- Is a sort implementation correct?
- Is a sort implementation fast?
This repository contains:
- An exhaustive test suite, including properties not commonly checked or upheld
- An extensive benchmark suite, abstracting over types, patterns and sizes
- A fuzzing harness
- A novel sort implementation ipnsort (Instruction-Parallel-Network-Sort)
- Vendored sort implementations (Rust, C++, C), eg. cpp_pdqsort, rust_std_stable
- Various experiments and demonstrations
- Results of the research as papers
Most tests and benchmarks can be applied to non Rust implementations. This works by implementing the 5 benchmark types as #[repr(C)] and having a defined C API that can be implemented, wrapping the C/C++ sorts.
Most functionality is by default disabled via cargo features, see the Cargo.toml. Some functionality can be enabled or switched by setting environment variables. See for example benches/bench.rs.
- ipnsort: an efficient, generic and robust unstable sort implementation.
- driftsort: an efficient, generic and robust stable sort implementation.
- Fast, small, robust: pick three. Introducing a novel branchless partition implementation.
- Safety vs Performance. A case study of C, C++ and Rust sort implementations.
- 10~17x faster than what? A performance analysis of Intel's x86-simd-sort (AVX-512)
- A performance analysis of glidesort and ipn_stable
cargo test
cargo miri test
# Might require disabling criterion dependency.
RUSTFLAGS=-Zsanitizer=address cargo t --release
cargo bench
cargo bench <sort_name>-<prediction_state>-<type>-<pattern>-<size>
# Eg:
cargo bench rust_std_stable-hot-u64-random-10000
cargo bench hot-u64-random-10000
cargo bench random
You can also set a custom regex to filter the benchmarks you want to run:
BENCH_REGEX="std.*i32-random-8$" cargo bench
If you want to collect a set of results that can then later be used to create graphs, you can use the run_benchmarks.py utility script:
# Will write results to my_test_zen3.json
BENCH_REGEX="_stable.*random-" python util/run_benchmarks.py my_test_zen3
To run the graph_all.py script to create graphs from this data you need to first install the dependencies as specified in requirements.txt e.g. on Linux:
python -m venv venv
source ./venv/bin/active
pip install --requirement util/graph_bench_result/requirements.txt
Afterwards, you can use the graph_all.py script:
python util/graph_bench_result/graph_all.py my_test_zen3.json
You'll need to install cargo fuzz and cargo afl respectively. See https://rust-fuzz.github.io/book/introduction.html.
cd fuzz
cargo fuzz run libfuzzer_main
cd fuzz-afl
RUSTFLAGS=-Zsanitizer=address cargo afl build --release && cargo afl fuzz -i in -o out -D target/release/afl
Adjust fuzz/fuzz_targets/libfuzzer_main.rs and
fuzz/fuzz_targets/libfuzzer_main.rs respectively to change the fuzz target.
Default rust_ipn_stable.
Please respect the CODE_OF_CONDUCT.md when contributing.
Please open a PR before investing the effort of adding a new sort implementation. The maintainer of this project is currently not interested in building an up-to-date database of all existing sort implementations. Implementations are added based on situational context and relevance to the maintainers' goals. Baseline for all new sort implementations is they must pass all functionality tests, they may pass the safety tests but don't have to.
- Lukas Bergdoll - Voultapher
See also the list of contributors who participated in this project.
This project is licensed under the Apache License, Version 2.0 - see the LICENSE.md file for details.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent