| Commit message (Collapse) | Author | Age | Files | Lines |
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This commit defines a new SPIR-V dialect attribute for specifying
a SPIR-V target environment. It is a dictionary attribute containing
the SPIR-V version, supported extension list, and allowed capability
list. A SPIRVConversionTarget subclass is created to take in the
target environment and sets proper dynmaically legal ops by querying
the op availability interface of SPIR-V ops to make sure they are
available in the specified target environment. All existing conversions
targeting SPIR-V is changed to use this SPIRVConversionTarget. It
probes whether the input IR has a `spv.target_env` attribute,
otherwise, it uses the default target environment: SPIR-V 1.0 with
Shader capability and no extra extensions.
Differential Revision: https://reviews.llvm.org/D72256
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properly value-typed.
Summary: These were temporary methods used to simplify the transition.
Reviewed By: antiagainst
Differential Revision: https://reviews.llvm.org/D72548
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Fix typos related to (de)serialization of spv.selection.
Differential Revision: https://reviews.llvm.org/D72503
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instances. NFCI.
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SPIRV/ headers live under mlir/Dialect/.
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D72141
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This commit fixes shader ABI attributes to use `spv.` as the prefix
so that they match the dialect's namespace. This enables us to add
verification hooks in the SPIR-V dialect to verify them.
Reviewed By: mravishankar
Differential Revision: https://reviews.llvm.org/D72062
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Lots of SPIR-V ops take enum attributes and certain enum cases
need extra capabilities or extensions to be available. This commit
extends to allow specifying availability spec on enum cases.
Extra utility functions are generated for the corresponding enum
classes to return the availability requirement. The availability
interface implemention for a SPIR-V op now goes over all enum
attributes to collect the availability requirements.
Reviewed By: mravishankar
Differential Revision: https://reviews.llvm.org/D71947
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This allows us to include the definitions of these attributes in
other files without pulling in all dependencies for lowering.
Reviewed By: mravishankar
Differential Revision: https://reviews.llvm.org/D72054
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SPIR-V has a few mechanisms to control op availability: version,
extension, and capabilities. These mechanisms are considered as
different availability classes.
This commit introduces basic definitions for modelling SPIR-V
availability classes. Specifically, an `Availability` class is
added to SPIRVBase.td, along with two subclasses: MinVersion
and MaxVersion for versioning. SPV_Op is extended to take a
list of `Availability`. Each `Availability` instance carries
information for generating op interfaces for the corresponding
availability class and also the concrete availability
requirements.
With the availability spec on ops, we can now auto-generate the
op interfaces of all SPIR-V availability classes and also
synthesize the op's implementations of these interfaces. The
interface generation is done via new TableGen backends
-gen-avail-interface-{decls|defs}. The op's implementation is
done via -gen-spirv-avail-impls.
Differential Revision: https://reviews.llvm.org/D71930
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ValuePtr was a temporary typedef during the transition to a value-typed Value.
PiperOrigin-RevId: 286945714
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This means that in-place, or root, updates need to use explicit calls to `startRootUpdate`, `finalizeRootUpdate`, and `cancelRootUpdate`. The major benefit of this change is that it enables in-place updates in DialectConversion, which simplifies the FuncOp pattern for example. The major downside to this is that the cases that *may* modify an operation in-place will need an explicit cancel on the failure branches(assuming that they started an update before attempting the transformation).
PiperOrigin-RevId: 286933674
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internal pointer storage.
This will enable future commits to reimplement the internal implementation of OpResult without needing to change all of the existing users. This is part of a chain of commits optimizing the size of operation results.
PiperOrigin-RevId: 286930047
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PiperOrigin-RevId: 286924059
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pointer storage.
This will enable future commits to reimplement the internal implementation of OpResult without needing to change all of the existing users. This is part of a chain of commits optimizing the size of operation results.
PiperOrigin-RevId: 286919966
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PiperOrigin-RevId: 286906740
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Value being value-typed.
This is an initial step to refactoring the representation of OpResult as proposed in: https://groups.google.com/a/tensorflow.org/g/mlir/c/XXzzKhqqF_0/m/v6bKb08WCgAJ
This change will make it much simpler to incrementally transition all of the existing code to use value-typed semantics.
PiperOrigin-RevId: 286844725
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* Fixes use of anonymous namespace for static methods.
* Uses explicit qualifiers(mlir::) instead of wrapping the definition with the namespace.
PiperOrigin-RevId: 286222654
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in `mlir` namespace.
Aside from being cleaner, this also makes the codebase more consistent.
PiperOrigin-RevId: 286206974
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GCC is unable to properly implicitly capture 'this' in generic lambdas. This bug is not fixed until 7.1.0:
https://gcc.gnu.org/bugzilla/show_bug.cgi?id=67274
PiperOrigin-RevId: 286083427
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PiperOrigin-RevId: 286066371
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The inline interface uses two methods to check legality of inling:
1) Can a region be inlined into another.
2) Can an operation be inlined into another.
Setting the former to true, allows the inliner to use the second for
legality checks. Add this method to the SPIR-V dialect inlining
interface.
PiperOrigin-RevId: 286041734
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Some changes to the dialect generation script to allow specification
of different base class to derive from in ODS.
PiperOrigin-RevId: 285859230
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This updates the lowering pipelines from the GPU dialect to lower-level
dialects (NVVM, SPIRV) to use the recently introduced gpu.func operation
instead of a standard function annotated with an attribute. In particular, the
kernel outlining is updated to produce gpu.func instead of std.func and the
individual conversions are updated to consume gpu.funcs and disallow standard
funcs after legalization, if necessary. The attribute "gpu.kernel" is preserved
in the generic syntax, but can also be used with the custom syntax on
gpu.funcs. The special kind of function for GPU allows one to use additional
features such as memory attribution.
PiperOrigin-RevId: 285822272
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This cleans up the implementation of the various operation print methods. This is done via a combination of code cleanup, adding new streaming methods to the printer(e.g. operand ranges), etc.
PiperOrigin-RevId: 285285181
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PiperOrigin-RevId: 285036647
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Add some convenience build methods to SPIR-V ops and update the
lowering to use these methods where possible.
For SPIRV::CompositeExtractOp move the method to deduce type of
element based on base and indices into a convenience function. Some
additional functionality needed to handle differences between parsing
and verification methods.
PiperOrigin-RevId: 284794404
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Closes tensorflow/mlir#308
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/308 from denis0x0D:sandbox/composite_construct 9ef7180f77f9374bcd05afc4f9e6c1d2d72d02b7
PiperOrigin-RevId: 284613617
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The patterns to be folded away can be commonly generated
during lowering to SPIR-V.
PiperOrigin-RevId: 284604855
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The existing GPU to SPIR-V lowering created a spv.module for every
function with gpu.kernel attribute. A better approach is to lower the
module that the function lives in (which has the attribute
gpu.kernel_module) to a spv.module operation. This better captures the
host-device separation modeled by GPU dialect and simplifies the
lowering as well.
PiperOrigin-RevId: 284574688
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Closes tensorflow/mlir#304
PiperOrigin-RevId: 284568358
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This allows for users to provide operand_range and result_range in builder.create<> calls, instead of requiring an explicit copy into a separate data structure like SmallVector/std::vector.
PiperOrigin-RevId: 284360710
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During lowering, spv.module might be within other modules (for example
gpu kernel module). Walk the module op to find spirv module to
serialize.
PiperOrigin-RevId: 284262550
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The iterator should be erased before adding a new entry
into blockMergeInfo to avoid iterator invalidation.
Closes tensorflow/mlir#299
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/299 from denis0x0D:sandbox/reoder_erase 983be565809aa0aadfc7e92962e4d4b282f63c66
PiperOrigin-RevId: 284173235
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Closes tensorflow/mlir#290
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/290 from kiszk:spelling_tweaks_201912 9d9afd16a723dd65754a04698b3976f150a6054a
PiperOrigin-RevId: 284169681
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A CompositeInsertOp operation make a copy of a composite object,
while modifying one part of it.
Closes tensorflow/mlir#292
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/292 from denis0x0D:sandbox/composite_insert 2200962b9057bda53cd2f2866b461e2797196380
PiperOrigin-RevId: 284036551
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PiperOrigin-RevId: 283997917
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For serialization, when we have nested ops, the inner loop will create multiple
SPIR-V blocks. If the outer loop has block arguments (which corresponds to
OpPhi instructions), we defer the handling of OpPhi's parent block handling
until we serialized all blocks and then fix it up with the result <id>. These two
cases happening together was generating invalid SPIR-V blob because we
previously assume the parent block to be the block containing the terminator.
That is not true anymore when the block contains structured control flow ops.
If that happens, it should be fixed to use the structured control flow op's
merge block.
For deserialization, we record a map from header blocks to their corresponding
merge and continue blocks during the initial deserialization and then use the
info to construct spv.selection/spv.loop. The existing implementation will also
fall apart when we have nested loops. If so, we clone all blocks for the outer
loop, including the ones for the inner loop, to the spv.loop's region. So the map
for header blocks' merge info need to be updated; otherwise we are operating
on already deleted blocks.
PiperOrigin-RevId: 283949230
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This CL also did the following cleanup:
- Moved the test for spv.SubgroupBallotKHR to its own file
- Wrapped generated canonicalization patterns in anonymous namespace
- Updated header comments in SPVOps.td
PiperOrigin-RevId: 283650091
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The SPIR-V lowering used nested !spv.arrays to represented
multi-dimensional arrays, with the hope that in-conjunction with the
layout annotations, the shape and layout of memref can be represented
directly. It is unclear though how portable this representation will
end up being. It will rely on driver compilers implementing complex
index computations faithfully. A more portable approach is to use
linearized arrays to represent memrefs and explicitly instantiate all
the index computation in SPIR-V. This gives added benefit that we can
further optimize the generated code in MLIR before generating the
SPIR-V binary.
PiperOrigin-RevId: 283571167
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PiperOrigin-RevId: 283522284
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folding.
Closes tensorflow/mlir#281
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/281 from denis0x0D:sandbox/composite_ex_fold d02d73658bd1b9eaa515eb4e0aee34bc41d4252b
PiperOrigin-RevId: 282971563
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Updated comments and used static instead of anonymous namspace
to hide functions to be consistent with the existing codebase.
PiperOrigin-RevId: 282847784
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Getting constant zero or one is very common so it merits a special handy
method on spirv::ConstantOp itself.
PiperOrigin-RevId: 282832572
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Adding zero and multiplying one can be common when generating code
for index calculation.
This CL also sorted canonicalize.mlir to alphabetical order.
PiperOrigin-RevId: 282828055
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These changes to SPIR-V lowering while adding support for lowering
SUbViewOp, but are not directly related.
- Change the lowering of MemRefType to
!spv.ptr<!spv.struct<!spv.array<...>[offset]>, ..>
This is consistent with the Vulkan spec.
- To enable testing a simple pattern of lowering functions is added to
ConvertStandardToSPIRVPass. This is just used to convert the type of
the arguments of the function. The added function lowering itself is
not meant to be the way functions are eventually lowered into SPIR-V
dialect.
PiperOrigin-RevId: 282589644
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PiperOrigin-RevId: 282415592
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To simplify the lowering into SPIR-V, while still respecting the ABI
requirements of SPIR-V/Vulkan, split the process into two
1) While lowering a function to SPIR-V (when the function is an entry
point function), allow specifying attributes on arguments and
function itself that describe the ABI of the function.
2) Add a pass that materializes the ABI described in the function.
Two attributes are needed.
1) Attribute on arguments of the entry point function that describe
the descriptor_set, binding, storage class, etc, of the
spv.globalVariable this argument will be replaced by
2) Attribute on function that specifies workgroup size, etc. (for now
only workgroup size).
Add the pass -spirv-lower-abi-attrs to materialize the ABI described
by the attributes.
This change makes the SPIRVBasicTypeConverter class unnecessary and is
removed, further simplifying the SPIR-V lowering path.
PiperOrigin-RevId: 282387587
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This CL added necessary files and settings for using DRR to
write SPIR-V canonicalization patterns and also converted the
patterns for spv.Bitcast and spv.LogicalNot.
PiperOrigin-RevId: 282132786
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Add a canonicalizer for `spirv::LogicalNotOp`.
Converts:
* spv.LogicalNot(spv.IEqual(...)) -> spv.INotEqual(...)
* spv.LogicalNot(spv.INotEqual(...)) -> spv.IEqual(...)
* spv.LogicalNot(spv.LogicalEqual(...)) -> spv.LogicalNotEqual(...)
* spv.LogicalNot(spv.LogicalNotEqual(...)) -> spv.LogicalEqual(...)
Also moved the test for spv.IMul to arithemtic tests.
Closes tensorflow/mlir#256
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/256 from denis0x0D:sandbox/canon_logical_not 76ab5787b2c777f948c8978db061d99e76453d44
PiperOrigin-RevId: 282012356
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