Hardware Acceleration Of Multi-Deme Genetic Algorithm for DNA Codeword Searching

Abstract

A large and reliable DNA codeword library is key to the success of DNA based computing. Searching for sets of reliable DNA codewords is an NP-hard problem which can take days on state-of-art high performance cluster computers. This work presents a hybrid architecture that consists of a general purpose microprocessor and a hardware accelerator for accelerating the multi-deme genetic algorithm (GA) for the application of DNA codeword searching. The presented architecture provides more than 1000X speed-up compared to a software only implementation. A code extender that uses exhaustive search to produce locally optimum codes in about 1.5 hours for the case of length 16 codes is also described. The experimental results demonstrate that the GA can find ~99% of the words in locally optimum libraries. Finally, we investigate the performance impact of migration, mating and mutation functions in the hardware accelerator. The analysis shows that a modified GA without mating is the most effective for DNA codeword searching.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2008
Accession Number
ADA597344

Entities

People

  • Daniel Burns
  • Prakash Mukre
  • Qing Wu
  • Qinru Qiu

Organizations

  • Air Force Research Laboratory

Tags

Communities of Interest

  • Advanced Electronics

DTIC Thesaurus Topics

  • Air Force Research Laboratories
  • Algorithms
  • Clocks
  • Computations
  • Computer Programming
  • Computers
  • Demographic Cohorts
  • Elements
  • Equations
  • Evolutionary Algorithms
  • Field Programmable Gate Arrays
  • Frequency
  • Genetic Algorithms
  • Information Systems
  • Melting Point
  • Migration
  • Mutations

Fields of Study

  • Computer science

Readers

  • Database Systems and Applications
  • Molecular Genetics
  • Operations Research

Technology Areas

  • AI & ML
  • AI & ML - Information Retrieval
  • AI & ML - Machine Learning Algorithms
  • Biotechnology