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opensecura / 3p / openxla / iree / fe53bc67a7f40ead0c29bbceeef567ee1ac42f26
commitfe53bc67a7f40ead0c29bbceeef567ee1ac42f26[log] [tgz]
authorJonathan DEKHTIAR <jonathan@dekhtiar.com>Tue Apr 18 16:02:59 2023 -0400
committerGitHub <noreply@github.com>Tue Apr 18 13:02:59 2023 -0700
treea3d169ef730571652a2f0ddafeb41ecee401e061
parent27179e2a79600b97aba5ba9ab6bcea3a9103ad73 [diff]
[NVIDIA Container] Fix `PATH` to include NVIDIA binaries (#13126)

This branch addresses and fix a `PATH` issue in the NVIDIA containers.

```sh
docker run -it \
    --gpus=all \
    gcr.io/iree-oss/nvidia-bleeding-edge bash

# %%%% Container is starting  %%%% 

# As you can see `nvcc` is not in the PATH
root@12c0c715d753:/ nvcc --version
bash: nvcc: command not found

# Now let's fix the issue "by hand" and try again
root@12c0c715d753:/ PATH=${PATH}:/usr/local/cuda/bin/
root@12c0c715d753:/ nvcc --version

nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2022 NVIDIA Corporation
Built on Wed_Sep_21_10:33:58_PDT_2022
Cuda compilation tools, release 11.8, V11.8.89
Build cuda_11.8.r11.8/compiler.31833905_0
```

This simple PR fixes the problem.

@ScottTodd & @GMNGeoffrey  for review

---------

Co-authored-by: Geoffrey Martin-Noble <gcmn@google.com>
6 files changed
tree: a3d169ef730571652a2f0ddafeb41ecee401e061
  1. .github/
  2. benchmarks/
  3. build_tools/
  4. compiler/
  5. docs/
  6. experimental/
  7. integrations/
  8. lib/
  9. llvm-external-projects/
  10. runtime/
  11. samples/
  12. tests/
  13. third_party/
  14. tools/
  15. .bazel_to_cmake.cfg.py
  16. .bazelignore
  17. .bazelrc
  18. .bazelversion
  19. .clang-format
  20. .dockerignore
  21. .gitignore
  22. .gitmodules
  23. .pylintrc
  24. .style.yapf
  25. .yamllint.yml
  26. AUTHORS
  27. BUILD.bazel
  28. CITATION.cff
  29. CMakeLists.txt
  30. configure_bazel.py
  31. CONTRIBUTING.md
  32. LICENSE
  33. README.md
  34. WORKSPACE
README.md

IREE: Intermediate Representation Execution Environment

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.

CI Status

Project Status

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!

Communication Channels

Related Project Channels

  • MLIR topic within LLVM Discourse: IREE is enabled by and heavily relies on MLIR. IREE sometimes is referred to in certain MLIR discussions. Useful if you are also interested in MLIR evolution.

Architecture Overview

IREE Architecture IREE Architecture

See our website for more information.

Presentations and Talks

  • 2021-06-09: IREE Runtime Design Tech Talk (recording and slides)
  • 2020-08-20: IREE CodeGen: MLIR Open Design Meeting Presentation (recording and slides)
  • 2020-03-18: Interactive HAL IR Walkthrough (recording)
  • 2020-01-31: End-to-end MLIR Workflow in IREE: MLIR Open Design Meeting Presentation (recording and slides)

License

IREE is licensed under the terms of the Apache 2.0 License with LLVM Exceptions. See LICENSE for more information.