Install FlagFFT

Install FlagFFT#

Quick Start#

Clone, build, and verify in one go:

# 1. Clone
git clone https://github.com/flagos-ai/FlagFFT.git
cd FlagFFT

# 2. Initialize submodule
git submodule update --init --recursive

# 3. Build the library, CLI, and test binaries
cmake -B build -DCMAKE_BUILD_TYPE=Release \
      -DFLAGFFT_BUILD_CLI=ON \
      -DFLAGFFT_BUILD_TESTS=ON
cmake --build build -j$(nproc)

# 4. Install the Python codegen package (required for JIT kernel generation)
pip install .

# 5. Run the full accuracy + performance test suite
python tools/run_tests.py --combination full --gpus 0

The runner prints a live progress table and writes summary.json with per-operator accuracy (pass/fail) and performance (geometric mean speedup vs cuFFT) results.

Build Options#

Option	Default	Description
`FLAGFFT_BUILD_CLI`	`OFF`	Build the `flagfft-cli` benchmark/verification tool
`FLAGFFT_BUILD_TESTS`	`OFF`	Build the C++ test suite (requires Google Test + CUDA)
`BACKEND`	`CUDA`	GPU backend selector (only `CUDA` is currently supported)
`CMAKE_BUILD_TYPE`	—	`Release`, `Debug`, `RelWithDebInfo`

Build Library Only#

cmake -B build -DCMAKE_BUILD_TYPE=Release
cmake --build build -j$(nproc)

This produces build/libflagfft.so.

Build Library + CLI + Tests#

cmake -B build -DCMAKE_BUILD_TYPE=Release \
      -DFLAGFFT_BUILD_CLI=ON \
      -DFLAGFFT_BUILD_TESTS=ON
cmake --build build -j$(nproc)

Install to System (Optional)#

After building, install the library and tools system-wide:

cmake --install build --prefix /usr/local

Installs libflagfft.so to lib/, the public header flagfft.h to include/, and flagfft-cli to bin/ (if built with -DFLAGFFT_BUILD_CLI=ON).

Use Docker#

A pre-built environment with all dependencies is available as an alternative to manual setup:

docker build -t flagfft-dev -f docker/Dockerfile .
docker run --gpus all -v $(pwd):/workspace/FlagFFT -it flagfft-dev
# Inside the container, run the build and test steps from Quick Start.

Set Environment Variables#

Variable	Description
`FLAGFFT_PYTHON`	Path to the Python interpreter used by JIT codegen (default: `python3` from PATH)
`FLAGFFT_TUNE_DB`	Path to the SQLite tuning database (default: `~/.flagfft/tune.db`)
`FLAGFFT_TUNE_DISABLE`	Set to `1` to disable tuned plan lookup and always use auto-selected plans