Summary:
To unblock other work, this implements basic lowering based on mapping
attributes that have to be provided on all loop.parallel. The lowering
does not yet support reduce.
Differential Revision: https://reviews.llvm.org/D73893
Summary:
On some platforms the build fails "std::function is not found". The include is used in
PassManager::IRPrinterConfig::enableIRPrinting.
Differential Revision: https://reviews.llvm.org/D74469
In code generators, one can automate the translation of typed ArrayAttrs
if element attribute translators are already implemented. However, the
type of the element attribute is lost at the construction of
TypedArrayAttrBase. With this change one can inspect the element type
and generate the translation logic automatically, which will reduce the
code repetition.
Differential Revision: https://reviews.llvm.org/D73579
Summary:
As discussed in https://llvm.discourse.group/t/rfc-add-affine-parallel/350, this is the first in a series of patches to bring in support for the `affine.parallel` operation.
This first patch adds the IR representation along with custom printer/parser implementations.
Reviewers: bondhugula, herhut, mehdi_amini, nicolasvasilache, rriddle, earhart, jbruestle
Reviewed By: bondhugula, nicolasvasilache, rriddle, earhart, jbruestle
Subscribers: jpienaar, burmako, shauheen, antiagainst, arpith-jacob, mgester, lucyrfox, aartbik, liufengdb, Joonsoo, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D74288
This patch adapts the method MemRefDescriptor::fromStaticShape to
support static non-zero offsets. The updated method uses the
getStridesAndOffset method to extract strides and offset. The patch also
adapts the test cases since sizes and strides are now set in forward
instead of reverse order.
Differential Revision: https://reviews.llvm.org/D74474
This revision prepares the ground for declaratively defining Linalg "named" ops.
Such named ops form the backbone of operations that are ubiquitous in the ML
application domain.
This revision closely related to the definition of a "Tensor Computation
Primitives Dialect" and demonstrates that ops can be expressed as declarative
configurations of the `linalg.generic` op.
Differential Revision: https://reviews.llvm.org/D74491
Summary:
This revision allows model builder to create a linalg_matmul whose body
is a vector.contract. This shows the abstractions compose nicely.
Differential Revision: https://reviews.llvm.org/D74457
Summary: This was a missed case when ValueRange was originally added, and allows for constructing a ValueRange from the arguments of a block.
Differential Revision: https://reviews.llvm.org/D74363
A memref_cast casting to a memref with a non identity map can't be
lowered to llvm. Take the following case:
```
func @invalid_memref_cast(%arg0: memref<?x?xf64>) {
%c1 = constant 1 : index
%c0 = constant 0 : index
%5 = memref_cast %arg0 : memref<?x?xf64> to memref<?x?xf64, #map1>
%25 = std.subview %5[%c0, %c0][%c1, %c1][] : memref<?x?xf64, #map1> to memref<?x?xf64, #map1>
return
}
```
When lowering the subview mlir was assuming `%5` to have an llvm type
(which is not the case as mlir failed to lower the memref_cast).
Differential Revision: https://reviews.llvm.org/D74466
Summary:
This was broken recently when moving from dialect registration via
static initializers to explicit intialization.
Differential Revision: https://reviews.llvm.org/D74480
Thus far we have been using builtin func op to model SPIR-V functions.
It was because builtin func op used to have special treatment in
various parts of the core codebase (e.g., pass pipelines, etc.) and
it's easy to bootstrap the development of the SPIR-V dialect. But
nowadays with general op concepts and region support we don't have
such limitations and it's time to tighten the SPIR-V dialect for
completeness.
This commits introduces a spv.func op to properly model SPIR-V
functions. Compared to builtin func op, it can provide the following
benefits:
* We can control the full op so we can integrate SPIR-V information
bits (e.g., function control) in a more integrated way and define
our own assembly form and enforcing better verification.
* We can have a better dialect and library boundary. At the current
moment only functions are modelled with an external op. With this
change, all ops modelling SPIR-V concpets will be spv.* ops and
registered to the SPIR-V dialect.
* We don't need to special-case func op anymore when creating
ConversionTarget declaring SPIR-V dialect as legal. This is quite
important given we'll see more and more conversions in the future.
In the process, bumps a few FuncOp methods to the FunctionLike trait.
Differential Revision: https://reviews.llvm.org/D74226
In the previous state, we were relying on forcing the linker to include
all libraries in the final binary and the global initializer to self-register
every piece of the system. This change help moving away from this model, and
allow users to compose pieces more freely. The current change is only "fixing"
the dialect registration and avoiding relying on "whole link" for the passes.
The translation is still relying on the global registry, and some refactoring
is needed to make this all more convenient.
Differential Revision: https://reviews.llvm.org/D74461
* Rename CMake target MLIROptMain to MLIROptLib:
The target provides the main library
* Rename CMake target MLIRMlirOptLib to MLIRMlirOptMain:
The target provides the main() entry function
At the moment, the Bazel configuration of TenorFlow maps the target
MlirOptLib to "lib/Support/MlirOptMain.cpp" and MlirOptMain to
"tools/mlir-opt/mlir-opt.cpp". This is the other way around in the CMake
configuration. As discussed in the context of the pull request
https://github.com/tensorflow/tensorflow/pull/36301, it seems useful to
revise the naming in the MLIR repo.
Differential Revision: https://reviews.llvm.org/D73778
Summary:
Adds affine loop fusion transformation function to LoopFusionUtils.
Updates TestLoopFusion utility to run loop fusion transformation until a fixed point is reached.
Adds unit tests to test the transformation.
Includes ASAN bug fix for D73190.
Reviewers: bondhugula, dcaballe
Reviewed By: bondhugula, dcaballe
Subscribers: mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, aartbik, liufengdb, Joonsoo, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D74330
Follow-up on D72802. Turn -convert-std-to-llvm-use-alloca and
-convert-std-to-llvm-bare-ptr-memref-call-conv into pass flags
of LLVMLoweringPass.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D73912
Defines a tablegen class RankedIntElementsAttr. This is an integer
version of RankedFloatElementsAttr.
Differential Revision: https://reviews.llvm.org/D73764
Summary:
The lowering to NVVM and ROCm handles tanh operations differently by
mapping them to NVVM/ROCm specific intrinsics. This conflicts with
the lowering to LLVM, which uses the default llvm intrinsic. This change
declares the LLVM intrinsics to be illegal, hence disallowing the
correspondign rewrite.
Differential Revision: https://reviews.llvm.org/D74389
We have spv.entry_point_abi for specifying the local workgroup size.
It should be decorated onto input gpu.func ops to drive the SPIR-V
CodeGen to generate the proper SPIR-V module execution mode. Compared
to using command-line options for specifying the configuration, using
attributes also has the benefits that 1) we are now able to use
different local workgroup for different entry points and 2) the
tests contains the configuration directly.
Differential Revision: https://reviews.llvm.org/D74012
Summary:
After D72555 has been landed, `linalg.indexed_generic` also accepts ranked
tensor as input and output. Add a test for it.
Differential Revision: https://reviews.llvm.org/D74267
Summary:
This revision adds EDSC support for VectorOps to enable the creation of a `vector_matmul` declaratively. The `vector_matmul` is a simple configuration
of the `vector.contract` op that follows the StructuredOps abstraction.
Differential Revision: https://reviews.llvm.org/D74284
This CL refactors EDSCs to layer them better and break unnecessary
dependencies. After this refactoring, the top-level EDSC target only
depends on IR but not on Dialects anymore and each dialect has its
own EDSC directory.
This simplifies the layering and breaks cyclic dependencies.
In particular, the declarative builder + folder are made explicit and
are now confined to Linalg.
As the refactoring occurred, certain classes and abstractions that were not
paying for themselves have been removed.
Differential Revision: https://reviews.llvm.org/D74302
The current standard to llvm conversion pass lowers subview ops only if
dynamic offsets are provided. This commit extends the lowering with a
code path that uses the constant offset of the target memref for the
subview op lowering (see Example 3 of the subview op definition for an
example) if no dynamic offsets are provided.
Differential Revision: https://reviews.llvm.org/D74280
The existing (default) calling convention for memrefs in standard-to-LLVM
conversion was motivated by interfacing with LLVM IR produced from C sources.
In particular, it passes a pointer to the memref descriptor structure when
calling the function. Therefore, the descriptor is allocated on stack before
the call. This convention leads to several problems. PR44644 indicates a
problem with stack exhaustion when calling functions with memref-typed
arguments in a loop. Allocating outside of the loop may lead to concurrent
access problems in case the loop is parallel. When targeting GPUs, the contents
of the stack-allocated memory for the descriptor (passed by pointer) needs to
be explicitly copied to the device. Using an aggregate type makes it impossible
to attach pointer-specific argument attributes pertaining to alignment and
aliasing in the LLVM dialect.
Change the default calling convention for memrefs in standard-to-LLVM
conversion to transform a memref into a list of arguments, each of primitive
type, that are comprised in the memref descriptor. This avoids stack allocation
for ranked memrefs (and thus stack exhaustion and potential concurrent access
problems) and simplifies the device function invocation on GPUs.
Provide an option in the standard-to-LLVM conversion to generate auxiliary
wrapper function with the same interface as the previous calling convention,
compatible with LLVM IR porduced from C sources. These auxiliary functions
pack the individual values into a descriptor structure or unpack it. They also
handle descriptor stack allocation if necessary, serving as an allocation
scope: the memory reserved by `alloca` will be freed on exiting the auxiliary
function.
The effect of this change on MLIR-generated only LLVM IR is minimal. When
interfacing MLIR-generated LLVM IR with C-generated LLVM IR, the integration
only needs to require auxiliary functions and change the function name to call
the wrapper function instead of the original function.
This also opens the door to forwarding aliasing and alignment information from
memrefs to LLVM IR pointers in the standrd-to-LLVM conversion.
The existing lowering of gpu.block_dim added a global variable with
the WorkGroupSize decoration. This raises an error within
Vulkan/SPIR-V validation since Vulkan requires this to have a constant
initializer. This is not yet supported in SPIR-V dialect. Changing the
lowering to return the workgroup size as a constant value instead,
obtained from spv.entry_point_abi attribute gets around the issue for
now. The validation goes through since the workgroup size is specified
using spv.execution_mode operation.
This revision adds support in the declarative assembly form for printing attributes with buildable types without the type, and moves several more parsers over to the declarative form.
Differential Revision: https://reviews.llvm.org/D74276
Summary:
This revision adds a utility to generate debug locations from the IR during compilation, by snapshotting to a output stream and using the locations that operations were dumped in that stream. The new locations may either;
* Replace the original location of the operation.
old:
loc("original_source.cpp":1:1)
new:
loc("snapshot_source.mlir":10:10)
* Fuse with the original locations as NamedLocs with a specific tag.
old:
loc("original_source.cpp":1:1)
new:
loc(fused["original_source.cpp":1:1, "snapshot"("snapshot_source.mlir":10:10)])
This feature may be used by a debugger to display the code at various different levels of the IR. It would also be able to show the different levels of IR attached to a specific source line in the original source file.
This feature may also be used to generate locations for operations generated during compilation, that don't necessarily have a user source location to attach to.
This requires changes in the printer to track the locations of operations emitted in the stream. Moving forward we need to properly(and efficiently) track the number of newlines emitted to the stream during printing.
Differential Revision: https://reviews.llvm.org/D74019
Stephan Herhut