commit | 658cf6c8a48d155259f3bb08a536cc47f1d50b78 | [log] [tgz] |
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author | Ben Vanik <benvanik@google.com> | Mon Nov 22 10:35:41 2021 -0800 |
committer | GitHub <noreply@github.com> | Mon Nov 22 10:35:41 2021 -0800 |
tree | aca3121dbd6ea3c1a6aa65ec0bb71e21f795b039 | |
parent | 9e20ae6728e821e8434ceaca6bbbaee412b367c5 [diff] |
Splitting librt into two builtins and changing linking style. (#7721) This is based on the work done in #7561 to better link the bitcode in the compiler. Instead of generating object files to pass to the linker tool this now links the bitcode modules directly together before running the LLVM optimization passes. This gets us LTO-like behavior and makes the bitcode equivalent to any other LLVM IR we could generate in the compiler. As part of this the IREE-specific portion has been reworked to compile both standalone and as part of a host binary. This lets us write tests and benchmarks for the functions in there and debug them independently of the compiler. The new setup will also allow us to specialize for particular archs if we really needed. For example, if we added MMA-like CPU primitives we could build them out in here. Each of the Builtins/ files can make a decision as to which bitcode file to link and what options to set based on the target configuration being compiled (selecting SIMD variants, etc). There's still some stuff to work out but this drops our embedded ELFs by 13KB (on x64) and will allow us to add more musl/runtime functions without bloating binaries. I think getting further will require us to generate a linker script. This also prepares us for removing the linker requirement when generating static libraries as we can include all of the code a user needs in the single static object we emit.
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.