commit | deb48059607272ba3a320ec5ccef48783e6b3fa5 | [log] [tgz] |
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author | Stella Laurenzo <laurenzo@google.com> | Fri Nov 25 10:41:46 2022 -0800 |
committer | GitHub <noreply@github.com> | Fri Nov 25 10:41:46 2022 -0800 |
tree | d673962e032122ef08f7335115c2076ce8283dab | |
parent | 7ed278e2d91b1a70187e5414ecb6e736444f9279 [diff] |
Enable split-dwarf and thin archives when possible. (#11292) Split-dwarf separates debug info to per-object .dwo files, which reduces IO throughout the build. It works best with the gdb-index linker feature (of gold and lld), which links to this debug info (vs embedding) and also adds an index to speed debugger launch. Thin archives, which is a feature of GNU AR and llvm-ar on Linux produces static archives that do not embed object files, instead just referencing them by path. While spit-dwarf is aimed at debug configurations, thin archives can help all builds. Results: ``` Before: Clean build: real 7m24.609s user 392m31.930s sys 18m59.113s build dir: 11GiB libIREECompiler.so: 1.4GiB Trivial relink the compiler: real 0m5.336s user 0m12.862s sys 0m31.818s After: Clean build: real 7m38.461s user 402m52.180s sys 18m8.314s build dir: 5.2GiB libIREECompiler.so: 490MiB Trivial relink the compiler: real 0m4.350s user 0m8.233s sys 0m8.104s gdb of iree-compile starts instantly and sets a breakpoint on ireeCompilerRunMain with no delay (a few seconds to step in) ``` For a RelWithDebInfo build as documented on our website, wall clock time to do a clean build is in the noise on my machine, but with the new flags: * Build directory size is reduced by >50% * Size of the main compiler shared library is reduced by ~65% * Time to incremental relink of the compiler after a trivial change to a C file is reduced by ~18%. Ideally there would be a less invasive way to enable these things, but that isn't coming any time soon. I think the complexity is worth it. The trivial relink case shows that this should make the cycle time better disproportionately on lower end machines as well.
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.