Open Source
We typicall release our most successful implementations as open source software libraries that are easy to use in real-world applications on github as well as project specific websites. In particular, we provide easy to use interfaces that are compatible with existing systems so that our tools are easy to adopt. Targeted unique features include scalability to huge numbers of processors and to input sizes that can only be handled by largest parallel machines currently available. The implementations are highly modularized and well documented so that changing the system itself is also possible for other researchers, enabling the emergence of a developer community. We have a wide experience in releasing successful algorithm libraries on different subjects. This includes widely used libraries such as (hyper-)graph partitioning, or independent sets. A complete list follows:- SCC -- Scalable Correlation Clustering
- HeiConnect -- Heidelberg Connectivity Augmentation
- HeiOrient -- Heidelberg Edge Orientation
- FLASH-TB -- Public Transit Routing
- HeidelbergMotifClustering -- Local Motif Clustering
- DynGraphLab -- Dynamic Graph Algorithms
- VieCut -- Vienna Minimum Cuts
- VieClus -- Vienna Graph Clustering
- VieM -- Vienna Mapping and Sparse Quadratic Assignment
- DyReach -- Dynamic Reachability
- KaSVM -- Karlsruhe Support Vector Machine
- KaGen -- Karlsruhe Graph Generation
- KaHIP -- Karlsruhe High Quality Partitioning
- KaHyPar -- Karlsruhe Hypergraph Partitioning
- KaDraw -- Karlsruhe Graph Drawing
- KaLP -- Karlsruhe Longest Paths
- KaMIS -- Karlsruhe Maximum Independent Sets
- DMAX -- Data Reduction for Maximum Cut