[MLIR][affine] Illegal affine loop fusion with vector types

[dragondracarys007]

Hi, I was playing around with affine fusion with affine.vector_load/store operations inside loop and came across this particular case:

`func.func @main(%a: memref<64x512xf32>, %b: memref<64x512xf32>, %c: memref<64x512xf32>, %d: memref<64x4096xf32>, %e: memref<64x4096xf32>) {

affine.for %j = 0 to 8 {
    %lhs = affine.vector_load %a[0, %j * 64] : memref<64x512xf32>, vector<64x64xf32>
    %rhs = affine.vector_load %b[0, %j * 64] : memref<64x512xf32>, vector<64x64xf32>
    %res = arith.addf %lhs, %rhs : vector<64x64xf32>
    affine.vector_store %res, %c[0, %j * 64] : memref<64x512xf32>, vector<64x64xf32>
}

affine.for %j = 0 to 8 {
    %lhs = affine.vector_load %c[0, 0] : memref<64x512xf32>, vector<64x512xf32>
    %rhs = affine.vector_load %d[0, %j * 512] : memref<64x4096xf32>, vector<64x512xf32>
    %res = arith.subf %lhs, %rhs : vector<64x512xf32>
    affine.vector_store %res, %d[0, %j * 512] : memref<64x4096xf32>, vector<64x512xf32>
}

func.return

}`

Upon invoking affine-fusion on this IR with the following command:

mlir-opt --pass-pipeline='builtin.module(affine-loop-fusion)' test.mlir

I see that the loops are getting fused for the above case. Fusion here is illegal since 2nd loop can only be executed once 1st loop completely finishes all its iterations and produces the result to be consumed in 2nd loop. I'm attaching the llvm discourse thread here for further reading about the issue.

https://discourse.llvm.org/t/affine-fusion-legality-for-vector-types/83079

As per the discussion, we should have a bailout in the presence of different-sized element types in the producer/consumer validity checking.

[rhanqtl]

I'd like to work on a fix for this.

[llvmbot]

@llvm/issue-subscribers-mlir-affine

Author: None (dragondracarys007)

Hi, I was playing around with affine fusion with affine.vector_load/store operations inside loop and came across this particular case:

`func.func @main(%a: memref<64x512xf32>, %b: memref<64x512xf32>, %c: memref<64x512xf32>, %d: memref<64x4096xf32>, %e: memref<64x4096xf32>) {

affine.for %j = 0 to 8 {
    %lhs = affine.vector_load %a[0, %j * 64] : memref<64x512xf32>, vector<64x64xf32>
    %rhs = affine.vector_load %b[0, %j * 64] : memref<64x512xf32>, vector<64x64xf32>
    %res = arith.addf %lhs, %rhs : vector<64x64xf32>
    affine.vector_store %res, %c[0, %j * 64] : memref<64x512xf32>, vector<64x64xf32>
}

affine.for %j = 0 to 8 {
    %lhs = affine.vector_load %c[0, 0] : memref<64x512xf32>, vector<64x512xf32>
    %rhs = affine.vector_load %d[0, %j * 512] : memref<64x4096xf32>, vector<64x512xf32>
    %res = arith.subf %lhs, %rhs : vector<64x512xf32>
    affine.vector_store %res, %d[0, %j * 512] : memref<64x4096xf32>, vector<64x512xf32>
}

func.return

}`

Upon invoking affine-fusion on this IR with the following command:

mlir-opt --pass-pipeline='builtin.module(affine-loop-fusion)' test.mlir

I see that the loops are getting fused for the above case. Fusion here is illegal since 2nd loop can only be executed once 1st loop completely finishes all its iterations and produces the result to be consumed in 2nd loop. I'm attaching the llvm discourse thread here for further reading about the issue.

https://discourse.llvm.org/t/affine-fusion-legality-for-vector-types/83079

As per the discussion, we should have a bailout in the presence of different-sized element types in the producer/consumer validity checking.

[llvmbot]

Hi!

This issue may be a good introductory issue for people new to working on LLVM. If you would like to work on this issue, your first steps are:

1. Check that no other contributor has already been assigned to this issue. If you believe that no one is actually working on it despite an assignment, ping the person. After one week without a response, the assignee may be changed.
2. In the comments of this issue, request for it to be assigned to you, or just create a pull request after following the steps below. Mention this issue in the description of the pull request.
3. Fix the issue locally.
4. Run the test suite locally. Remember that the subdirectories under test/ create fine-grained testing targets, so you can e.g. use make check-clang-ast to only run Clang's AST tests.
5. Create a Git commit.
6. Run git clang-format HEAD~1 to format your changes.
7. Open a pull request to the upstream repository on GitHub. Detailed instructions can be found in GitHub's documentation. Mention this issue in the description of the pull request.

If you have any further questions about this issue, don't hesitate to ask via a comment in the thread below.

[llvmbot]

@llvm/issue-subscribers-good-first-issue

Author: None (dragondracarys007)

Hi, I was playing around with affine fusion with affine.vector_load/store operations inside loop and came across this particular case:

`func.func @main(%a: memref<64x512xf32>, %b: memref<64x512xf32>, %c: memref<64x512xf32>, %d: memref<64x4096xf32>, %e: memref<64x4096xf32>) {

affine.for %j = 0 to 8 {
    %lhs = affine.vector_load %a[0, %j * 64] : memref<64x512xf32>, vector<64x64xf32>
    %rhs = affine.vector_load %b[0, %j * 64] : memref<64x512xf32>, vector<64x64xf32>
    %res = arith.addf %lhs, %rhs : vector<64x64xf32>
    affine.vector_store %res, %c[0, %j * 64] : memref<64x512xf32>, vector<64x64xf32>
}

affine.for %j = 0 to 8 {
    %lhs = affine.vector_load %c[0, 0] : memref<64x512xf32>, vector<64x512xf32>
    %rhs = affine.vector_load %d[0, %j * 512] : memref<64x4096xf32>, vector<64x512xf32>
    %res = arith.subf %lhs, %rhs : vector<64x512xf32>
    affine.vector_store %res, %d[0, %j * 512] : memref<64x4096xf32>, vector<64x512xf32>
}

func.return

}`

Upon invoking affine-fusion on this IR with the following command:

mlir-opt --pass-pipeline='builtin.module(affine-loop-fusion)' test.mlir

I see that the loops are getting fused for the above case. Fusion here is illegal since 2nd loop can only be executed once 1st loop completely finishes all its iterations and produces the result to be consumed in 2nd loop. I'm attaching the llvm discourse thread here for further reading about the issue.

https://discourse.llvm.org/t/affine-fusion-legality-for-vector-types/83079

As per the discussion, we should have a bailout in the presence of different-sized element types in the producer/consumer validity checking.

[brod4910]

Is this being worked on? If not, I can pick this up.

[rhanqtl]

Is this being worked on? If not, I can pick this up.

@brod4910 Feel free to work on it.

[brod4910]

Sounds good, thank you!

[avithemad]

Is this still open? New to MLIR, would like to try to work on this.