commit | b3db3dd202669bf8b7b1adcbfe4b5d6d55eebdde | [log] [tgz] |
---|---|---|
author | Geoffrey Martin-Noble <gcmn@google.com> | Wed Aug 25 15:32:16 2021 -0700 |
committer | GitHub <noreply@github.com> | Wed Aug 25 15:32:16 2021 -0700 |
tree | e60408555c39d01a650a3129aa5bb076dc1b16e9 | |
parent | fd387a4d25284b5111afbf251454f7cc6bf11eac [diff] |
Use RBE to cache TF build results (#6867) TF makes it a total PITA to build it with remote execution, but we *can* get a bunch of the benefits (and with much less configuration) with remote caching. This has actions executed locally but cached remotely. Note that we need to ensure that the machines reading and writing from the cache are ~identical, so this should only be executed inside of a docker container and the docker image digest is used as the cache key. Not really sure why I didn't think of this earlier. Tested: observe that in the integrations build of the second commit here, the Bazel part of the build took 30 seconds.
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!
IREE is licensed under the terms of the Apache 2.0 License with LLVM Exceptions. See LICENSE for more information.