The bufferization of the BConcrete dialect emits calls to Concrete
wrapper functions and casts all memrefs to ranked memrefs with dynamic
strides and an implicit identity layout map. The implicit identity map
does not allow for casts of memrefs with non-zero offsets, e.g.,
resulting from folding of memrefs related to intermediate results
passed as operands to the operation implemented by a wrapper.
Casting to memrefs symbolic offsets in the layout map (e.g.,
`[d0, d1, ...](s0, s1, ...) -> (d0 + s0, d1 + s1, ...)`) allows
for more flexibility, in particular this adds support for memrefs
with non-zero, constant offsets returned by operations generating
intermediate results.
For now what it works are only levelled ops with user parameters. (take a look to the tests)
Done:
- Add parameters to the fhe parameters to support CRT-based large integers
- Add command line options and tests options to allows the user to give those new parameters
- Update the dialects and pipeline to handle new fhe parameters for CRT-based large integers
- Update the client parameters and the client library to handle the CRT-based large integers
Todo:
- Plug the optimizer to compute the CRT-based large interger parameters
- Plug the pbs for the CRT-based large integer
Rebase to llvm-project at 3f81841474fe with a pending upstream patch
for arbitrary element types in linalg named operations.
Co-authored-by: Ayoub Benaissa <ayoub.benaissa@zama.ai>
This commit is introduced because python bindings for `tensor.from_elements` are not generated automatically. Previously, we overcame this with string manipulation, but with the latest version of the compiler, it became a problem. This commit should be reverted eventually. See https://discourse.llvm.org/t/cannot-create-tensor-from-elements-operation-from-python-bindings/4768 for the discussion in LLVM forums.
This commit rebases the compiler onto commit f69328049e9e from
llvm-project.
Changes:
* Use of the one-shot bufferizer for improved memory management
* A new pass `OneShotBufferizeDPSWrapper` that converts functions
returning tensors to destination-passing-style as required by the
one-shot bufferizer
* A new pass `LinalgGenericOpWithTensorsToLoopsPass` that converts
`linalg.generic` operations with value semantics to loop nests
* Rebase onto a fork of llvm-project at f69328049e9e with local
modifications to enable bufferization of `linalg.generic` operations
with value semantics
* Workaround for the absence of type propagation after type conversion
via extra patterns in all dialect conversion passes
* Printer, parser and verifier definitions moved from inline
declarations in ODS to the respective source files as required by
upstream changes
* New tests for functions with a large number of inputs
* Increase the number of allowed task inputs as required by new tests
* Use upstream function `mlir_configure_python_dev_packages()` to
locate Python development files for compatibility with various CMake
versions
Co-authored-by: Quentin Bourgerie <quentin.bourgerie@zama.ai>
Co-authored-by: Ayoub Benaissa <ayoub.benaissa@zama.ai>
Co-authored-by: Antoniu Pop <antoniu.pop@zama.ai>
