  This paper presents an architecture which is suitable for a massive
parallelization of the compact genetic algorithm. The resulting scheme has
three major advantages. First, it has low synchronization costs. Second, it is
fault tolerant, and third, it is scalable.
  The paper argues that the benefits that can be obtained with the proposed
approach is potentially higher than those obtained with traditional parallel
genetic algorithms. In addition, the ideas suggested in the paper may also be
relevant towards parallelizing more complex probabilistic model building
genetic algorithms.
