Add support for attribute nvvm.grid_constant on LLVM function arguments.
The attribute can be attached only to arguments of type llvm.ptr that
have llvm.byval attribute.
Generate LLVM metadata for functions with nvvm.grid_constant arguments.
The metadata node is a list of integers, where each integer n denotes
that the nth parameter has the
grid_constant annotation (numbering from 1). The generated metadata node
will be handled by NVVM compiler. See
https://docs.nvidia.com/cuda/nvvm-ir-spec/index.html#supported-properties
for documentation on grid_constant property.
This patch also adds convertParameterAttr to
LLVMTranslationDialectInterface for supporting the translation of
derived dialect attributes on function parameters
Extend the `amendOperation` mechanism for translating dialect attributes
attached to operations from another dialect when translating MLIR to
LLVM IR. Previously, this mechanism would have no knowledge of the LLVM
IR instructions created for the given operation, making it impossible
for it to perform local modifications such as attaching operation-level
metadata. Collect instructions inserted by the LLVM IR builder and pass
them to `amendOperation`.
Generalize `extractFromI64ArrayAttr` to `extractFromIntegerArrayAttr`, so that arbitrary integer/bool types can be extracted.
Differential Revision: https://reviews.llvm.org/D154974
The MLIR classes Type/Attribute/Operation/Op/Value support
cast/dyn_cast/isa/dyn_cast_or_null functionality through llvm's doCast
functionality in addition to defining methods with the same name.
This change begins the migration of uses of the method to the
corresponding function call as has been decided as more consistent.
Note that there still exist classes that only define methods directly,
such as AffineExpr, and this does not include work currently to support
a functional cast/isa call.
Caveats include:
- This clang-tidy script probably has more problems.
- This only touches C++ code, so nothing that is being generated.
Context:
- https://mlir.llvm.org/deprecation/ at "Use the free function variants
for dyn_cast/cast/isa/…"
- Original discussion at https://discourse.llvm.org/t/preferred-casting-style-going-forward/68443
Implementation:
This first patch was created with the following steps. The intention is
to only do automated changes at first, so I waste less time if it's
reverted, and so the first mass change is more clear as an example to
other teams that will need to follow similar steps.
Steps are described per line, as comments are removed by git:
0. Retrieve the change from the following to build clang-tidy with an
additional check:
https://github.com/llvm/llvm-project/compare/main...tpopp:llvm-project:tidy-cast-check
1. Build clang-tidy
2. Run clang-tidy over your entire codebase while disabling all checks
and enabling the one relevant one. Run on all header files also.
3. Delete .inc files that were also modified, so the next build rebuilds
them to a pure state.
4. Some changes have been deleted for the following reasons:
- Some files had a variable also named cast
- Some files had not included a header file that defines the cast
functions
- Some files are definitions of the classes that have the casting
methods, so the code still refers to the method instead of the
function without adding a prefix or removing the method declaration
at the same time.
```
ninja -C $BUILD_DIR clang-tidy
run-clang-tidy -clang-tidy-binary=$BUILD_DIR/bin/clang-tidy -checks='-*,misc-cast-functions'\
-header-filter=mlir/ mlir/* -fix
rm -rf $BUILD_DIR/tools/mlir/**/*.inc
git restore mlir/lib/IR mlir/lib/Dialect/DLTI/DLTI.cpp\
mlir/lib/Dialect/Complex/IR/ComplexDialect.cpp\
mlir/lib/**/IR/\
mlir/lib/Dialect/SparseTensor/Transforms/SparseVectorization.cpp\
mlir/lib/Dialect/Vector/Transforms/LowerVectorMultiReduction.cpp\
mlir/test/lib/Dialect/Test/TestTypes.cpp\
mlir/test/lib/Dialect/Transform/TestTransformDialectExtension.cpp\
mlir/test/lib/Dialect/Test/TestAttributes.cpp\
mlir/unittests/TableGen/EnumsGenTest.cpp\
mlir/test/python/lib/PythonTestCAPI.cpp\
mlir/include/mlir/IR/
```
Differential Revision: https://reviews.llvm.org/D150123
Ptx model has `redux.sync` that performs reduction operation on the data from each predicated active thread in the thread group. It only is available sm80+.
This revision adds redux as on op to nvvm dialect.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D142088
PTX programming models provides some performance tuning directives; see https://docs.nvidia.com/cuda/parallel-thread-execution/index.html#performance-tuning-directives
The downstream compiler namely `ptxas` leverages these information for better register allocation or to handle other resource management that improves the performance.
This revision introduce all the kernel based directives to MLIR's NVVM dialect. The list is below
```
maxnreg -> max register per thread in CTA
maxntid -> max threads per CTA
reqntid -> exact number of threads per CTA
minnctapersm -> min CTA per SM
```
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D136931
The current dialect registry allows for attaching delayed interfaces, that are added to attrs/dialects/ops/etc.
when the owning dialect gets loaded. This is clunky for quite a few reasons, e.g. each interface type has a
separate tracking structure, and is also quite limiting. This commit refactors this delayed mutation of
dialect constructs into a more general DialectExtension mechanism. This mechanism is essentially a registration
callback that is invoked when a set of dialects have been loaded. This allows for attaching interfaces directly
on the loaded constructs, and also allows for loading new dependent dialects. The latter of which is
extremely useful as it will now enable dependent dialects to only apply in the contexts in which they
are necessary. For example, a dialect dependency can now be conditional on if a user actually needs the
interface that relies on it.
Differential Revision: https://reviews.llvm.org/D120367
NamedAttribute is currently represented as an std::pair, but this
creates an extremely clunky .first/.second API. This commit
converts it to a class, with better accessors (getName/getValue)
and also opens the door for more convenient API in the future.
Differential Revision: https://reviews.llvm.org/D113956
wmma intrinsics have a large number of combinations, ideally we want to be able
to target all the different variants. To avoid a combinatorial explosion in the
number of mlir op we use attributes to represent the different variation of
load/store/mma ops. We also can generate with tablegen helpers to know which
combinations are available. Using this we can avoid having too hardcode a path
for specific shapes and can support more types.
This patch also adds boiler plates for tf32 op support.
Differential Revision: https://reviews.llvm.org/D112689
There is no need for the interface implementations to be exposed, opaque
registration functions are sufficient for all users, similarly to passes.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D97852
Port the translation of five dialects that define LLVM IR intrinsics
(LLVMAVX512, LLVMArmNeon, LLVMArmSVE, NVVM, ROCDL) to the new dialect
interface-based mechanism. This allows us to remove individual translations
that were created for each of these dialects and just use one common
MLIR-to-LLVM-IR translation that potentially supports all dialects instead,
based on what is registered and including any combination of translatable
dialects. This removal was one of the main goals of the refactoring.
To support the addition of GPU-related metadata, the translation interface is
extended with the `amendOperation` function that allows the interface
implementation to post-process any translated operation with dialect attributes
from the dialect for which the interface is implemented regardless of the
operation's dialect. This is currently applied to "kernel" functions, but can
be used to construct other metadata in dialect-specific ways without
necessarily affecting operations.
Depends On D96591, D96504
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D96592
