Currently, in the MLIR `{Sparse,Dense}DataFlowAnalysis` API, there is a small optimization:
Before running a transfer function, if the "out state" is already at the pessimistic fixpoint (bottom lattice value), then we know that it cannot possibly be changed, therefore we can skip the transfer function.
I benchmarked and found that this optimization is ineffective, so we can remove it and simplify `{Sparse,Dense}DataFlowAnalysis`. In a subsequent patch, I plan to change/remove the concept of the pessimistic fixpoint so that the API is further simplified.
Benchmark: I ran the following tests 5 times (after 3 warmup runs), and timed the `initializeAndRun()` function.
| Test | Before (us) | After (us) |
| mlir-opt -test-dead-code-analysis mlir/test/Analysis/DataFlow/test-dead-code-analysis.mlir | 181.2536 | 187.7074 |
| mlir-opt -- -test-dead-code-analysis mlir/test/Analysis/DataFlow/test-last-modified-callgraph.mlir | 109.5504 | 105.0654 |
| mlir-opt -- -test-dead-code-analysis mlir/test/Analysis/DataFlow/test-last-modified.mlir | 333.3646 | 322.4224 |
| mlir-opt -- -allow-unregistered-dialect -sccp mlir/test/Analysis/DataFlow/test-combined-sccp.mlir | 1027.1492 | 1081.818 |
Note: `test-combined-sccp.mlir` is crafted by combining `mlir/test/Transforms/sccp.mlir`, `mlir/test/Transforms/sccp-structured.mlir` and `mlir/test/Transforms/sccp-callgraph.mlir`.
Reviewed By: aartbik, Mogball
Differential Revision: https://reviews.llvm.org/D131660
This patch introduces an implementation of dense data-flow analysis. Dense
data-flow analysis attaches a lattice before and after the execution of every
operation. The lattice state is propagated across operations by a user-defined
transfer function. The state is joined across control-flow and callgraph edges.
Thge patch provides an example pass that uses both a dense and a sparse analysis
together.
Depends on D127139
Reviewed By: rriddle, phisiart
Differential Revision: https://reviews.llvm.org/D127173
