Mt-KaHyPar (Multi-Threaded Karlsruhe Hypergraph Partitioner) is a shared-memory multilevel graph and hypergraph partitioner equipped with parallel implementations of techniques used in the best sequential partitioning algorithms. Mt-KaHyPar can partition extremely large hypergraphs very fast and with high quality.

KaHIP -- Karlsruhe HIGH Quality Partitioning.

Header-Only C++ Library for Graph Representation and Algorithms

KaHyPar (Karlsruhe Hypergraph Partitioning) is a multilevel hypergraph partitioning framework providing direct k-way and recursive bisection based partitioning algorithms that compute solutions of very high quality.

massively parallel geophysics distributed mesh generator

Ultra fast DFT scan stitching partition generator. Amortized O(N) complexity

Verlet particle simulator that uses spatial grid partitioning for more optimized collision detection.

Spatial cache data structures with python binding implementation.

Multiway Parallel Quicksort (MPQsort) is a fast implementation of parallel in-place Quicksort using OpenMP.

University of Pittsburgh ECE 0302

PSML: parallel system modeling and simulation language for electronic system level

Header-Only-Library providing functions that perform parallel in-place Partitioning, Quickselect and Quicksort

A Parallel Discrete Event Simulation Engine with Examples

In mathematics, the graph partition problem is defined on data represented in the form of a graph G = (V,E), with V vertices and E edges, such that it is possible to partition G into smaller components with specific properties.

Tailor is a spatially load balancing flow solver which can operate on three-dimensional moving overset meshes.

METIS, Balanced Label Propagation, Bayesian Sharding, and its optimization techniques

Módulo Node.js para execução de sub-rotinas de processamento do algoritmo Cloud Partitioning for Iterative Closest Point (CP-ICP).

Shared-Memory Parallel Multilevel Partitioning.

Image partitioning (color/gray/multichannel) based on the piecewise affine-linear Mumford-Shah model (aka the affine-linear Potts model)

A Parallel Graph Partitioning Approach designed to work on density-based clustering algorithms.