6 Commits

Author SHA1 Message Date
donald chen
4b3f251bad
[mlir] [dataflow] unify semantics of program point (#110344)
The concept of a 'program point' in the original data flow framework is
ambiguous. It can refer to either an operation or a block itself. This
representation has different interpretations in forward and backward
data-flow analysis. In forward data-flow analysis, the program point of
an operation represents the state after the operation, while in backward
data flow analysis, it represents the state before the operation. When
using forward or backward data-flow analysis, it is crucial to carefully
handle this distinction to ensure correctness.

This patch refactors the definition of program point, unifying the
interpretation of program points in both forward and backward data-flow
analysis.

How to integrate this patch?

For dense forward data-flow analysis and other analysis (except dense
backward data-flow analysis), the program point corresponding to the
original operation can be obtained by `getProgramPointAfter(op)`, and
the program point corresponding to the original block can be obtained by
`getProgramPointBefore(block)`.

For dense backward data-flow analysis, the program point corresponding
to the original operation can be obtained by
`getProgramPointBefore(op)`, and the program point corresponding to the
original block can be obtained by `getProgramPointAfter(block)`.

NOTE: If you need to get the lattice of other data-flow analyses in
dense backward data-flow analysis, you should still use the dense
forward data-flow approach. For example, to get the Executable state of
a block in dense backward data-flow analysis and add the dependency of
the current operation, you should write:

``getOrCreateFor<Executable>(getProgramPointBefore(op),
getProgramPointBefore(block))``

In case above, we use getProgramPointBefore(op) because the analysis we
rely on is dense backward data-flow, and we use
getProgramPointBefore(block) because the lattice we query is the result
of a non-dense backward data flow computation.

related dsscussion:
https://discourse.llvm.org/t/rfc-unify-the-semantics-of-program-points/80671/8
corresponding PSA:
https://discourse.llvm.org/t/psa-program-point-semantics-change/81479
2024-10-11 21:59:05 +08:00
Ivan Butygin
15e915a44f
[mlir][dataflow] Propagate errors from visitOperation (#105448)
Base `DataFlowAnalysis::visit` returns `LogicalResult`, but wrappers's
Sparse/Dense/Forward/Backward `visitOperation` doesn't.

Sometimes it's needed to abort solver early if some unrecoverable
condition detected inside analysis.

Update `visitOperation` to return `LogicalResult` and propagate it to
`solver.initializeAndRun()`. Only `visitOperation` is updated for now,
it's possible to update other hooks like `visitNonControlFlowArguments`,
bit it's not needed immediately and let's keep this PR small.

Hijacked `UnderlyingValueAnalysis` test analysis to test it.
2024-08-22 12:16:03 +03:00
Jeff Niu
e95e94adc6
[mlir][test] Reorganize the test dialect (#89424)
This PR massively reorganizes the Test dialect's source files. It moves
manually-written op hooks into `TestOpDefs.cpp`, moves format custom
directive parsers and printers into `TestFormatUtils`, adds missing
comment blocks, and moves around where generated source files are
included for types, attributes, enums, etc. into their own source file.

This will hopefully help navigate the test dialect source code, but also
speeds up compile time of the test dialect by putting generated source
files into separate compilation units.

This also sets up the test dialect to shard its op definitions, done in
the next PR.
2024-04-22 13:42:05 -07:00
Oleksandr "Alex" Zinenko
32a4e3fcca
[mlir] support non-interprocedural dataflow analyses (#75583)
The core implementation of the dataflow anlysis framework is
interpocedural by design. While this offers better analysis precision,
it also comes with additional cost as it takes longer for the analysis
to reach the fixpoint state. Add a configuration mechanism to the
dataflow solver to control whether it operates inteprocedurally or not
to offer clients a choice.

As a positive side effect, this change also adds hooks for explicitly
processing external/opaque function calls in the dataflow analyses,
e.g., based off of attributes present in the the function declaration or
call operation such as alias scopes and modref available in the LLVM
dialect.

This change should not affect existing analyses and the default solver
configuration remains interprocedural.

Co-authored-by: Jacob Peng <jacobmpeng@gmail.com>
2023-12-18 14:16:52 +01:00
vic
a9d0f5e2f0
[mlir] Allow loop-like operations in AbstractDenseForwardDataFlowAnalysis (#66179)
Remove assertion violated by loop-like operations.

Signed-off-by: Victor Perez <victor.perez@codeplay.com>
2023-09-14 10:30:40 +02:00
Alex Zinenko
b2b7efb96d [mlir] NFC: rename XDataFlowAnalysis to XForwardDataFlowAnalysis
This makes naming consisnt with XBackwardDataFlowAnalysis.

Reviewed By: Mogball, phisiart

Differential Revision: https://reviews.llvm.org/D155930
2023-07-27 11:11:40 +00:00