12 Commits

Author SHA1 Message Date
Shenghang Tsai
7610b13729
[MLIR] Split ExecutionEngine Initialization out of ctor into an explicit method call (#153524)
Retry landing https://github.com/llvm/llvm-project/pull/153373
## Major changes from previous attempt
- remove the test in CAPI because no existing tests in CAPI deal with
sanitizer exemptions
- update `mlir/docs/Dialects/GPU.md` to reflect the new behavior: load
GPU binary in global ctors, instead of loading them at call site.
- skip the test on Aarch64 since we have an issue with initialization there

---------

Co-authored-by: Mehdi Amini <joker.eph@gmail.com>
2025-08-17 23:07:24 +02:00
Mehdi Amini
bfd490e0cd
Revert "[MLIR] Split ExecutionEngine Initialization out of ctor into an explicit method call" (#153477)
Reverts llvm/llvm-project#153373

Sanitizer bot is broken
2025-08-13 19:43:04 +00:00
Shenghang Tsai
2f93693f76
[MLIR] Split ExecutionEngine Initialization out of ctor into an explicit method call (#153373)
This PR introduces a mechanism to defer JIT engine initialization,
enabling registration of required symbols before global constructor
execution.

## Problem

Modules containing `gpu.module` generate global constructors (e.g.,
kernel load/unload) that execute *during* engine creation. This can
force premature symbol resolution, causing failures when:
- Symbols are registered via `mlirExecutionEngineRegisterSymbol` *after*
creation
- Global constructors exist (even if not directly using unresolved
symbols, e.g., an external function declaration)
   - GPU modules introduce mandatory binary loading logic

## Usage
```c
// Create engine without initialization
MlirExecutionEngine jit = mlirExecutionEngineCreate(...);

// Register required symbols
mlirExecutionEngineRegisterSymbol(jit, ...);

// Explicitly initialize (runs global constructors)
mlirExecutionEngineInitialize(jit);
```

---------

Co-authored-by: Mehdi Amini <joker.eph@gmail.com>
2025-08-13 15:22:01 +02:00
Denys Shabalin
95c083f579 [mlir] Fix and test python bindings for dump_to_object_file
Reviewed By: ftynse

Differential Revision: https://reviews.llvm.org/D136334
2022-10-20 15:53:16 +02:00
Mehdi Amini
8f23296bcc Apply clang-tidy fixes for llvm-header-guard in MLIR (NFC)
Differential Revision: https://reviews.llvm.org/D117251
2022-01-13 23:14:06 +00:00
Tres Popp
106f307499 Rename MlirExecutionEngine lookup to lookupPacked
The purpose of the change is to make clear whether the user is
retrieving the original function or the wrapper function, in line with
the invoke commands. This new functionality is useful for users that
already have defined their own packed interface, so they do not want the
extra layer of indirection, or for users wanting to the look at the
resulting primary function rather than the wrapper function.

All locations, except the python bindings now have a `lookupPacked`
method that matches the original `lookup` functionality. `lookup`
still exists, but with new semantics.

- `lookup` returns the function with a given name. If `bool f(int,int)`
is compiled, `lookup` will return a reference to `bool(*f)(int,int)`.
- `lookupPacked` returns the packed wrapper of the function with the
given name. If `bool f(int,int)` is compiled, `lookupPacked` will return
`void(*mlir_f)(void**)`.

Differential Revision: https://reviews.llvm.org/D114352
2021-11-22 14:12:09 +01:00
Uday Bondhugula
c8b8e8e022 [MLIR] Execution engine python binding support for shared libraries
Add support to Python bindings for the MLIR execution engine to load a
specified list of shared libraries - for eg. to use MLIR runtime
utility libraries.

Differential Revision: https://reviews.llvm.org/D104009
2021-06-12 05:46:38 +05:30
Uday Bondhugula
185ce8cdfc [MLIR][PYTHON] Provide opt level for ExecutionEngine Python binding
Provide an option to specify optimization level when creating an
ExecutionEngine via the MLIR JIT Python binding. Not only is the
specified optimization level used for code generation, but all LLVM
optimization passes at the optimization level are also run prior to
machine code generation (akin to the mlir-cpu-runner tool).

Default opt level continues to remain at level two (-O2).

Contributions in part from Prashant Kumar <prashantk@polymagelabs.com>
as well.

Differential Revision: https://reviews.llvm.org/D102551
2021-05-16 13:58:49 +05:30
Nicolas Vasilache
1dc533cea4 [mlir][python] ExecutionEngine can dump to object file
Differential Revision: https://reviews.llvm.org/D100786
2021-04-19 19:33:27 +00:00
Mehdi Amini
7a4d630764 Add a "register_runtime" method to the mlir.execution_engine and show calling back from MLIR into Python
This exposes the ability to register Python functions with the JIT and
exposes them to the MLIR jitted code. The provided test case illustrates
the mechanism.

Differential Revision: https://reviews.llvm.org/D99562
2021-03-30 17:04:38 +00:00
Mehdi Amini
13cb431719 Add basic JIT Python Bindings
This offers the ability to create a JIT and invoke a function by passing
ctypes pointers to the argument and the result.

Differential Revision: https://reviews.llvm.org/D97523
2021-03-03 18:19:40 +00:00
Mehdi Amini
86c8a7857d Add C bindings for mlir::ExecutionEngine
This adds minimalistic bindings for the execution engine, allowing to
invoke the JIT from the C API. This is still quite early and
experimental and shouldn't be considered stable in any way.

Differential Revision: https://reviews.llvm.org/D96651
2021-03-03 18:19:40 +00:00