Shared-memory parallel minimum cut algorithms (inexact, exact, cactus, multiterminal)
-
Updated
Apr 15, 2026 - C++
Shared-memory parallel minimum cut algorithms (inexact, exact, cactus, multiterminal)
FREIGHT: Fast Streaming Hypergraph Partitioning — SEA 2023 Best Paper Award
StreamCPI is a framework for reducing the memory consumption of streaming graph partitioners by compressing the array of block assignments used by such partitioners with run-length compression.
Buffered Streaming Graph Partitioning
Exact minimum cuts in hypergraphs at scale using FPT kernelization
Weighted connectivity augmentation algorithms: heuristics, local search, and ILP-based exact approaches
Streaming Process Mapping
Neural LSH implementation!
Implementation of Neural LSH (Dong et al., ICLR 2020) for ANN search: C++ k-NN graph + KaHIP graph partitioning + PyTorch MLP for learned bucket assignment, with Bayesian HPO via Optuna. Beats HW1's IVF-Flat ~4× at high recall on MNIST.
A buffered streaming graph partitioner using prioritized buffering and multilevel refinement. Robust against adversarial node orderings.
Add a description, image, and links to the kahip topic page so that developers can more easily learn about it.
To associate your repository with the kahip topic, visit your repo's landing page and select "manage topics."