Design Goals

Providing a language called Dena for designing arbitrary complex optimizers by combining
- Modular and parallel search strategies: Genetic, PSO, EDA, ...
- Communication strategies for distributed optimization on top of MPI
- Analyzer strategies for analyzing objective functions
- Blocking strategies for block optimization
- Logging strategies for tracking optimization experiments on local system or a remote server
Hybrid parallelism: multi-threading in each node and message passing across nodes (MPI)
‌Block optimization for using memory-intensive optimizers for large number of variables