commit | 5aaeabde69371d8b01bb1a0181fa8163b17d83ee | [log] [tgz] |
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author | Geoffrey Martin-Noble <gcmn@google.com> | Thu Aug 26 09:18:46 2021 -0700 |
committer | GitHub <noreply@github.com> | Thu Aug 26 09:18:46 2021 -0700 |
tree | 7719ad62425c94c24d2aaa0e772dfd346a725f42 | |
parent | 84438926446e11696f91022a22f9e2f7db052824 [diff] |
Enable remote caching on the integrations GPU build as well (#6881) https://github.com/google/iree/pull/6867 enabled this for the swiftshader integrations build, to good effect, frequently halving the time for the whole workflow. We don't run these builds on presubmit by default, but they're running on machines with real GPUs, so the resources are actually much more precious. Due to GCE constraints on machines with real GPUs, they build machines are also only 16 cores. Technically, these builds are running in slightly different docker containers and so should perhaps have different cache keys, but the only difference is in the final stage either installing nvidia or swiftshader and that only makes a difference for the CMake part of each build when we run vulkan tests. Tested: Bazel part of the turing presubmit run on this PR took under a minute instead of the typical 45 minutes (https://source.cloud.google.com/results/invocations/c23ee21c-2ca8-4717-896d-83e39e49e281 vs https://source.cloud.google.com/results/invocations/8511982d-8120-4e18-985f-5f68be93d4a8)
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.