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Getting Started with the CIRCT Project

Overview

Welcome to the CIRCT project!

"CIRCT" stands for "Circuit IR Compilers and Tools". The CIRCT project is an (experimental!) effort looking to apply MLIR and the LLVM development methodology to the domain of hardware design tools.

Take a look at the following diagram, which gives a brief overview of the current dialects and how they interact:

Setting this up

These commands can be used to setup CIRCT project:

  1. Install Dependencies of LLVM/MLIR according to the instructions, including cmake and ninja.

If you plan to use the Python bindings, you should start by reading the instructions for building the MLIR Python bindings, which describe extra dependencies, CMake variables, and helpful Python development practices. Note the extra CMake variables, which you will need to specify in step 3) below.

  1. Check out LLVM and CIRCT repos. CIRCT contains LLVM as a git submodule. The LLVM repo here includes staged changes to MLIR which may be necessary to support CIRCT. It also represents the version of LLVM that has been tested. MLIR is still changing relatively rapidly, so feel free to use the current version of LLVM, but APIs may have changed.
$ git clone git@github.com:circt/circt.git
$ cd circt
$ git submodule init
$ git submodule update

Note: The repository is set up so that git submodule update performs a shallow clone, meaning it downloads just enough of the LLVM repository to check out the currently specified commit. If you wish to work with the full history of the LLVM repository, you can manually "unshallow" the the submodule:

$ cd llvm
$ git fetch --unshallow
  1. Build and test LLVM/MLIR:
$ cd circt
$ mkdir llvm/build
$ cd llvm/build
$ cmake -G Ninja ../llvm \
    -DLLVM_ENABLE_PROJECTS="mlir" \
    -DLLVM_TARGETS_TO_BUILD="X86;RISCV" \
    -DLLVM_ENABLE_ASSERTIONS=ON \
    -DCMAKE_BUILD_TYPE=DEBUG
$ ninja
$ ninja check-mlir
  1. Build and test CIRCT:
$ cd circt
$ mkdir build
$ cd build
$ cmake -G Ninja .. \
    -DMLIR_DIR=$PWD/../llvm/build/lib/cmake/mlir \
    -DLLVM_DIR=$PWD/../llvm/build/lib/cmake/llvm \
    -DLLVM_ENABLE_ASSERTIONS=ON \
    -DCMAKE_BUILD_TYPE=DEBUG
$ ninja
$ ninja check-circt
$ ninja check-circt-integration # Run the integration tests.

The -DCMAKE_BUILD_TYPE=DEBUG flag enables debug information, which makes the whole tree compile slower, but allows you to step through code into the LLVM and MLIR frameworks.

To get something that runs fast, use -DCMAKE_BUILD_TYPE=Release or -DCMAKE_BUILD_TYPE=RelWithDebInfo if you want to go fast and optionally if you want debug info to go with it. Release mode makes a very large difference in performance.

If you plan to use the Python bindings, you should also specify -DCIRCT_BINDINGS_PYTHON_ENABLED=ON.

  1. Optionally configure your environment:

It is useful to add the .../circt/build/bin and .../circt/llvm/build/bin directories to the end of your PATH, allowing you to use the tools like circt-opt in a natural way on the command line. Similarly, you need to be in the build directory to invoke ninja, which is super annoying. You might find a bash/zsh alias like this to be useful:

build() {
  (cd $HOME/Projects/circt/build/; ninja $1 $2 $3)
}

This allows you to invoke build check-circt from any directory and have it do the right thing.

  1. Run the Verilator tests: (optional)

Verilator can be used to check SystemVerilog code. To run the tests, build or install a recent version of Verilator (at least v4.034, ideally v1.110 or later to avoid a known bug). (Some Linux distributions have ancient versions.) If Verilator is in your PATH, build check-circt should run the tests which require Verilator.

We provide a script utils/get-verilator.sh to automate the download and compilation of Verilator into a known location. The testing script will check this location first. This script assumes that all the Verilator package dependencies are installed on your system. They are:

  • make
  • autoconf
  • g++
  • flex
  • bison
  • libfl2 # Ubuntu only (ignore if gives error)
  • libfl-dev # Ubuntu only (ignore if gives error)
  1. Install Cap'nProto (optional, affects ESI dialect only)

Some of the ESI dialect code requires libcapnp. (Specifically, the cosimulation component.) That code requires a version of libcapnp which is not yet part of a release. Most of the ESI cosim integration tests also require the python bindings: pycapnp. The utils/get-capnp.sh script downloads, compiles, and installs a known good version to a directory within the circt source code. It optionally installs pycapnp via 'pip3'. The capnp compile requires libtool. Alternatively, you can use a docker image we provide via utils/run-docker.sh.

Windows: notes on setting up with Ninja

Building on Windows using MSVC + Ninja + Python support is straight forward, though full of landmines. Here are some notes:

  • Ninja and cmake must be run in a VS Developer Command shell. If you use Powershell and don't want to start the VS GUI, you can run:
> $vsPath = &(Join-Path ${env:ProgramFiles(x86)} "\Microsoft Visual Studio\Installer\vswhere.exe") -property installationpath
> Import-Module (Get-ChildItem $vsPath -Recurse -File -Filter Microsoft.VisualStudio.DevShell.dll).FullName
> Enter-VsDevShell -VsInstallPath $vsPath -SkipAutomaticLocation
  • VSCode's cmake configure does not operate properly with Python support. The symptom is that the build will complete, but importing circt or mlir crashes Python. Doing everything from the command line is the only way CIRCT compiles have been made to work.

Cheat sheet for powershell:

# Install cmake, ninja, and Visual Studio
> python -m pip install psutil pyyaml numpy pybind11

> $vsPath = &(Join-Path ${env:ProgramFiles(x86)} "\Microsoft Visual Studio\Installer\vswhere.exe") -property installationpath
> Import-Module (Get-ChildItem $vsPath -Recurse -File -Filter Microsoft.VisualStudio.DevShell.dll).FullName
> Enter-VsDevShell -VsInstallPath $vsPath -SkipAutomaticLocation

> cd <circt clone>
> cmake -B<build_dir> llvm/llvm `
    -GNinja `
    -DLLVM_ENABLE_PROJECTS=mlir `
    -DCMAKE_BUILD_TYPE=Debug `
    -DLLVM_TARGETS_TO_BUILD=X86 `
    -DLLVM_ENABLE_ASSERTIONS=ON `
    -DMLIR_ENABLE_BINDINGS_PYTHON=ON `
    -DLLVM_EXTERNAL_PROJECTS=circt `
    -DLLVM_EXTERNAL_CIRCT_SOURCE_DIR="$(PWD)" `
    -DCIRCT_BINDINGS_PYTHON_ENABLED=ON `
    -DCMAKE_EXPORT_COMPILE_COMMANDS=ON
> ninja -C<build_dir> check-circt

Submitting changes to CIRCT

The project is small so there are few formal process yet. We generally follow the LLVM and MLIR community practices, but we currently use pull requests and GitHub issues. Here are some high-level guidelines:

  • Please use clang-format in the LLVM style. There are good plugins for common editors like VSCode, Atom, etc, or you can run it manually. This makes code easier to read and understand.

  • Beyond mechanical formatting issues, please follow the LLVM Coding Standards.

  • Please practice "incremental development", preferring to send a small series of incremental patches rather than large patches. There are other policies in the LLVM Developer Policy document that are worth skimming.

  • Please use "Squash and Merge" in PRs when they are approved - we don't need the intra-change history in the repository history.

  • Please create a PR to get a code review. For reviewers, it is good to look at the primary author of the code you are touching to make sure they are at least CC'd on the PR.

Submitting changes to LLVM / MLIR

This project depends on MLIR and LLVM, and it is occasionally useful to improve them. To get set up for this:

  1. Follow the "How to Contribute" instructions, and install the right tools, e.g. 'arcanist' and clang-format.
  2. Get an LLVM Phabricator account
  3. Ask for LLVM commit access, the barrier is low.

Submitting a patch

The patch flow goes like this:

  1. Check out the LLVM mono repo (as described above).
  2. Make changes to your codebase.
  3. Stage your changes with git add.
  4. Run clang-format to tidy up the details of the patch with git clang-format origin/main
  5. Create a patch in Phabricator with arc diff.
  6. Iterate on review, changing your code and sending another patch with arc diff.

When your review converges and your patch is approved, do the following:

  1. commit your changes with git commit
  2. rebase your changes with git pull --rebase
  3. retest your patch with ninja check-mlir (or whatever other target makes sense)
  4. push your changes with git push