John Newborough, Susan Stepney.
A generic framework for population-based algorithms, implemented on multiple FPGAs.

In Christian Jacob, Marcin L. Pilat, Peter J. Bentley, Jonathan Timmis, editors. ICARIS 2005: Fourth International Conference on Artificial Immune Systems, Banff, Canada, August 2005 . Volume 3627 of Lecture Notes in Computer Science, pp 43-55. Springer, 2005

Abstract:

Many bio-inspired algorithms (evolutionary algorithms, artificial immune systems, particle swarm optimisation, ant colony optimisation, …) are based on populations of agents. Stepney et al [2005] argue for the use of conceptual frameworks and meta-frameworks to capture the principles and commonalities underlying these, and other bio-inspired algorithms. Here we outline a generic framework that captures a collection of population-based algorithms, allowing commonalities to be factored out, and properties previously thought particular to one class of algorithms to be applied uniformly across all the algorithms. We then describe a prototype proof-of-concept implementation of this framework on a small grid of FPGA (field programmable gate array) chips, thus demonstrating a generic architecture for both parallelism (on a single chip) and distribution (across the grid of chips) of the algorithms.

@inproceedings(SS-ICARIS-05,
  author = "John Newborough and Susan Stepney",
  title = "A generic framework for population-based algorithms,
           implemented on multiple FPGAs",
  pages = "43--55",
  crossref = "ICARIS-05"  
)

@proceedings(ICARIS-05,
  title = "ICARIS 2005: Fourth International Conference
           on Artificial Immune Systems,
           Banff, Canada, August 2005",
  booktitle = "ICARIS 2005: Fourth International Conference
           on Artificial Immune Systems,
           Banff, Canada, August 2005",
  series = "LNCS",
  volume = 3627,
  publisher = "Springer",
  year = 2005
)