This relies on the existing TileAndFuse pattern for tensor-based structured
ops. It complements pure tiling, from which some utilities are generalized.
Depends On D127300
Reviewed By: springerm
Differential Revision: https://reviews.llvm.org/D127319
Introduce transform ops for "for" loops, in particular for peeling, software
pipelining and unrolling, along with a couple of "IR navigation" ops. These ops
are intended to be generalized to different kinds of loops when possible and
therefore use the "loop" prefix. They currently live in the SCF dialect as
there is no clear place to put transform ops that may span across several
dialects, this decision is postponed until the ops actually need to handle
non-SCF loops.
Additionally refactor some common utilities for transform ops into trait or
interface methods, and change the loop pipelining to be a returning pattern.
Reviewed By: springerm
Differential Revision: https://reviews.llvm.org/D127300
These ops complement the tiling/padding transformations by transforming
higher-level named structured operations such as depthwise convolutions into
lower-level and/or generic equivalents that are better handled by some
downstream transformations.
Differential Revision: https://reviews.llvm.org/D126698
Vectorization is a key transformation to achieve high performance on most
architectures. In the transform dialect, vectorization is implemented as a
parameterizable transform op. It currently applies to a scope of payload IR
delimited by some isolated-from-above op, mainly because several enabling
transformations (such as affine simplification) are needed to perform
vectorization and these transformation would apply to ops other than the "main"
computational payload op. A separate "navigation" transform op that obtains the
isolated-from-above ancestor of an op is introduced in the core transform
dialect. Even though it is currently only useful for vectorization,
isolated-from-above ops are a common anchor for transformations (usually
implemented as passes) that is likely to be reused in the future.
Depends On D126374
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D126542
Add ops to the structured transform extension of the transform dialect that
perform interchange, padding and scalarization on structured ops. Along with
tiling that is already defined, this provides a minimal set of transformations
necessary to build vectorizable code for a single structured op.
Define two helper traits: one that implements TransformOpInterface by applying
a function to each payload op independently and another that provides a simple
"functional-style" producer/consumer list of memory effects for the transform
ops.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D126374
There are a lot of cases where we accidentally ignored the result of some
parsing hook. Mark ParseResult as LLVM_NODISCARD just like ParseResult is.
This exposed some stuff to clean up, so do.
Differential Revision: https://reviews.llvm.org/D125549
