polybench 0.3.2

Multivariate polynomial arithmetic benchmark tests.

polybench

Multivariate polynomial arithmetic benchmark tests.

Many scientific and engineering applications utilise multivariate polynomial arithmetic in their algorithms and solutions. Here we provide a set of benchmark tests for often-used operations in multivariate polynomial arithmetic:

• Greatest common divisor
• Factorisation

Requirements

• Python >= 3.6.1

You also need at least one or more tools to be benchmarked. They are (in alphabetical order):

• Fermat
• FLINT: automatically downloaded via vcpkg (requires CMake >= 3.15, a C compiler and the Make utility; see also vcpkg dependencies).
• FORM: if not available in the system, then a release binary will be automatically downloaded.
• Mathematica: indeed, Free Wolfram Engine for Developers is sufficient to run.
• reFORM: automatically downloaded (requires Rust >= 1.36).
• Rings: automatically downloaded (requires JDK >= 8).
• Singular
• Symbolica: automatically downloaded (requires Rust >= 1.73), running in restricted mode.

Getting started

Clone this repository and try to run the run.sh script:

git clone https://github.com/tueda/polybench.git
cd polybench
./run.sh --all

When starting the script for the first time, it automatically sets up a virtual environment for required Python packages so that it will not dirty your environment. Some of the tools are provided as libraries registered in public package registries, so the first run takes some time to download, compile and link them with test binaries. After testing, a CSV file and comparison plots will be generated.

For practical benchmarking, configuration parameters should be set adequately. See the help message shown by

./run.sh --help

You can also use pip, pipx, Poetry or Docker with this repository. Installation with pip(x) install or poetry install makes a command polybench available, which acts as the run.sh script described above.

pip install polybench
polybench --all
python -m polybench --all  # alternative way to launch

pipx install polybench
polybench --all

git clone https://github.com/tueda/polybench.git
cd polybench
poetry install
poetry run polybench --all

docker build -t polybench:latest https://github.com/tueda/polybench.git
docker run -it --rm polybench:latest
./run.sh --all

Example

platform	Linux-5.15.0-84-generic-x86_64-with-glibc2.29
python_version	3.8.10.final.0 (64 bit)
cpu_brand	12th Gen Intel(R) Core(TM) i9-12900
cpu_count	16 (logical: 24)
total_memory	62.6GB
FLINT	flint 2.9.0, cc (GNU) 10.5.0
FORM	FORM 4.3.1 (Apr 11 2023, v4.3.1) 64-bits
Mathematica	14.1.0 for Linux x86 (64-bit) (July 22, 2024)
reFORM	0.1.0-fix-serialize, rustc 1.84.1 (e71f9a9a9 2025-01-27)
Rings	2.5.8, JVM: 11.0.20.1 (Ubuntu 11.0.20.1+1-post-Ubuntu-0ubuntu120.04)
Singular	Singular for x86_64-Linux version 4.4.1 (44100, 64 bit) Jan 2025
Symbolica	0.15.0, rustc 1.84.1 (e71f9a9a9 2025-01-27)

Additional benchmark results are available here.

Development

# Initialisation
poetry install
pre-commit install

# Linting and testing
pre-commit run --all-files
poetry run pytest

# Linting and testing for Cargo subproject
cd path/to/project
cargo fmt
cargo clippy
cargo test

# Linting and testing for Gradle subproject
cd path/to/project
./gradlew spotlessApply
./gradlew check

# Test run
./run.sh <options>  # for example, --all

# Release a new version
./scripts/make-release.sh <new_version>  # for example, 0.3.0rc1

License

MIT