Hardware acceleration for thermodynamic constrained DNA code generation

Qinru Qiu, Prakash Mukre, Morgan Bishop, Daniel Burns, Qing Wu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

Reliable DNA computing requires a large pool of oligonucleotides that do not cross-hybridize. In this paper, we present a transformed algorithm to calculate the maximum weight of the 2-stem common subsequence of two DNA oligonucleotides. The result is the key part of the Gibbs free energy of the DNA cross-hybridized duplexes based on the nearest-neighbor model. The transformed algorithm preserves the physical data locality and hence is suitable for implementation using a systolic array. A novel hybrid architecture that consists of a general purpose microprocessor and a hardware accelerator for accelerating the discovery of DNA under thermodynamic constraints is designed, implemented and tested. Experimental results show that the hardware system provides more than 250X speed-up compared to a software only implementation.

Original languageEnglish (US)
Title of host publicationDNA Computing - 13th International Meeting on DNA Computing, DNA13, Revised Selected Papers
Pages201-210
Number of pages10
DOIs
StatePublished - Aug 27 2008
Externally publishedYes
Event13th International Meeting on DNA Computing, DNA13 - Memphis, TN, United States
Duration: Jun 4 2007Jun 8 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4848 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other13th International Meeting on DNA Computing, DNA13
CountryUnited States
CityMemphis, TN
Period6/4/076/8/07

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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    Qiu, Q., Mukre, P., Bishop, M., Burns, D., & Wu, Q. (2008). Hardware acceleration for thermodynamic constrained DNA code generation. In DNA Computing - 13th International Meeting on DNA Computing, DNA13, Revised Selected Papers (pp. 201-210). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4848 LNCS). https://doi.org/10.1007/978-3-540-77962-9_21