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
When the origin of a shape is an extent tensor the operation `get_extent` can be
lowered directly to `extract_element`.
This choice circumvents the necessity to materialize the shape in memory.
Differential Revision: https://reviews.llvm.org/D82645
When the shape is derived from a tensor argument the shape extent can be derived
directly from that tensor with `std.dim`.
This lowering pattern circumvents the necessity to materialize the shape in
memory.
Differential Revision: https://reviews.llvm.org/D82644
The error message in the `std.constant` verifier for function-typed constants
had the name of the undefined function hardcoded to `bar`. Report the actual
name instead.
Differential Revision: https://reviews.llvm.org/D82666
This test largely predates MLIR testing guidelines. Update it to match the
guidelines. In particular, avoid pattern-matching SSA value names, avoid
unnecessary CHECK-NEXT, relax assumptions about the form of SSA names.
Value-returning operations are still matched agaist _any_ name in order to
check that the operation indeed produces values.
Differential Revision: https://reviews.llvm.org/D82656
Rationale:
In general, passing "fastmath" from MLIR to LLVM backend is not supported, and even just providing such a feature for experimentation is under debate. However, passing fine-grained fastmath related attributes on individual operations is generally accepted. This CL introduces an option to instruct the vector-to-llvm lowering phase to annotate floating-point reductions with the "reassociate" fastmath attribute, which allows the LLVM backend to use SIMD implementations for such constructs. Oher lowering passes can start using this mechanism right away in cases where reassociation is allowed.
Benefit:
For some microbenchmarks on x86-avx2, speedups over 20 were observed for longer vector (due to cleaner, spill-free and SIMD exploiting code).
Usage:
mlir-opt --convert-vector-to-llvm="reassociate-fp-reductions"
Reviewed By: ftynse, mehdi_amini
Differential Revision: https://reviews.llvm.org/D82624
To be able to have more meaningful performance out of workloadsi going through
the vulkan-runner we need to use buffers from GPU device memory as access to
system memory is significantly slower for GPU with dedicated memory. This adds
code to do a copy through staging buffer as GPU memory cannot always be mapped
on the host.
Differential Revision: https://reviews.llvm.org/D82504
Implemented conversion for `spv.BitReverse` and `spv.BitCount`. Since ODS
generates builders in a different way for LLVM dialect intrinsics, I
added attributes to build method in `DirectConversionPattern` class. The
tests for these ops are in `bitwise-ops-to-llvm.mlir`.
Differential Revision: https://reviews.llvm.org/D82286
Add a pass to rewrite sequential chains of `spirv::CompositeInsert`
operations into `spirv::CompositeConstruct` operations.
Reviewed By: antiagainst
Differential Revision: https://reviews.llvm.org/D82198
This patch add support for 'spv.CopyMemory'. The following changes are
introduced:
- 'CopyMemory' op is added to SPIRVOps.td.
- Custom parse and print methods are introduced.
- A few Roundtripping tests are added.
Differential Revision: https://reviews.llvm.org/D82384
Summary: The patch fixes an off by one error in the method collapseParallelLoops. It ensures the same normalized bound is used for the computation of the division and the remainder.
Reviewers: herhut
Reviewed By: herhut
Subscribers: mehdi_amini, rriddle, jpienaar, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, aartbik, liufengdb, stephenneuendorffer, Joonsoo, grosul1, Kayjukh, jurahul, msifontes
Tags: #mlir
Differential Revision: https://reviews.llvm.org/D82634
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
Using fully qualified names wherever possible avoids ambiguous class and function names. This is a follow-up to D82371.
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D82471
When there is a mix of affine load/store and non-affine operations (e.g. std.load, std.store),
affine-loop-fusion ignores the present of non-affine ops, thus changing the program semantics.
E.g. we have a program of three affine loops operating on the same memref in which one of them uses std.load and std.store, as follows.
```
affine.for
affine.store %1
affine.for
std.load %1
std.store %1
affine.for
affine.load %1
affine.store %1
```
affine-loop-fusion will produce the following result which changed the program semantics:
```
affine.for
std.load %1
std.store %1
affine.for
affine.store %1
affine.load %1
affine.store %1
```
This patch is to fix the above problem by checking non-affine users of the memref that are between the source and destination nodes of interest.
Differential Revision: https://reviews.llvm.org/D82158
Lower `shape.rank` to standard dialect.
A shape's size is the same as the extent of the first and only dimension of the
`tensor<?xindex>` it is represented by.
Differential Revision: https://reviews.llvm.org/D82080
Replace any `rank(shape_of(tensor))` that relies on a ranked tensor with the
corresponding constant `const_size`.
Differential Revision: https://reviews.llvm.org/D82077
Summary: The patch optimizes the tiling of parallel loops with static bounds if the number of loop iterations is an integer multiple of the tile size.
Reviewers: herhut, ftynse, bondhugula
Reviewed By: herhut, ftynse
Subscribers: bondhugula, mehdi_amini, rriddle, jpienaar, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, aartbik, liufengdb, stephenneuendorffer, Joonsoo, grosul1, frgossen, Kayjukh, jurahul, msifontes
Tags: #mlir
Differential Revision: https://reviews.llvm.org/D82003
This patch introduces conversion patterns for `spv.module` and `spv._module_end`.
SPIR-V module is converted into `ModuleOp`. This will play a role of enclosing
scope to LLVM ops. At the moment, SPIR-V module attributes (such as memory model,
etc) are ignored.
Differential Revision: https://reviews.llvm.org/D82468
This revision adds a new support header, InterfaceSupport, to contain various generic bits of functionality for implementing "Interfaces". Interfaces embody a mechanism for attaching concept-based polymorphism to a type system. With this refactoring a new InterfaceMap type is added to allow for efficient interface lookups without going through an indirect call. This should provide a decent performance speedup without changing the size of AbstractOperation.
In a future revision, this functionality will also be used to bring Interface like functionality to Attributes and Types.
Differential Revision: https://reviews.llvm.org/D81882
Note that this does not mean that check-mlir will run check-mlir-integration
tests for all configurations. You still need to do a set up with the flag
MLIR_INCLUDE_INTEGRATION_TESTS set to ON in order to activate the integration test.
Reviewed By: jpienaar
Differential Revision: https://reviews.llvm.org/D82413
Use vector compares for the 1-D case. This approach scales much better
than generating insertion operations, and exposes SIMD directly to backend.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D82402
Summary: The Pass class exists in both the mlir and the llvm namespaces. Use the fully qualified class name to avoid any ambiguities.
Reviewers: rriddle
Reviewed By: rriddle
Subscribers: mehdi_amini, jpienaar, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, aartbik, liufengdb, stephenneuendorffer, Joonsoo, grosul1, jurahul, msifontes
Tags: #mlir
Differential Revision: https://reviews.llvm.org/D82371
Introduced `llvm.intr.bitreverse` and `llvm.intr.ctpop` LLVM bit
intrinsics to LLVM dialect. These intrinsics help with SPIR-V to
LLVM conversion, allowing a direct mapping from `spv.BitReverse`
and `spv.BitCount` respectively. Tests are added to `roundtrip.mlir`
and `llvm-intrinsics.mlir`.
Differential Revision: https://reviews.llvm.org/D82285
This patch adds a new cli argument to the automation script to generate
a report of the current SPIRV spec instruction coverage. It dumps to the
standard output a YAML string with the coverage information.
Differential Revision: https://reviews.llvm.org/D82006
This patch provides an implementation for `spv.func` conversion. The pattern
is populated in a separate method added to the pass. At the moment, the type
signature conversion only includes the supported types. The conversion pattern
also matches SPIR-V function control attributes to LLVM function attributes.
Those are modelled as `passthrough` attributes in LLVM dialect. The following
mapping are used:
- None: no attributes passed
- Inline: `alwaysinline` seems to be the right equivalent (`inlinehint` is
semantically weaker in my opinion)
- DontInline: `noinline`
- Pure and Const: I think those can be modelled as `readonly` and `readnone`
attributes respectively.
Also, 2 patterns added for return ops conversion (`spv.Return` for void return
and `spv.ReturnValue` for a single value return).
Differential Revision: https://reviews.llvm.org/D81931
Add option to filter which op the OpDefinitionsGen run on. This enables having multiple ops together in the same TD file but generating different CC files for them (useful if one wants to use multiclasses or split out 1 dialect into multiple different libraries). There is probably more general query here (e.g., split out all ops that don't have a verify method, or that are commutative) but filtering based on op name (e.g., test.a_op) seemed a reasonable start and didn't require inventing a query specification mechanism here.
Differential Revision: https://reviews.llvm.org/D82319
Stephan Herhut