This patch takes the first step towards a more principled modeling of undefined behavior in MLIR as discussed in the following discourse threads:
1. https://discourse.llvm.org/t/semantics-modeling-undefined-behavior-and-side-effects/4812
2. https://discourse.llvm.org/t/rfc-mark-tensor-dim-and-memref-dim-as-side-effecting/65729
This patch in particular does the following:
1. Introduces a ConditionallySpeculatable OpInterface that dynamically determines whether an Operation can be speculated.
2. Re-defines `NoSideEffect` to allow undefined behavior, making it necessary but not sufficient for speculation. Also renames it to `NoMemoryEffect`.
3. Makes LICM respect the above semantics.
4. Changes all ops tagged with `NoSideEffect` today to additionally implement ConditionallySpeculatable and mark themselves as always speculatable. This combined trait is named `Pure`. This makes this change NFC.
For out of tree dialects:
1. Replace `NoSideEffect` with `Pure` if the operation does not have any memory effects, undefined behavior or infinite loops.
2. Replace `NoSideEffect` with `NoSideEffect` otherwise.
The next steps in this process are (I'm proposing to do these in upcoming patches):
1. Update operations like `tensor.dim`, `memref.dim`, `scf.for`, `affine.for` to implement a correct hook for `ConditionallySpeculatable`. I'm also happy to update ops in other dialects if the respective dialect owners would like to and can give me some pointers.
2. Update other passes that speculate operations to consult `ConditionallySpeculatable` in addition to `NoMemoryEffect`. I could not find any other than LICM on a quick skim, but I could have missed some.
3. Add some documentation / FAQs detailing the differences between side effects, undefined behavior, speculatabilty.
Reviewed By: rriddle, mehdi_amini
Differential Revision: https://reviews.llvm.org/D135505
Simplify the lowering of warp_execute_on_lane0 of scf.if by making the
logic more generic. Also remove the assumption that the most inner
dimension is the dimension distributed.
Differential Revision: https://reviews.llvm.org/D133826
This revision significantly improves and tests the broadcast behavior of vector.warp_execute_on_lane_0.
Previously, the implementation of the broadcast behavior of vector.warp_execute_on_lane_0
assumed that the broadcasted value was always of scalar type.
This is not necessarily the case.
Differential Revision: https://reviews.llvm.org/D133767
Running: `mlir-opt -test-vector-warp-distribute=rewrite-warp-ops-to-scf-if -canonicalize -verify-each=0`.
Prior to this revision, IR resembling the following would be produced:
```
%4 = "vector.load"(%3, %arg0) : (memref<1x32xf32, 3>, index) -> vector<1x1xf32>
```
This fails verification since it needs 2 indices to load but only 1 is provided.
Differential Revision: https://reviews.llvm.org/D133106
Prevent creating multiple output for the same Value when distributing
operations out of WarpExecuteOnLane0Op. This avoid creating combinatory
explosion of outputs.
Differential Revision: https://reviews.llvm.org/D129465
This revision avoids a crash in the 0-D case of distributing vector.transfer ops out of
vector.warp_execute_on_lane_0.
Due to the code complexity and lack of documentation, it took untangling the implementation
before realizing that the simple fix was to fail in the 0-D case.
The rewrite is still very useful to understand this code better.
Differential Revision: https://reviews.llvm.org/D128793
When creating a scf.for without argument a scf.yield is automatically
created. Make sure we don't create a second one.
Differential Revision: https://reviews.llvm.org/D128405
This aligns the SCF dialect file layout with the majority of the dialects.
Reviewed By: jpienaar
Differential Revision: https://reviews.llvm.org/D128049
Make the reduction distribution pattern more generic and remove layering
problem. The new pattern to distribute reduction is now independent of
GPU and takes a lamdba to decide how the distributed reduction should be
generated.
Differential Revision: https://reviews.llvm.org/D127867
Add a pattern to do ad hoc lowering of vector.reduction to a sequence of
warp shuffles. This allow distributing reduction on a warp for GPU targets.
Also add an execution test for warp reduction.
co-authored with @springerm
Differential Revision: https://reviews.llvm.org/D127176
Add patterns to propagate vector distribution and remove dead
arguments. This handles propagation for several vector operations.
recommit after minor bug fix.
Differential Revision: https://reviews.llvm.org/D127167
Add patterns to propagate vector distribution and remove dead
arguments. This handles propagation for several vector operations.
Differential Revision: https://reviews.llvm.org/D127167
Add pattern to hoist scalar code outside of warp distribute region as
those cannot be distributed and we would want to execute them on all
the lanes.
Add patterns to distribute transfer_write ops. Those operations can be
distributed in different ways and it is control by user.
Differential Revision: https://reviews.llvm.org/D127152
Add lowering of the vector.warp_execute_on_lane_0 into scf.if plus memory
transfer for the operands and yield values.
This also add an integration test running on GPU warp. The same tests can be
later re-used with different comment lines to tests distribution
transformations.
This is mostly from @springerm contribution.
Differential Revision: https://reviews.llvm.org/D125430
