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Project Summary

Geneva is a library written in C++ for performing parametric optimization in parallel on devices ranging from multi-processor machines over clusters to Grids and Cloud installations. Geneva currently supports Evolutionary Algorithms, Swarm Algorithms, Gradient Descents, a form of Simulated Annealing as well as Parameter Scans. All algorithms act on the same data structures for the description of optimization problems, so that it becomes possible to "chain" different algorithms, making the result of one algorithm the input of another.

Tags

ai boost c++ cloud cluster evolutionaryalgorithm geneticalgorithm gpgpu gradientdescent grid highperformancecomputing optimization parameterscan particleswarmoptimization simulatedannealing

In a Nutshell, Gemfony Optimization Library (Geneva)...

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Languages

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C++
94%
CMake
5%
3 Other
1%

30 Day Summary

Sep 13 2019 — Oct 13 2019

12 Month Summary

Oct 13 2018 — Oct 13 2019
  • 125 Commits
    Down -153 (55%) from previous 12 months
  • 2 Contributors
    Down -1 (33%) from previous 12 months