skip to main content
10.1145/2593069.2593126acmotherconferencesArticle/Chapter ViewAbstractPublication PagesdacConference Proceedingsconference-collections
research-article

Disease Diagnosis-on-a-Chip: Large Scale Networks-on-Chip based Multicore Platform for Protein Folding Analysis

Published:01 June 2014Publication History

ABSTRACT

Protein folding is critical for many biological processes. In this work, we propose an NoC-based multi-core platform for protein folding computation. We first identify the speedup bottleneck for applying conventional genetic algorithm on a mesh-based multi-core platform. Then, we address this computation- and communication- intensive problem while taking into account both hardware and software aspects. Specifically, we group the processing cores into islands and propose an NoC-based multicore architecture for intra- and inter-island communication. The high scalability of the proposed platform allows us to integrate from 100 to 1200 cores for the folding computation. We then propose a genetic migration algorithm to take advantage of the massive parallel platform. Our simulation results show that the proposed platform offers near-linear speedup as the number of cores increases. We also report the hardware cost in area and power based on a 100-core FPGA prototype.

References

  1. J. Atkins and W. E. Hart. On the intractability of protein folding with a finite alphabet of amino acids. Algorithmica, 25(2-3):279--294, 1999.Google ScholarGoogle ScholarCross RefCross Ref
  2. A. Beberg et.al. Folding@home: Lessons from eight years of volunteer distributed computing. In Proc. IPDPS 2009., pages 1--8, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. C. Benitez and H. Lopes. A parallel genetic algorithm for protein folding prediction using the 3d-hp side chain model. In Evolutionary Computation, 2009. IEEE Congress on, pages 1297--1304, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. C. Benitez and H. Lopes. Hierarchical parallel genetic algorithm applied to the three-dimensional hp side-chain protein folding problem. In Systems Man and Cybernetics (SMC), 2010 IEEE International Conference on, pages 2669--2676, 2010.Google ScholarGoogle ScholarCross RefCross Ref
  5. K. A. Dill and J. L. MacCallum. The protein-folding problem, 50 years on. Science, 338(6110):1042--1046.Google ScholarGoogle ScholarCross RefCross Ref
  6. S. C. Flores et.al. Multiscale modeling of macromolecular biosystems. Brief Bioinform, 13(4):395--405, 2012.Google ScholarGoogle ScholarCross RefCross Ref
  7. A. Jain et.al. Fpga accelerator for protein structure prediction algorithm. In Programmable Logic, 5th Southern Conference on, pages 123--128, 2009.Google ScholarGoogle Scholar
  8. Z. Li and H. A. Scheraga. Monte carlo-minimization approach to the multiple-minima problem in protein folding. PNAS, 84(19): 6611--6615, 1987.Google ScholarGoogle ScholarCross RefCross Ref
  9. R. Marculescu and P. Bogdan. The chip is the network: Toward a science of network-on-chip design. Foundations and Trends in Electronic Design Automation, 2(4):371--461, 2009.Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. D. E. Shaw et.al. Anton, a special-purpose machine for molecular dynamics simulation. In Proc, ISCA '07, pages 1--12, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. W.-T. Sung. Efficiency enhancement of protein folding for complete molecular simulation via hardware computing. In Bioinformatics and BioEngineering, 2009., pages 307--312. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. R. Unger and J. Moult. Genetic algorithm for 3d protein folding simulations. In Proceedings of the 5th International Conference on Genetic Algorithms, pages 581--588, 1993. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. K. D. Wilkinson. The discovery of ubiquitin-dependent proteolysis. Proceedings of the National Academy of Sciences of the United States of America, 102(43): 15280--15282, 2005.Google ScholarGoogle ScholarCross RefCross Ref
  14. K. Yue et.al. A test of lattice protein folding algorithms. PNAS, 92(1):325--329, 1995.Google ScholarGoogle ScholarCross RefCross Ref

Recommendations

Comments

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Sign in
  • Published in

    cover image ACM Other conferences
    DAC '14: Proceedings of the 51st Annual Design Automation Conference
    June 2014
    1249 pages
    ISBN:9781450327305
    DOI:10.1145/2593069

    Copyright © 2014 ACM

    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    • Published: 1 June 2014

    Permissions

    Request permissions about this article.

    Request Permissions

    Check for updates

    Qualifiers

    • research-article
    • Research
    • Refereed limited

    Acceptance Rates

    Overall Acceptance Rate1,770of5,499submissions,32%

PDF Format

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader