FSM_GA v1.0


FSM_GA is a GPU-accelerated implementation of a genetic algorithm (GA) for finding well-performing finite-state machines (FSM) for predicting binary sequences.

The source code can be requested via email from burtscher@txstate.edu. A description of the FSM_GA implementation and its usage is available here. Note that the FSM_GA code is protected by this license and that by obtaining the FSM_GA code you agree to the terms and conditions set forth in this license.

More information will follow later.

The source code can be compiled into an executable called FSM_GA as follows:

nvcc -O3 -arch=sm_20 FSM_GA10.cu -o FSM_GA

Publications

M. Burtscher and H. Rabeti. "GPU Acceleration of a Genetic Algorithm for the Synthesis of FSM-based Bimodal Predictors." 2013 International Conference on Parallel and Distributed Processing Techniques and Applications. July 2013. [pdf] [pptx]

Official Texas State University Disclaimer