Paper Info
Title
PyDGGA: Distributed GGA for Automatic Configuration
Abstract
We present PYDGGA, a Python tool that implements a distributed version of the automatic algorithm configurator GGA, which is a specialized genetic algorithm to find high quality parameters for solvers and algorithms. PYDGGA implements GGA using an event-driven architecture and runs a simulation of future generations of the genetic algorithm to maximize the usage of the available computing resources. Overall, PYDGGA offers a friendly interface to deploy elastic distributed AC scenarios on shared high-performance computing clusters.
Year
DOI
Venue
2021
10.1007/978-3-030-80223-3_2
THEORY AND APPLICATIONS OF SATISFIABILITY TESTING, SAT 2021
Keywords
DocType
Volume
Automatic algorithm configuration, Satisfiability
Conference
12831
ISSN
Citations 
PageRank 
0302-9743
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
Carlos Ansotegui11179.84
Josep Pon241.46
Meinolf Sellmann372848.77
Kevin Tierney4141.69