IREE LLVM Sandbox

DISCLAIMER: This is not an officially-supported Google project. It is a sandbox for quick iteration and experimentation on projects related to the IREE project, MLIR, and LLVM.

This repository contains experimental work by the IREE team closely related to LLVM and MLIR, usually with the aim of upstreaming in some form. The main project is at https://github.com/google/iree.

As an experimental project, build greenness, documentation, and polish are likely to be minimal, as it instead prioritizes easy experimentation.

License

Licensed under the Apache license with LLVM Exceptions. See LICENSE for more information.

Subprojects

The repository currently houses the following projects:

The Iterators dialect: database-style iterators for expressing computations on streams of data.
The Tuple: ops for manipulation of built-in tuples (used by the Iterators dialect).

Build Instructions

This project builds as part of the LLVM External Projects facility (see documentation for the LLVM_EXTERNAL_PROJECTS config setting).

It is left to the reader to adapt paths if deviating. We assume below that projects are checked out to $HOME/src.

Check out Project

In your $HOME/src directory, clone this project recursively:

git clone --recursive https://github.com/google/iree-llvm-sandbox

If you have cloned non-recursively already and every time a submodule is updated, run the following command inside the cloned repository instead:

git submodule update --recursive --init

Define the following environment variables (adapted to your situation), ideally making them permanent in your $HOME/.bashrc or in the activate script of your Python virtual environment (see below):

export IREE_LLVM_SANDBOX_SOURCE_DIR=$HOME/src/iree-llvm-sandbox
export IREE_LLVM_SANDBOX_BUILD_DIR=${IREE_LLVM_SANDBOX_SOURCE_DIR}/build

Python prerequisites

Create a virtual environment, activate it, and install the dependencies from requirements.txt:

python -m venv ~/.venv/mlirdev
source ~/.venv/mlirdev/bin/activate
python -m pip install --upgrade pip
python -m pip install -r ${IREE_LLVM_SANDBOX_SOURCE_DIR}/requirements.txt

For details, see the documentation of the MLIR Python Bindings.

Configure and build main project

Run the command below to set up the build system, possibly adapting it to your needs. For example, you may choose not to compile clang, clang-tools-extra, lld, and/or the examples to save compilation time, or use a different variant than Debug.

cmake \
  -DPython3_EXECUTABLE=$(which python) \
  -DBUILD_SHARED_LIBS=ON \
  -DCMAKE_EXPORT_COMPILE_COMMANDS=TRUE \
  -DCMAKE_BUILD_TYPE=Debug \
  -DLLVM_ENABLE_PROJECTS="mlir;clang;clang-tools-extra" \
  -DLLVM_TARGETS_TO_BUILD="X86" \
  -DLLVM_ENABLE_ASSERTIONS=ON \
  -DLLVM_INCLUDE_UTILS=ON \
  -DLLVM_INSTALL_UTILS=ON \
  -DLLVM_BUILD_EXAMPLES=ON \
  -DLLVM_EXTERNAL_PROJECTS=structured \
  -DLLVM_EXTERNAL_STRUCTURED_SOURCE_DIR=${IREE_LLVM_SANDBOX_SOURCE_DIR} \
  -DLLVM_ENABLE_LLD=ON \
  -DLLVM_CCACHE_BUILD=ON \
  -DMLIR_INCLUDE_INTEGRATION_TESTS=ON \
  -DMLIR_ENABLE_BINDINGS_PYTHON=ON \
  -DMLIR_ENABLE_PYTHON_BENCHMARKS=ON \
  -S${IREE_LLVM_SANDBOX_SOURCE_DIR}/third_party/llvm-project/llvm \
  -B${IREE_LLVM_SANDBOX_BUILD_DIR} \
  -G Ninja

To build, run:

cd ${IREE_LLVM_SANDBOX_BUILD_DIR} && ninja

Using structured-opt

"${IREE_LLVM_SANDBOX_BUILD_DIR}"/bin/structured-opt --help

Running tests

You can run all tests with the following command:

cd ${IREE_LLVM_SANDBOX_BUILD_DIR} && ninja

You may also use lit to run a subset of the tests. You may

lit -v ${IREE_LLVM_SANDBOX_BUILD_DIR}/test
lit -v ${IREE_LLVM_SANDBOX_BUILD_DIR}/test/Integration
lit -v ${IREE_LLVM_SANDBOX_BUILD_DIR}/test/Dialect/Iterators/map.mlir

Diagnostics via LSP servers

The MLIR LSP Servers allows editors to display as-you-type diagnostics, code navigation, and similar features. In order to extend this functionality to the dialects from this repository, use the following LSP server binaries:

${IREE_LLVM_SANDBOX_BUILD_DIR}/bin/mlir-proto-lsp-server
${IREE_LLVM_SANDBOX_BUILD_DIR}/bin/tblgen-lsp-server",
${IREE_LLVM_SANDBOX_BUILD_DIR}/bin/mlir-pdll-lsp-server

In VS Code, this is done via the mlir.server_path, mlir.pdll_server_path, and mlir.tablegen_server_path properties in settings.json.

Hashes of Interest

Repro for experimental results described in the arxiv paper:

git checkout 680c8160edb7aa13b621b28c221288624ebc37e4
echo Please update LLVM to $(cat pinned-llvm-version)

Hash before transitioning to schedule dialect only:

git checkout ea0e5ec37a4d73808e16926c0335cc21fde0286c
echo Please update LLVM to $(cat pinned-llvm-version)

iree-org/iree-llvm-sandbox