline.
This changes simplifies the configuration of the registration: a compiler only
need to load the dialect for the IR it will emit, and the optimizer is
self-contained and load the required Dialects. For example in the Toy tutorial,
the compiler only needs to load the Toy dialect in the Context, all the others
(linalg, affine, std, LLVM, ...) are automatically loaded depending on the
optimization pipeline enabled.
To adjust to this change, stop using the existing dialect registration: the
global registry will be removed soon.
1) For passes, you need to override the method:
virtual void getDependentDialects(DialectRegistry ®istry) const {}
and registery on the provided registry any dialect that this pass can produce.
Passes defined in TableGen can provide this list in the dependentDialects list
field.
2) For dialects, on construction you can register dependent dialects using the
provided MLIRContext: `context.getOrLoadDialect<DialectName>()`
This is useful if a dialect may canonicalize or have interfaces involving
another dialect.
3) For loading IR, dialect that can be in the input file must be explicitly
registered with the context. `MlirOptMain()` is taking an explicit registry for
this purpose. See how the standalone-opt.cpp example is setup:
mlir::DialectRegistry registry;
registry.insert<mlir::standalone::StandaloneDialect>();
registry.insert<mlir::StandardOpsDialect>();
Only operations from these two dialects can be in the input file. To include all
of the dialects in MLIR Core, you can populate the registry this way:
mlir::registerAllDialects(registry);
4) For `mlir-translate` callback, as well as frontend, Dialects can be loaded in
the context before emitting the IR: context.getOrLoadDialect<ToyDialect>()
Differential Revision: https://reviews.llvm.org/D85622
This changes the behavior of constructing MLIRContext to no longer load globally
registered dialects on construction. Instead Dialects are only loaded explicitly
on demand:
- the Parser is lazily loading Dialects in the context as it encounters them
during parsing. This is the only purpose for registering dialects and not load
them in the context.
- Passes are expected to declare the dialects they will create entity from
(Operations, Attributes, or Types), and the PassManager is loading Dialects into
the Context when starting a pipeline.
This changes simplifies the configuration of the registration: a compiler only
need to load the dialect for the IR it will emit, and the optimizer is
self-contained and load the required Dialects. For example in the Toy tutorial,
the compiler only needs to load the Toy dialect in the Context, all the others
(linalg, affine, std, LLVM, ...) are automatically loaded depending on the
optimization pipeline enabled.
To adjust to this change, stop using the existing dialect registration: the
global registry will be removed soon.
1) For passes, you need to override the method:
virtual void getDependentDialects(DialectRegistry ®istry) const {}
and registery on the provided registry any dialect that this pass can produce.
Passes defined in TableGen can provide this list in the dependentDialects list
field.
2) For dialects, on construction you can register dependent dialects using the
provided MLIRContext: `context.getOrLoadDialect<DialectName>()`
This is useful if a dialect may canonicalize or have interfaces involving
another dialect.
3) For loading IR, dialect that can be in the input file must be explicitly
registered with the context. `MlirOptMain()` is taking an explicit registry for
this purpose. See how the standalone-opt.cpp example is setup:
mlir::DialectRegistry registry;
registry.insert<mlir::standalone::StandaloneDialect>();
registry.insert<mlir::StandardOpsDialect>();
Only operations from these two dialects can be in the input file. To include all
of the dialects in MLIR Core, you can populate the registry this way:
mlir::registerAllDialects(registry);
4) For `mlir-translate` callback, as well as frontend, Dialects can be loaded in
the context before emitting the IR: context.getOrLoadDialect<ToyDialect>()
Differential Revision: https://reviews.llvm.org/D85622
This changes the behavior of constructing MLIRContext to no longer load globally
registered dialects on construction. Instead Dialects are only loaded explicitly
on demand:
- the Parser is lazily loading Dialects in the context as it encounters them
during parsing. This is the only purpose for registering dialects and not load
them in the context.
- Passes are expected to declare the dialects they will create entity from
(Operations, Attributes, or Types), and the PassManager is loading Dialects into
the Context when starting a pipeline.
This changes simplifies the configuration of the registration: a compiler only
need to load the dialect for the IR it will emit, and the optimizer is
self-contained and load the required Dialects. For example in the Toy tutorial,
the compiler only needs to load the Toy dialect in the Context, all the others
(linalg, affine, std, LLVM, ...) are automatically loaded depending on the
optimization pipeline enabled.
To adjust to this change, stop using the existing dialect registration: the
global registry will be removed soon.
1) For passes, you need to override the method:
virtual void getDependentDialects(DialectRegistry ®istry) const {}
and registery on the provided registry any dialect that this pass can produce.
Passes defined in TableGen can provide this list in the dependentDialects list
field.
2) For dialects, on construction you can register dependent dialects using the
provided MLIRContext: `context.getOrLoadDialect<DialectName>()`
This is useful if a dialect may canonicalize or have interfaces involving
another dialect.
3) For loading IR, dialect that can be in the input file must be explicitly
registered with the context. `MlirOptMain()` is taking an explicit registry for
this purpose. See how the standalone-opt.cpp example is setup:
mlir::DialectRegistry registry;
mlir::registerDialect<mlir::standalone::StandaloneDialect>();
mlir::registerDialect<mlir::StandardOpsDialect>();
Only operations from these two dialects can be in the input file. To include all
of the dialects in MLIR Core, you can populate the registry this way:
mlir::registerAllDialects(registry);
4) For `mlir-translate` callback, as well as frontend, Dialects can be loaded in
the context before emitting the IR: context.getOrLoadDialect<ToyDialect>()
There should be an equivalent std.floor op to std.ceil. This includes
matching lowerings for SPIRV, NVVM, ROCDL, and LLVM.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D85940
Legacy implementation of the LLVM dialect in MLIR contained an instance of
llvm::Module as it was required to parse LLVM IR types. The access to the data
layout of this module was exposed to the users for convenience, but in practice
this layout has always been the default one obtained by parsing an empty layout
description string. Current implementation of the dialect no longer relies on
wrapping LLVM IR types, but it kept an instance of DataLayout for
compatibility. This effectively forces a single data layout to be used across
all modules in a given MLIR context, which is not desirable. Remove DataLayout
from the LLVM dialect and attach it as a module attribute instead. Since MLIR
does not yet have support for data layouts, use the LLVM DataLayout in string
form with verification inside MLIR. Introduce the layout when converting a
module to the LLVM dialect and keep the default "" description for
compatibility.
This approach should be replaced with a proper MLIR-based data layout when it
becomes available, but provides an immediate solution to compiling modules with
different layouts, e.g. for GPUs.
This removes the need for LLVMDialectImpl, which is also removed.
Depends On D85650
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D85652
This changes the behavior of constructing MLIRContext to no longer load globally registered dialects on construction. Instead Dialects are only loaded explicitly on demand:
- the Parser is lazily loading Dialects in the context as it encounters them during parsing. This is the only purpose for registering dialects and not load them in the context.
- Passes are expected to declare the dialects they will create entity from (Operations, Attributes, or Types), and the PassManager is loading Dialects into the Context when starting a pipeline.
This changes simplifies the configuration of the registration: a compiler only need to load the dialect for the IR it will emit, and the optimizer is self-contained and load the required Dialects. For example in the Toy tutorial, the compiler only needs to load the Toy dialect in the Context, all the others (linalg, affine, std, LLVM, ...) are automatically loaded depending on the optimization pipeline enabled.
Differential Revision: https://reviews.llvm.org/D85622
This changes the behavior of constructing MLIRContext to no longer load globally registered dialects on construction. Instead Dialects are only loaded explicitly on demand:
- the Parser is lazily loading Dialects in the context as it encounters them during parsing. This is the only purpose for registering dialects and not load them in the context.
- Passes are expected to declare the dialects they will create entity from (Operations, Attributes, or Types), and the PassManager is loading Dialects into the Context when starting a pipeline.
This changes simplifies the configuration of the registration: a compiler only need to load the dialect for the IR it will emit, and the optimizer is self-contained and load the required Dialects. For example in the Toy tutorial, the compiler only needs to load the Toy dialect in the Context, all the others (linalg, affine, std, LLVM, ...) are automatically loaded depending on the optimization pipeline enabled.
The convresion of memref cast operaitons from the Standard dialect to the LLVM
dialect has been emitting bitcasts from a struct type to itself. Beyond being
useless, such casts are invalid as bitcast does not operate on aggregate types.
This kept working by accident because LLVM IR bitcast construction API skips
the construction if types are equal before it verifies that the types are
acceptable in a bitcast. Do not emit such bitcasts, the memref cast that only
adds/erases size information is in fact a noop on the current descriptor as it
always contains dynamic values for all sizes.
Reviewed By: pifon2a
Differential Revision: https://reviews.llvm.org/D85899
This revision removes all of the lingering usages of Type::getKind. A consequence of this is that FloatType is now split into 4 derived types that represent each of the possible float types(BFloat16Type, Float16Type, Float32Type, and Float64Type). Other than this split, this revision is NFC.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D85566
Original modeling of LLVM IR types in the MLIR LLVM dialect had been wrapping
LLVM IR types and therefore required the LLVMContext in which they were created
to outlive them, which was solved by placing the LLVMContext inside the dialect
and thus having the lifetime of MLIRContext. This has led to numerous issues
caused by the lack of thread-safety of LLVMContext and the need to re-create
LLVM IR modules, obtained by translating from MLIR, in different LLVM contexts
to enable parallel compilation. Similarly, llvm::Module had been introduced to
keep track of identified structure types that could not be modeled properly.
A recent series of commits changed the modeling of LLVM IR types in the MLIR
LLVM dialect so that it no longer wraps LLVM IR types and has no dependence on
LLVMContext and changed the ownership model of the translated LLVM IR modules.
Remove LLVMContext and LLVM modules from the implementation of MLIR LLVM
dialect and clean up the remaining uses.
The only part of LLVM IR that remains necessary for the LLVM dialect is the
data layout. It should be moved from the dialect level to the module level and
replaced with an MLIR-based representation to remove the dependency of the
LLVMDialect on LLVM IR library.
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D85445
Historical modeling of the LLVM dialect types had been wrapping LLVM IR types
and therefore needed access to the instance of LLVMContext stored in the
LLVMDialect. The new modeling does not rely on that and only needs the
MLIRContext that is used for uniquing, similarly to other MLIR types. Change
LLVMType::get<Kind>Ty functions to take `MLIRContext *` instead of
`LLVMDialect *` as first argument. This brings the code base closer to
completely removing the dependence on LLVMContext from the LLVMDialect,
together with additional support for thread-safety of its use.
Depends On D85371
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D85372
This prepares for the removal of llvm::Module and LLVMContext from the
mlir::LLVMDialect.
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D85371
`promoteMemRefDescriptors` also converts types of every operand, not only
memref-typed ones. I think `promoteMemRefDescriptors` name does not imply that.
Differential Revision: https://reviews.llvm.org/D85325
Handle the case where the ViewOp takes in a memref that has
an memory space.
Reviewed By: ftynse, bondhugula, nicolasvasilache
Differential Revision: https://reviews.llvm.org/D85048
The bug was not noticed because we didn't have a lot of custom type conversions
directly to LLVM dialect.
Differential Revision: https://reviews.llvm.org/D85192
The current modeling of LLVM IR types in MLIR is based on the LLVMType class
that wraps a raw `llvm::Type *` and delegates uniquing, printing and parsing to
LLVM itself. This is model makes thread-safe type manipulation hard and is
being progressively replaced with a cleaner MLIR model that replicates the type
system. In the new model, LLVMType will no longer have an underlying LLVM IR
type. Restrict access to this type in the current model in preparation for the
change.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D84389
The default lowering of `assert` calls `abort` in case the assertion is
violated. The failure message is ignored but should be used by custom lowerings
that can assume more about their environment.
Differential Revision: https://reviews.llvm.org/D83886
This revision adds support for much deeper type conversion integration into the conversion process, and enables auto-generating cast operations when necessary. Type conversions are now largely automatically managed by the conversion infra when using a ConversionPattern with a provided TypeConverter. This removes the need for patterns to do type cast wrapping themselves and moves the burden to the infra. This makes it much easier to perform partial lowerings when type conversions are involved, as any lingering type conversions will be automatically resolved/legalized by the conversion infra.
To support this new integration, a few changes have been made to the type materialization API on TypeConverter. Materialization has been split into three separate categories:
* Argument Materialization: This type of materialization is used when converting the type of block arguments when calling `convertRegionTypes`. This is useful for contextually inserting additional conversion operations when converting a block argument type, such as when converting the types of a function signature.
* Source Materialization: This type of materialization is used to convert a legal type of the converter into a non-legal type, generally a source type. This may be called when uses of a non-legal type persist after the conversion process has finished.
* Target Materialization: This type of materialization is used to convert a non-legal, or source, type into a legal, or target, type. This type of materialization is used when applying a pattern on an operation, but the types of the operands have not yet been converted.
Differential Revision: https://reviews.llvm.org/D82831
Summary:
The patch makes the index type lowering of the GPU to NVVM/ROCDL conversion configurable. It introduces a pass option that controls the bitwidth used when lowering index computations and uses the LowerToLLVMOptions structure to control the Standard to LLVM lowering.
This commit fixes a use-after-free bug introduced by the reverted commit d10b1a3. It implements the following changes:
- Added a getDefaultOptions method to the LowerToLLVMOptions struct that returns a reference to statically allocated default options.
- Use the getDefaultOptions method to provide default LowerToLLVMOptions (instead of an initializer list).
- Added comments to clarify the required lifetime of the LowerToLLVMOptions
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D82475
`llvm.mlir.constant` was originally introduced as an LLVM dialect counterpart
to `std.constant`. As such, it was supporting "function pointer" constants
derived from the symbol name. This is different from `std.constant` that allows
for creation of a "function" constant since MLIR, unlike LLVM IR, supports
this. Later, `llvm.mlir.addressof` was introduced as an Op that obtains a
constant pointer to a global in the LLVM dialect. It naturally extends to
functions (in LLVM IR, functions are globals) and should be used for defining
"function pointer" values instead.
Fixes PR46344.
Differential Revision: https://reviews.llvm.org/D82667
Conversions of allocation-related operations in Standard-to-LLVM need
declarations of "malloc" and "free" (or equivalents). They use locally created
OpBuilders pointed at the module level to declare these functions if necessary.
This is poorly compatible with the pattern infrastructure that is unaware of
new operations being created. Update the insertion point of the main rewriter
instead.
Differential Revision: https://reviews.llvm.org/D82649
Initially, unranked memref descriptors in the LLVM dialect were designed only
to be passed into functions. An assertion was guarding against returning
unranked memrefs from functions in the standard-to-LLVM conversion. This is
insufficient for functions that wish to return an unranked memref such that the
caller does not know the rank in advance, and hence cannot allocate the
descriptor and pass it in as an argument.
Introduce a calling convention for returning unranked memref descriptors as
follows. An unranked memref descriptor always points to a ranked memref
descriptor stored on stack of the current function. When an unranked memref
descriptor is returned from a function, the ranked memref descriptor it points
to is copied to dynamically allocated memory, the ownership of which is
transferred to the caller. The caller is responsible for deallocating the
dynamically allocated memory and for copying the pointed-to ranked memref
descriptor onto its stack.
Provide default lowerings for std.return, std.call and std.indirect_call that
maintain the conversion defined above.
This convention is additionally exercised by a runtime test to guard against
memory errors.
Differential Revision: https://reviews.llvm.org/D82647
The patch makes the index type lowering of the GPU to NVVM/ROCDL
conversion configurable. It introduces a pass option that controls the
bitwidth used when lowering index computations.
Differential Revision: https://reviews.llvm.org/D80285
This revision removes the TypeConverter parameter passed to the apply* methods, and instead moves the responsibility of region type conversion to patterns. The types of a region can be converted using the 'convertRegionTypes' method, which acts similarly to the existing 'applySignatureConversion'. This method ensures that all blocks within, and including those moved into, a region will have the block argument types converted using the provided converter.
This has the benefit of making more of the legalization logic controlled by patterns, instead of being handled explicitly by the driver. It also opens up the possibility to support multiple type conversions at some point in the future.
This revision also adds a new utility class `FailureOr<T>` that provides a LogicalResult friendly facility for returning a failure or a valid result value.
Differential Revision: https://reviews.llvm.org/D81681
Implement the missing lowering from `std.dim` to the LLVM dialect in case of a
dynamic dimension.
Differential Revision: https://reviews.llvm.org/D81834
Use ::Adaptor alias instead uniformly. Makes the naming more consistent as
adaptor can refer to attributes now too.
Differential Revision: https://reviews.llvm.org/D81789
Allow for dynamic indices in the `dim` operation.
Rather than an attribute, the index is now an operand of type `index`.
This allows to apply the operation to dynamically ranked tensors.
The correct lowering of dynamic indices remains to be implemented.
Differential Revision: https://reviews.llvm.org/D81551
Dialect conversion infrastructure supports 1->N type conversions by requiring
individual conversions to provide facilities to generate operations
retrofitting N values into 1 of the original type when N > 1. This
functionality can also be used to materialize explicit "cast"-like operations,
but it did not support 1->1 type conversions until now. Modify TypeConverter to
support materialization of cast operations for 1-1 conversions.
This also makes materialization specification more extensible following the
same pattern as type conversions. Instead of overloading a virtual function,
users or subclasses of TypeConversion can now register type-specific
materialization callbacks that will be called in order for the given type.
Differential Revision: https://reviews.llvm.org/D79729
This allows constructing operand adaptor from existing op (useful for commonalizing verification as I want to do in a follow up).
I also add ability to use member initializers for the generated adaptor constructors for convenience.
Differential Revision: https://reviews.llvm.org/D80667
This revision starts decoupling the include the kitchen sink behavior of Linalg to LLVM lowering by inserting a -convert-linalg-to-std pass.
The lowering of linalg ops to function calls was previously lowering to memref descriptors by having both linalg -> std and std -> LLVM patterns in the same rewrite.
When separating this step, a new issue occurred: the layout is automatically type-erased by this process. This revision therefore introduces memref casts to perform these type erasures explicitly. To connect everything end-to-end, the LLVM lowering of MemRefCastOp is relaxed because it is artificially more restricted than the op semantics. The op semantics already guarantee that source and target MemRefTypes are cast-compatible. An invalid lowering test now becomes valid and is removed.
Differential Revision: https://reviews.llvm.org/D79468
The main objective of this revision is to change the way static information is represented, propagated and canonicalized in the SubViewOp.
In the current implementation the issue is that canonicalization may strictly lose information because static offsets are combined in irrecoverable ways into the result type, in order to fit the strided memref representation.
The core semantics of the op do not change but the parser and printer do: the op always requires `rank` offsets, sizes and strides. These quantities can now be either SSA values or static integer attributes.
The result type is automatically deduced from the static information and more powerful canonicalizations (as powerful as the representation with sentinel `?` values allows). Previously static information was inferred on a best-effort basis from looking at the source and destination type.
Relevant tests are rewritten to use the idiomatic `offset: x, strides : [...]`-form. Bugs are corrected along the way that were not trivially visible in flattened strided memref form.
Lowering to LLVM is updated, simplified and now supports all cases.
A mixed static-dynamic mode test that wouldn't previously lower is added.
It is an open question, and a longer discussion, whether a better result type representation would be a nicer alternative. For now, the subview op carries the required semantic.
Differential Revision: https://reviews.llvm.org/D79662
This [discussion](https://llvm.discourse.group/t/viewop-isnt-expressive-enough/991/2) raised some concerns with ViewOp.
In particular, the handling of offsets is incorrect and does not match the op description.
Note that with an elemental type change, offsets cannot be part of the type in general because sizeof(srcType) != sizeof(dstType).
Howerver, offset is a poorly chosen term for this purpose and is renamed to byte_shift.
Additionally, for all intended purposes, trying to support non-identity layouts for this op does not bring expressive power but rather increases code complexity.
This revision simplifies the existing semantics and implementation.
This simplification effort is voluntarily restrictive and acts as a stepping stone towards supporting richer semantics: treat the non-common cases as YAGNI for now and reevaluate based on concrete use cases once a round of simplification occurred.
Differential revision: https://reviews.llvm.org/D79541
Complex addition and substraction are the first two binary operations on complex
numbers.
Remaining operations will follow the same pattern.
Differential Revision: https://reviews.llvm.org/D79479
Adding this pattern reduces code duplication. There is no need to have a
custom implementation for lowering to llvm.cmpxchg.
Differential Revision: https://reviews.llvm.org/D78753
Add `CreateComplexOp`, `ReOp`, and `ImOp` to the standard dialect.
This is the first step to support complex numbers.
Differential Revision: https://reviews.llvm.org/D79159
On certain targets std.subview should be able to take memrefs from non-zero
addrspaces. Improve lowering logic to llvm dialect and amend the tests.
Differential Revision: https://reviews.llvm.org/D79024
`addArgument()` is not undoable and should not be used in
ConversionPattern, therefore replacing `splitBlock()` with
`createBlock()`, that creates a block with specified args.
Differential Revision: https://reviews.llvm.org/D78731
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
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
Summary:
Remove usages of asserting vector getters in Type in preparation for the
VectorType refactor. The existence of these functions complicates the
refactor while adding little value.
Reviewers: rriddle, efriedma, sdesmalen
Reviewed By: sdesmalen
Subscribers: frgossen, mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, aartbik, liufengdb, Joonsoo, grosul1, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D77258
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
Minor fixes and cleanup for ShapedType accessors, use
ShapedType::kDynamicSize, add ShapedType::isDynamicDim.
Differential Revision: https://reviews.llvm.org/D77710
820c420d4e1c630b5ead285917c6ecdd2f5092ad did not really fix all build
issues by D77528. This gets rid of two unnecessary 'using' declarations.
Differential Revision: https://reviews.llvm.org/D77726
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
Summary:
This is much cleaner, and fits the same structure as many other tablegen backends. This was not done originally as the CRTP in the pass classes made it overly verbose/complex.
Differential Revision: https://reviews.llvm.org/D77367
This revision removes all of the CRTP from the pass hierarchy in preparation for using the tablegen backend instead. This creates a much cleaner interface in the C++ code, and naturally fits with the rest of the infrastructure. A new utility class, PassWrapper, is added to replicate the existing behavior for passes not suitable for using the tablegen backend.
Differential Revision: https://reviews.llvm.org/D77350
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
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
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.
This revision adds support for generating utilities for passes such as options/statistics/etc. that can be inferred from the tablegen definition. This removes additional boilerplate from the pass, and also makes it easier to remove the reliance on the pass registry to provide certain things(e.g. the pass argument).
Differential Revision: https://reviews.llvm.org/D76659
This removes the need to statically register conversion passes, and also puts all of the conversions within one centralized file.
Differential Revision: https://reviews.llvm.org/D76658
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
Multiple operation conversions from the Standard dialect to the LLVM dialect
are trivial one-to-one conversions that use only the pattern defined in base
utility classes such as OneToOneConvertToLLVMPattern and
VectorConvertToLLVMPattern. Use template aliases ("using" declarations) instead
of creating derived classes without new functionality.
Summary:
Provide a public VectorConvertToLLVMPattern utility class to implement
conversions with automatic unrolling of operation on multidimensional vectors
to lists of operations on single-dimensional vectors when lowering to the LLVM
dialect. Drop the template-based check on the number of operands since the
actual implementation does not depend on the operand number anymore. This check
only creates spurious concepts (UnaryOpLowering, BinaryOpLowering, etc).
Differential Revision: https://reviews.llvm.org/D76865
Summary:
The Standard-to-LLVM dialect convresion has a set of utility classes that
simplify conversions, including patterns that provide one-to-one conversion
operation conversion with optional result packing. Expose these classes in a
public header so that conversions other than Standard-to-LLVM (e.g. vectors, or
LLVM-based intrinsics) could also use them. Since the patterns are implemented
as class templates and in order to keep the code size limited, keep the
implementation private by resorting to op identifiers instead of template-based
builders.
Differential Revision: https://reviews.llvm.org/D76864
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
Diego Caballero