This reverts commit 4986d5eaff with
proper patches to CMakeLists.txt:
- Add MLIRAsync as a dependency to MLIRAsyncToLLVM
- Add Coroutines as a dependency to MLIRExecutionEngine
Lower from Async dialect to LLVM by converting async regions attached to `async.execute` operations into LLVM coroutines (https://llvm.org/docs/Coroutines.html):
1. Outline all async regions to functions
2. Add LLVM coro intrinsics to mark coroutine begin/end
3. Use MLIR conversion framework to convert all remaining async types and ops to LLVM + Async runtime function calls
All `async.await` operations inside async regions converted to coroutine suspension points. Await operation outside of a coroutine converted to the blocking wait operations.
Implement simple runtime to support concurrent execution of coroutines.
Reviewed By: herhut
Differential Revision: https://reviews.llvm.org/D89292
Many LLVM transformations benefits from knowing the targets. This enables optimizations,
especially in a JIT context when the target is (generally) well-known.
Closestensorflow/mlir#49
PiperOrigin-RevId: 261840617
Original implementation of OutUtils provided two different LLVM IR module
transformers to be used with the MLIR ExecutionEngine: OptimizingTransformer
parameterized by the optimization levels (similar to -O3 flags) and
LLVMPassesTransformer parameterized by the string formatted similarly to
command line options of LLVM's "opt" tool without support for -O* flags.
Introduce such support by declaring the flags inside the parser and by
populating the pass managers similarly to what "opt" does. Remove the
additional flags from mlir-cpu-runner as they can now be wrapped into
`-llvm-opts` together with other LLVM-related flags.
PiperOrigin-RevId: 236107292
A recent change introduced a possibility to run LLVM IR transformation during
JIT-compilation in the ExecutionEngine. Provide helper functions that
construct IR transformers given either clang-style optimization levels or a
list passes to run. The latter wraps the LLVM command line option parser to
parse strings rather than actual command line arguments. As a result, we can
run either of
mlir-cpu-runner -O3 input.mlir
mlir-cpu-runner -some-mlir-pass -llvm-opts="-llvm-pass -other-llvm-pass"
to combine different transformations. The transformer builder functions are
provided as a separate library that depends on LLVM pass libraries unlike the
main execution engine library. The library can be used for integrating MLIR
execution engine into external frameworks.
PiperOrigin-RevId: 234173493
Lei Zhang