Rename away from `AArch`-everything (#11903) A number of things in LLVMCPU/ unnecessarily have references to AArch64 in their names. It's most obvious in the `setRootConfig` overload taking a `Mmt4dOp`: this function is called regardless of architecture for any `Mmt4dOp`, and yet it ends up selecting `CPUAArchDoubleTilingExpert`: https://github.com/iree-org/iree/blob/a9227685614999b4de7ee53b3843ef1c7b409489/compiler/src/iree/compiler/Codegen/LLVMCPU/KernelDispatch.cpp#L993-L1038 So the chain of renamings in this PR starts here. There are multiple problems in the name `CPUAArchDoubleTilingExpert`: 1. It's suggesting something specific to ARM architectures ("AArch") even though it's used everywhere. 2. Just `AArch` alone without a 64 or 32 suffix is not a common term. 3. The `Double` part is out of sync with what the code actually does (it uses a `SingleTilingExpert`). So, in line with other experts in the same file, we rename `CPUAArchDoubleTilingExpert` to `Mmt4dTilingExpert`. This is consistent with the above described call site; there is only one other place that creates that expert, that was `setAArch64RootConfig` in the same file. That one was actually specific to `AArch64` but not Mmt4d, so the new name looks out of place here, but I think that's OK because this should only be used in non-data-tiling on AArch64 and I think we already know that this is going away soon. The rest of this PR follows by similar renamings to be consistent. This results in over-using the term `Mmt4d` a bit, since for instance the vector lowerings only see `vector` ops such as the `vector.contract` that result from vectorization of `mmt4d`, not the `mmt4d` themselves. But I think that's less bad than overusing `AArch64` in code that runs on all CPU architectures. Very much open to better names --- don't want to blindly jump from aarch-everything to mmt4d-everything. Maybe a follow-up would reduce the number of separate experts, and the new name would arise for the more unified expert?
IREE (Intermediate Representation Execution Environment, pronounced as “eerie”) is an MLIR-based end-to-end compiler and runtime that lowers Machine Learning (ML) models to a unified IR that scales up to meet the needs of the datacenter and down to satisfy the constraints and special considerations of mobile and edge deployments.
See our website for project details, user guides, and instructions on building from source.
IREE is still in its early phase. We have settled down on the overarching infrastructure and are actively improving various software components as well as project logistics. It is still quite far from ready for everyday use and is made available without any support at the moment. With that said, we welcome any kind of feedback on any communication channels!
See our website for more information.
IREE is licensed under the terms of the Apache 2.0 License with LLVM Exceptions. See LICENSE for more information.