Summary: This revision adds support to the declarative parser for formatting enum attributes in the symbolized form. It uses this new functionality to port several of the SPIRV parsers over to the declarative form.
Differential Revision: https://reviews.llvm.org/D74525
Summary:
This sets the basic framework for lowering vector.contract progressively
into simpler vector.contract operations until a direct vector.reduction
operation is reached. More details will be filled out progressively as well.
Reviewers: nicolasvasilache
Reviewed By: nicolasvasilache
Subscribers: mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, liufengdb, Joonsoo, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D74520
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 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
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
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:
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 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 initial implementation of the fusion operation exposes a method to
fuse a consumer with its producer, when
- both the producer and consumer operate on tensors
- the producer has only a single result value
- the producer has only "parallel" iterator types
A new interface method hasTensorSemantics is added to verify that an
operation has all operands and results of type RankedTensorType.
Differential Revision: https://reviews.llvm.org/D74172
Summary:
Previously, vector.contract did not allow an empty set of
free or batch dimensions (K = 0) which defines a basic
reduction into a scalar (like a dot product). This CL
relaxes that restriction. Also adds constraints on
element type of operands and results. With tests.
Reviewers: nicolasvasilache, andydavis1, rriddle
Reviewed By: andydavis1
Subscribers: merge_guards_bot, mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, liufengdb, Joonsoo, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D74014
Summary:
[mlir][VectorOps] Support vector transfer_read/write unrolling for memrefs with vector element type. When unrolling vector transfer read/write on memrefs with vector element type, the indices used to index the memref argument must be updated to reflect the unrolled operation. However, in the case of memrefs with vector element type, we need to be careful to only update the relevant memref indices.
For example, a vector transfer read with the following source/result types, memref<6x2x1xvector<2x4xf32>>, vector<2x1x2x4xf32>, should only update memref indices 1 and 2 during unrolling.
Reviewers: nicolasvasilache, aartbik
Reviewed By: nicolasvasilache, aartbik
Subscribers: lebedev.ri, Joonsoo, merge_guards_bot, mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, arpith-jacob, mgester, lucyrfox, liufengdb, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D72965
Summary:
Add ShapeCastOp to the vector ops dialect.
The shape_cast operation casts between an n-D source vector shape and a k-D result vector shape (the element type remains the same).
Reviewers: nicolasvasilache, aartbik
Reviewed By: nicolasvasilache
Subscribers: Joonsoo, merge_guards_bot, mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, arpith-jacob, mgester, lucyrfox, liufengdb, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D73635
Summary:
MLIRAnalysis depended on MLIRVectorOps
MLIRVectorOps depended on MLIRAnalysis for Loop information.
Both of these can be solved by factoring out libraries related to loop
analysis into their own library. The new MLIRLoopAnalysis might be
better off with the Loop Dialect in the future.
Reviewers: nicolasvasilache, rriddle!, mehdi_amini
Reviewed By: mehdi_amini
Subscribers: Joonsoo, vchuravy, merge_guards_bot, mgorny, mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, arpith-jacob, mgester, lucyrfox, aartbik, liufengdb, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D73655
Summary:
It is often needed to map entire ranges rather than single values. To avoid
writing the same for loop every time, I have added an overload to the map
method.
Differential Revision: https://reviews.llvm.org/D73894
We were using normal dictionary attribute for target environment
specification. It becomes cumbersome with more and more fields.
This commit changes the modelling to a dialect-specific attribute,
where we can have control over its storage and assembly form.
Differential Revision: https://reviews.llvm.org/D73959
Summary:
This patch is a step towards enabling BUILD_SHARED_LIBS=on, which
builds most libraries as DLLs instead of statically linked libraries.
The main effect of this is that incremental build times are greatly
reduced, since usually only one library need be relinked in response
to isolated code changes.
The bulk of this patch is fixing incorrect usage of cmake, where library
dependencies are listed under add_dependencies rather than under
target_link_libraries or under the LINK_LIBS tag. Correct usage should be
like this:
add_dependencies(MLIRfoo MLIRfooIncGen)
target_link_libraries(MLIRfoo MLIRlib1 MLIRlib2)
A separate issue is that in cmake, dependencies between static libraries
are automatically included in dependencies. In the above example, if MLIBlib1
depends on MLIRlib2, then it is sufficient to have only MLIRlib1 in the
target_link_libraries. When compiling with shared libraries, it is necessary
to have both MLIRlib1 and MLIRlib2 specified if MLIRfoo uses symbols from both.
Reviewers: mravishankar, antiagainst, nicolasvasilache, vchuravy, inouehrs, mehdi_amini, jdoerfert
Reviewed By: nicolasvasilache, mehdi_amini
Subscribers: Joonsoo, merge_guards_bot, jholewinski, mgorny, mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, csigg, arpith-jacob, mgester, lucyrfox, herhut, aartbik, liufengdb, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D73653
This commit adds two resource limits, max_compute_workgroup_size
and max_compute_workgroup_invocations as resource limits to
the target environment. They are not used at the current moment,
but they will affect the SPIR-V CodeGen. Adding for now to have
a proper target environment modelling.
Differential Revision: https://reviews.llvm.org/D73905
Summary: This revision add support for accepting a few type constraints, e.g. AllTypesMatch, when inferring types for operands and results. This is used to remove the c++ parsers for several additional operations.
Differential Revision: https://reviews.llvm.org/D73735
Summary:
Replace the generic zero- and one-result builders in LLVM::CallOp with a custom
builder that takes an LLVMFuncOp, which can be used to extract the result type
and create the symbol reference attribute. This is merely a convenience for
upcoming changes. The ODS-generated builders remain present.
Introduce LLVM::LLVMType::isVoidTy by analogy with the underlying LLVM type.
Differential Revision: https://reviews.llvm.org/D73895
LinalgDependenceGraph was not updated after successful producer-consumer
fusion for linalg ops. In this patch it is fixed by reconstructing
LinalgDependenceGraph on every iteration. This is very ineffective and
should be improved by updating LDGraph only when it is necessary.
Summary:
In the original design, gpu.launch required explicit capture of uses
and passing them as operands to the gpu.launch operation. This was
motivated by infrastructure restrictions rather than design. This
change lifts the requirement and removes the concept of kernel
arguments from gpu.launch. Instead, the kernel outlining
transformation now does the explicit capturing.
This is a breaking change for users of gpu.launch.
Differential Revision: https://reviews.llvm.org/D73769
Summary:
After the `subview` operation was migrated from Linalg to Standard, it changed
semantics and does not guarantee the absence of out-of-bounds accesses through
the created view anymore. Compute the size of the subview to make sure it
always fits within the view (subviews in last iterations of the loops may be
smaller than those in other iterations).
Differential Revision: https://reviews.llvm.org/D73614
This commit adds a pattern to lower linalg.generic for reduction
to spv.GroupNonUniform* ops. Right now this only supports integer
reduction on 1-D input memref. Shader entry point ABI is queried
to make sure that the input memref's shape matches the local
workgroup's invocation configuration. This makes sure that the
workload fits in one local workgroup so that we can leverage
SPIR-V group non-uniform operations.
linglg.generic is a structured op that preserves the right level
of information. It is easier to recognize reduction at this level
than performing analysis on loops.
This commit also exposes `getElementPtr` in SPIRVLowering.h given
that it's a generally useful utility function.
Differential Revision: https://reviews.llvm.org/D73437
The refactored MemRefType::get() calls all intend to clone from another
memref type, with some modifications. In fact, some calls dropped memory space
during the cloning. Migrate them to the cloning API so that nothing gets
dropped if they are not explicitly listed.
It's close to NFC but not quite, as it helps with propagating memory spaces in
some places.
Differential Revision: https://reviews.llvm.org/D73296
Uday Bondhugula