https://github.com/guodong/nanobdd
First-ever high-performance thread-safe BDD library
https://github.com/guodong/nanobdd
bdd bdd-framework concurrency formal-methods parallel threadsafe verification
Last synced: 7 days ago
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First-ever high-performance thread-safe BDD library
- Host: GitHub
- URL: https://github.com/guodong/nanobdd
- Owner: guodong
- License: apache-2.0
- Created: 2023-05-05T14:49:50.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2025-12-30T07:08:13.000Z (about 1 month ago)
- Last Synced: 2026-01-02T18:41:02.126Z (about 1 month ago)
- Topics: bdd, bdd-framework, concurrency, formal-methods, parallel, threadsafe, verification
- Language: C++
- Homepage: https://github.com/guodong/nanobdd/wiki
- Size: 105 KB
- Stars: 8
- Watchers: 1
- Forks: 5
- Open Issues: 0
-
Metadata Files:
- Readme: Readme.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Security: .github/SECURITY.md
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README
# Nanobdd
First-ever high-performance thread-safe BDD (Binary Decision Diagrams) library.
As of our research, Nanobdd is currently the fastest BDD library available, achieving exceptional performance in various benchmarks and use cases.
This project is the public implementation of our SIGCOMM'23 poster:
* Guo D, Luo J, Gao K, et al. Poster: Scaling Data Plane Verification with Throughput-Optimized Atomic Predicates. In Proceedings of the SIGCOMM '23 Poster and Demo Sessions (SIGCOMM '23), New York, NY, USA, Sep. 10 2023.
# Features
- Fully **lock-free** concurrency
- **Automatic referencing** for BDD nodes
- User controlled **garbage collection**
- Easy-to-use APIs by C++ **operator overloading**
- **Java JNI bindings** for Java developers
- And of course, it is **thread-safe**!
# Install
## Dependencies
Nanobdd depends on tbb for concurrent data structures.
CMake (>=v3.2) and g++(>=v9) are required for compilation.
For Java JNI bindings, make sure that you have JDK 17 pre-installed and set the
JAVA_HOME environment variable correctly.
## Compile and install
Nanobdd follows the standard CMake project structure, the quick installation steps are as follows:
```
git clone https://github.com/guodong/nanobdd
cd nanobdd
mkdir build
cd build
cmake ..
make
sudo make install
```
For Java bindings, use maven to compile and install:
```
cd java
mvn install
# should see repository/org/snlab/jni/NanoBDD/1/NanoBDD-1.jar in your $M2_HOME
```
# Basic usage
A simple c++ code to use nanobdd is as follows:
```c++
// include the nanobdd header file
#include
#include
int main(int argc, char** argv) {
// init nanobdd with node table size, cache size, and the number of variables
nanobdd::init(1000, 1000, 3);
// get the three variables
auto x = nanobdd::getVar(0);
auto y = nanobdd::getVar(1);
auto z = nanobdd::getVar(2);
// do magic using c++ operators
auto xy = x & y;
auto xyz = xy & z;
auto xyZ = xy & !z;
assert(xy == (xyz | xyZ));
assert(xy != nanobdd::bddFalse());
return 0;
}
```
Compile and execute the above code by:
```
g++ -o exe test.cpp -lnanobdd -ltbb
./exe
```
If no exceptions, that means the assertions are passed.
# Thread-safe concurrency
The most powerful feature of nanobdd is that it is thread-safe, which is achieved lock-free algorithms. One can safely perform any bdd operations in different threads, nanobdd will handle all underlay data contensions.
An example for using C++17 parallel STL:
```c++
std::for_each(
std::execution::par,
somebdds.begin(),
somebdds.end(),
[&](auto bdd) {
// operate your bdd here
});
```
See `examples/paralle.cpp` for full example.
# Performance
We have compared nanobdd with other librarys including Buddy, JDD and Sylvan in a network verification project on a 40 CPU cores server. Typically, nanobdd is 2~10x faster than others.
# Author and contact
Author: Dong Guo (PhD candidate of Tongji University)
Email: gd@tongji.edu.cn