Distributed Parametric Optimization with the Geneva Library

Explore the Geneva library, an open-source collection of distributed optimization algorithms, in this conference talk from BoostCon 2011. Learn how Geneva leverages various Boost libraries to solve large-scale parametric optimization problems across multi-core systems, clusters, and cloud environments. Discover the library's support for gradient descents, evolutionary algorithms, and swarm algorithms, with plans to include simulated annealing. Understand how Geneva's unified data structures allow candidate solutions to move freely between optimization algorithms. Gain insights into the library's scalability, having been tested with hundreds of clients working simultaneously on optimization problems. Hear about the presenter's experiences using Boost libraries such as Serialization, Threads, Conversion, Date/Time, Function, and Bind from a user's perspective.