The existing approach to translation to the LLVM IR relies on a single
translation supporting the base LLVM dialect, extensible through inheritance to
support intrinsic-based dialects also derived from LLVM IR such as NVVM and
AVX512. This approach does not scale well as it requires additional
translations to be created for each new intrinsic-based dialect and does not
allow them to mix in the same module, contrary to the rest of the MLIR
infrastructure. Furthermore, OpenMP translation ingrained itself into the main
translation mechanism.
Start refactoring the translation to LLVM IR to operate using dialect
interfaces. Each dialect that contains ops translatable to LLVM IR can
implement the interface for translating them, and the top-level translation
driver can operate on interfaces without knowing about specific dialects.
Furthermore, the delayed dialect registration mechanism allows one to avoid a
dependency on LLVM IR in the dialect that is translated to it by implementing
the translation as a separate library and only registering it at the client
level.
This change introduces the new mechanism and factors out the translation of the
"main" LLVM dialect. The remaining dialects will follow suit.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D96503
This reverts commit 511dd4f438 along with
a couple fixes.
Original message:
Now the context is the first, rather than the last input.
This better matches the rest of the infrastructure and makes
it easier to move these types to being declaratively specified.
Phabricator: https://reviews.llvm.org/D96111
Now the context is the first, rather than the last input.
This better matches the rest of the infrastructure and makes
it easier to move these types to being declaratively specified.
Differential Revision: https://reviews.llvm.org/D96111
A cast-like operation is one that converts from a set of input types to a set of output types. The arity of the inputs may be from 0-N, whereas the arity of the outputs may be anything from 1-N. Cast-like operations are removable in cases where they produce a "no-op", i.e when the input types and output types match 1-1.
Differential Revision: https://reviews.llvm.org/D94831
The LLVM dialect type system has been closed until now, i.e. did not support
types from other dialects inside containers. While this has had obvious
benefits of deriving from a common base class, it has led to some simple types
being almost identical with the built-in types, namely integer and floating
point types. This in turn has led to a lot of larger-scale complexity: simple
types must still be converted, numerous operations that correspond to LLVM IR
intrinsics are replicated to produce versions operating on either LLVM dialect
or built-in types leading to quasi-duplicate dialects, lowering to the LLVM
dialect is essentially required to be one-shot because of type conversion, etc.
In this light, it is reasonable to trade off some local complexity in the
internal implementation of LLVM dialect types for removing larger-scale system
complexity. Previous commits to the LLVM dialect type system have adapted the
API to support types from other dialects.
Replace LLVMIntegerType with the built-in IntegerType plus additional checks
that such types are signless (these are isolated in a utility function that
replaced `isa<LLVMType>` and in the parser). Temporarily keep the possibility
to parse `!llvm.i32` as a synonym for `i32`, but add a deprecation notice.
Reviewed By: mehdi_amini, silvas, antiagainst
Differential Revision: https://reviews.llvm.org/D94178
Remove unnecessary `&` from loop variables.
Fix warnings: "loop variable is always a copy because the range does not
return a reference".
```
[240/2862] Building CXX object tools/mlir/tools/mlir-tblgen/CMakeFiles/mlir-tblgen.dir/TypeDefGen.cpp.o
llvm-project/mlir/tools/mlir-tblgen/TypeDefGen.cpp:50:25: warning: loop variable 'typeDef' is always a copy because the range of type 'llvm::iterator_range<llvm::mapped_iterator<std::__1::__wrap_iter<llvm::Record **>, (lambda at llvm-project/mlir/tools/mlir-tblgen/TypeDefGen.cpp:40:16), mlir::tblgen::TypeDef> >' does not return a reference [-Wrange-loop-analysis]
for (const TypeDef &typeDef : defs)
^
llvm-project/mlir/tools/mlir-tblgen/TypeDefGen.cpp:50:10: note: use non-reference type 'mlir::tblgen::TypeDef'
for (const TypeDef &typeDef : defs)
^~~~~~~~~~~~~~~~~~~~~~~~
llvm-project/mlir/tools/mlir-tblgen/TypeDefGen.cpp:64:23: warning: loop variable 'typeDef' is always a copy because the range of type 'llvm::iterator_range<llvm::mapped_iterator<std::__1::__wrap_iter<llvm::Record **>, (lambda at llvm-project/mlir/tools/mlir-tblgen/TypeDefGen.cpp:40:16), mlir::tblgen::TypeDef> >' does not return a reference [-Wrange-loop-analysis]
for (const TypeDef &typeDef : defs)
^
llvm-project/mlir/tools/mlir-tblgen/TypeDefGen.cpp:64:8: note: use non-reference type 'mlir::tblgen::TypeDef'
for (const TypeDef &typeDef : defs)
^~~~~~~~~~~~~~~~~~~~~~~~
2 warnings generated.
[1934/2862] Building CXX object tools...Files/toyc-ch4.dir/mlir/MLIRGen.cpp.o
llvm-project/mlir/examples/toy/Ch4/mlir/MLIRGen.cpp:139:22: warning: loop variable 'name_value' is always a copy because the range of type 'detail::zippy<detail::zip_shortest, ArrayRef<unique_ptr<VariableExprAST, default_delete<VariableExprAST> > > &, MutableArrayRef<BlockArgument> >' does not return a reference [-Wrange-loop-analysis]
for (const auto &name_value :
^
llvm-project/mlir/examples/toy/Ch4/mlir/MLIRGen.cpp:139:10: note: use non-reference type 'std::__1::tuple<const std::__1::unique_ptr<toy::VariableExprAST, std::__1::default_delete<toy::VariableExprAST> > &, mlir::BlockArgument &>'
for (const auto &name_value :
^~~~~~~~~~~~~~~~~~~~~~~~
1 warning generated.
[1940/2862] Building CXX object tools...Files/toyc-ch5.dir/mlir/MLIRGen.cpp.o
llvm-project/mlir/examples/toy/Ch5/mlir/MLIRGen.cpp:139:22: warning: loop variable 'name_value' is always a copy because the range of type 'detail::zippy<detail::zip_shortest, ArrayRef<unique_ptr<VariableExprAST, default_delete<VariableExprAST> > > &, MutableArrayRef<BlockArgument> >' does not return a reference [-Wrange-loop-analysis]
for (const auto &name_value :
^
llvm-project/mlir/examples/toy/Ch5/mlir/MLIRGen.cpp:139:10: note: use non-reference type 'std::__1::tuple<const std::__1::unique_ptr<toy::VariableExprAST, std::__1::default_delete<toy::VariableExprAST> > &, mlir::BlockArgument &>'
for (const auto &name_value :
^~~~~~~~~~~~~~~~~~~~~~~~
1 warning generated.
```
Reviewed By: jpienaar
Differential Revision: https://reviews.llvm.org/D94003
LLVMType contains numerous static constructors that were initially introduced
for API compatibility with LLVM. Most of these merely forward to arguments to
`SpecificType::get` (MLIR defines classes for all types, unlike LLVM IR), while
some introduce subtle semantics differences due to different modeling of MLIR
types (e.g., structs are not auto-renamed in case of conflicts). Furthermore,
these constructors don't match MLIR idioms and actively prevent us from making
the LLVM dialect type system more open. Remove them and use `SpecificType::get`
instead.
Depends On D93680
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D93681
This is part of a larger refactoring the better congregates the builtin structures under the BuiltinDialect. This also removes the problematic "standard" naming that clashes with the "standard" dialect, which is not defined within IR/. A temporary forward is placed in StandardTypes.h to allow time for downstream users to replaced references.
Differential Revision: https://reviews.llvm.org/D92435
Given that OpState already implicit converts to Operator*, this seems reasonable.
The alternative would be to add more functions to OpState which forward to Operation.
Reviewed By: rriddle, ftynse
Differential Revision: https://reviews.llvm.org/D92266
These includes have been deprecated in favor of BuiltinDialect.h, which contains the definitions of ModuleOp and FuncOp.
Differential Revision: https://reviews.llvm.org/D91572
This is an error prone behavior, I frequently have ~20 min debugging sessions when I hit
an unexpected implicit nesting. This default makes the C++ API safer for users.
Depends On D90669
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D90671
Often times the legality of inlining can change depending on if the callable is going to be inlined in-place, or cloned. For example, some operations are not allowed to be duplicated and can only be inlined if the original callable will cease to exist afterwards. The new `wouldBeCloned` flag allows for dialects to hook into this when determining legality.
Differential Revision: https://reviews.llvm.org/D90360
In certain situations it isn't legal to inline a call operation, but this isn't something that is possible(at least not easily) to prevent with the current hooks. This revision adds a new hook so that dialects with call operations that shouldn't be inlined can prevent it.
Differential Revision: https://reviews.llvm.org/D90359
A recent commit introduced a new syntax for specifying builder arguments in
ODS, which is better amenable to automated processing, and deprecated the old
form. Transition all dialects as well as Linalg ODS generator to use the new
syntax.
Add a deprecation notice to ODS generator.
Reviewed By: rriddle, jpienaar
Differential Revision: https://reviews.llvm.org/D90038
This class represents a rewrite pattern list that has been frozen, and thus immutable. This replaces the uses of OwningRewritePatternList in pattern driver related API, such as dialect conversion. When PDL becomes more prevalent, this API will allow for optimizing a set of patterns once without the need to do this per run of a pass.
Differential Revision: https://reviews.llvm.org/D89104
This patch introduces a SPIR-V runner. The aim is to run a gpu
kernel on a CPU via GPU -> SPIRV -> LLVM conversions. This is a first
prototype, so more features will be added in due time.
- Overview
The runner follows similar flow as the other runners in-tree. However,
having converted the kernel to SPIR-V, we encode the bind attributes of
global variables that represent kernel arguments. Then SPIR-V module is
converted to LLVM. On the host side, we emulate passing the data to device
by creating in main module globals with the same symbolic name as in kernel
module. These global variables are later linked with ones from the nested
module. We copy data from kernel arguments to globals, call the kernel
function from nested module and then copy the data back.
- Current state
At the moment, the runner is capable of running 2 modules, nested one in
another. The kernel module must contain exactly one kernel function. Also,
the runner supports rank 1 integer memref types as arguments (to be scaled).
- Enhancement of JitRunner and ExecutionEngine
To translate nested modules to LLVM IR, JitRunner and ExecutionEngine were
altered to take an optional (default to `nullptr`) function reference that
is a custom LLVM IR module builder. This allows to customize LLVM IR module
creation from MLIR modules.
Reviewed By: ftynse, mravishankar
Differential Revision: https://reviews.llvm.org/D86108
Now backends spell out which namespace they want to be in, instead of relying on
clients #including them inside already-opened namespaces. This also means that
cppNamespaces should be fully qualified, and there's no implicit "::mlir::"
prepended to them anymore.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D86811
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
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
The documentation needs a refresh now that "kinds" are no longer a concept. This revision also adds mentions to a few other new concepts, e.g. traits and interfaces.
Differential Revision: https://reviews.llvm.org/D86182
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 greatly simplifies a large portion of the underlying infrastructure, allows for lookups of singleton classes to be much more efficient and always thread-safe(no locking). As a result of this, the dialect symbol registry has been removed as it is no longer necessary.
For users broken by this change, an alert was sent out(https://llvm.discourse.group/t/removing-kinds-from-attributes-and-types) that helps prevent a majority of the breakage surface area. All that should be necessary, if the advice in that alert was followed, is removing the kind passed to the ::get methods.
Differential Revision: https://reviews.llvm.org/D86121
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>()
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.
This revision refactors the default definition of the attribute and type `classof` methods to use the TypeID of the concrete class instead of invoking the `kindof` method. The TypeID is already used as part of uniquing, and this allows for removing the need for users to define any of the type casting utilities themselves.
Differential Revision: https://reviews.llvm.org/D85356
This patch moves the registration to a method in the MLIRContext: getOrCreateDialect<ConcreteDialect>()
This method requires dialect to provide a static getDialectNamespace()
and store a TypeID on the Dialect itself, which allows to lazyily
create a dialect when not yet loaded in the context.
As a side effect, it means that duplicated registration of the same
dialect is not an issue anymore.
To limit the boilerplate, TableGen dialect generation is modified to
emit the constructor entirely and invoke separately a "init()" method
that the user implements.
Differential Revision: https://reviews.llvm.org/D85495
Due to the original type system implementation, LLVMDialect in MLIR contains an
LLVMContext in which the relevant objects (types, metadata) are created. When
an MLIR module using the LLVM dialect (and related intrinsic-based dialects
NVVM, ROCDL, AVX512) is converted to LLVM IR, it could only live in the
LLVMContext owned by the dialect. The type system no longer relies on the
LLVMContext, so this limitation can be removed. Instead, translation functions
now take a reference to an LLVMContext in which the LLVM IR module should be
constructed. The caller of the translation functions is responsible for
ensuring the same LLVMContext is not used concurrently as the translation no
longer uses a dialect-wide context lock.
As an additional bonus, this change removes the need to recreate the LLVM IR
module in a different LLVMContext through printing and parsing back, decreasing
the compilation overhead in JIT and GPU-kernel-to-blob passes.
Reviewed By: rriddle, mehdi_amini
Differential Revision: https://reviews.llvm.org/D85443
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 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
We recently introduced support for building loops or loop nests using callbacks
that populate the body. Use these in the tutorial instead of setInsertionPoint
manipulations.
Differential Revision: https://reviews.llvm.org/D82104
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
The tutorial refers to invoking toyc with '-mlir-print-debuginfo' but
it wasn't registered anymore.
Differential Revision: https://reviews.llvm.org/D81604
The lower-to-affine-loops pass in chapters 5-7 of the Toy tutorial has
been creating affine loops, erasing their terminator and creating it
anew using a PatternRewriter instance to work around the fact that
implicit terminators were created without notifying the rewriter. Now
that has been fixed in 3ccf4a5bd1, remove the code erasing and
re-creating the terminators and rely on the default ones.
Multiple places in the code base were erasing Blocks or operations in them
using in-place modifications (`Block::erase` or `Block::clear`) unknown to
ConversionPatternRewriter. These operations could not be undone if the pattern
failed and could lead to inconsistent in-memory state of the IR with dangling
pointers. Use `ConversionPatternRewriter::eraseOp` and `::eraseBlock` instead.
Differential Revision: https://reviews.llvm.org/D80136
When creating temporary `scf.for` loops in `toy.print` lowering, the block
insertion point was erronously set up to the beginning of the block rather than
to its end, contradicting the comment just above the insertion point change.
The code was nevertheless operational because `scf.for` was setting up its
`scf.yield` terminator in an opaque to the pattern rewriting infrastructure
way. Now that it is about to change, the problem would have been exposed and
lead to conversion failures.
Differential Revision: https://reviews.llvm.org/D80133
Alex Zinenko