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KaHyPar

KaHyPar is a fast, high-quality, and scalable algorithm for partitioning graphs and hypergraphs with billions of edges. It finds applications in minimizing communication costs for distributed (hyper)graph computations, quantum circuit simulations, storage sharding in databases, and VLSI design.

Clustering
Data analysis
Graphs
+ 8

159

KaGen - Communication-free Massively Distributed Graph Generators

Network generators help to provide synthethic instances with controllable parameters by algorithm developers and researchers. KaGen provides generators for a large variety of network models, which are communication-free by making use of pseudorandomization and divide-and-conquer schemes.

Graph Generation
High performance computing
Network Analysis
+ 1

C
C++
CMake
+ 2

Propulate

An asynchronous evolutionary optimization algorithm and software package for global optimization and hyperparameter search on high-performance computers.

Aeronautics, Space and Transport
Earth & Environment
Energy
+ 9

Python

FAME

FAME is the open Framework for distributed Agent-based Modelling of Energy systems. Its purpose is supporting the rapid development and fast execution of complex agent-based energy system simulations.

Agent-based Model
framework
Java
+ 2

TomoBEAR

TomoBEAR is an open-source configurable and customizable modular pipeline for streamlined and parallelized processing of large-scale cryo-electron tomography data for subtomogram averaging.

Alignment
automated reasoning
cluster
+ 16

MATLAB
M
Python
+ 1

KaMPIng - Karlsruhe MPI next generation

KaMPIng is a flexible and (near) zero-overhead C++ wrapper for MPI, covering the whole range of abstraction levels from low-level MPI calls to convenient STL-style bindings. This allows for both rapid prototyping and highly engineered distributed algorithms.

C++
High performance computing
MPI
+ 1

C++
CMake
Shell
+ 1