This topic may have been covered before, but I can’t find answers. I am trying to generate code for a device where memory needs padding in the lowest dimensions. Memrefs and maps seems uniquely suited for this:

```
#paddedMap = affine-map<(d0, d1) -> (d0 floordiv 32, d1 floordiv 32, d0 mod 32, d1 mod 32)
%1 = alloc() : memref<62x61xf32, #paddedMap>
```

Using the maps is perfect as it let us preserve the original data dimension (i.e. 62x61, data that matters), while also carrying with the memrefs the desired data layout and memory size needed for data allocation (i.e. 2x2x32x32).

All is well until lowering to LLVM where I hit this assert:

```
Assertion failed: (isStrided(type) && "Non-strided layout maps must have been normalized away"), function convertMemRefSignature, file /Users/alexe/MLIR/llvm-project/mlir/lib/Conversion/StandardToLLVM/StandardToLLVM.cpp, line 237.
```

The example is simple (and actually has no padding as dimensions match):

```
#pad = affine_map<(i) -> (i floordiv 4, i mod 4)>
func @matmul(%A: memref<16xf64, #pad>) {
affine.for %arg3 = 0 to 16 {
%a = affine.load %A[%arg3] : memref<16xf64, #pad>
%p = mulf %a, %a : f64
affine.store %p, %A[%arg3] : memref<16xf64, #pad>
}
return
}
```

when compiled with various different options (did not find a combination that works):

```
mlir-opt simple.mlir --simplify-affine-structures --lower-affine --convert-std-to-llvm
```

I have looked at some of the test codes, they often seems to flatten N-dimensional tensors to a 1D in maps, not sure why that is needed.

Is my error due to missing functionality, erroneous input, erroneous optimization sequence?

I think the expressivity of N dimensional memrefs with maps to deal with layout is a very strong abstraction. I hope we can make it work for this case, which hardly seems to be a corner case.

Thanks