Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
10.1145/1569901.1570094acmconferencesArticle/Chapter ViewAbstractPublication PagesgeccoConference Proceedingsconference-collections
research-article

Evolutionary algorithms for the mapping of pipelined applications onto heterogeneous embedded systems

Published: 08 July 2009 Publication History

Abstract

In this paper, we compare four algorithms for the mapping of pipelined applications on a heterogeneous multiprocessor platform implemented using Field Programmable Gate Arrays (FPGAs) with customizable processors. Initially, we describe the framework and the model of pipelined application we adopted. Then, we focus on the problem of mapping a set of pipelined applications onto a heterogeneous multiprocessor platform and consider four search algorithms: Tabu Search, Simulated Annealing, Genetic Algorithms, and the Bayesian Optimization Algorithm. We compare the performance of these four algorithms on a set of synthetic problems and on two real-world applications (the JPEG image encoding and the ADPCM sound encoding). Our results show that on our framework the Bayesian Optimization Algorithm outperforms all the other three methods for the mapping of pipelined applications.

References

[1]
S. Banerjee, T. Hamada, P.M. Chau, and R.D. Fellman. Macro pipelining based scheduling on high performance heterogeneous multiprocessor systems. IEEE Transactions on Signal Processing, 43(6):1468--1484, June 1995.
[2]
A. Benoit and Y. Robert. Mapping pipeline skeletons onto heterogeneous platforms. J. Parallel Distrib. Comput., 68(6):790--808, 2008.
[3]
K.S. Chatha and R. Vemuri. A tool for partitioning and pipelined scheduling of hardware-software systems. In ISSS-98: 11th international symposium on System synthesis, pages 145--151, Washington, DC, USA, 1998. IEEE Computer Society.
[4]
W.J. Dally, U.J. Kapasi, B. Khailany, J.H. Ahn, and A. Das. Stream Processors: Progammability and Efficiency. Queue, 2(1):52--62, 2004.
[5]
P. Eles, Z. Peng, K. Kuchcinski, and A. Doboli. System level hardware/software partitioning based on simulated annealing and tabu search. Design Automation for Embedded Systems, 2:5--32, 1997.
[6]
C. Gagné and M. Parizeau. Open beagle: A new c++ evolutionary computation framework. In W.B. Langdon, E. Cantù-Paz, K.E. Mathias, R. Roy, D. Davis, R. Poli, K. Balakrishnan, V. Honavar, G. Rudolph, J. Wegener, L. Bull, M.A. Potter, A.C. Schultz, J.F. Miller, E.K. Burke, and N. Jonoska, editors, GECCO, page 888. Morgan Kaufmann, 2002.
[7]
F. Glover and M. Laguna. Tabu Search. Kluwer, Norwell, MA., 1997. Now published by Springer.
[8]
D.E. Goldberg. Genetic Algorithms in Search,Optimization, and Machine Learning. Addison-Wesley, Reading, Mass., 1989.
[9]
M.I. Gordon, W. Thies, and S. Amarasinghe. Exploiting coarse-grained task, data, and pipeline parallelism in stream programs. In ASPLOS-XII: 2th international conference on Architectural support for programming languages and operating systems, pages 151--162, October 2006.
[10]
M. Grajcar. Genetic list scheduling algorithm for scheduling and allocation on a loosely coupled heterogeneous multiprocessor system. In DAC '99: Proceedings of the 36th ACM/IEEE conference on Design automation, pages 280--285, New York, NY, USA, 1999. ACM.
[11]
H. Javaid and S. Parameswaran. Synthesis of heterogeneous pipelined multiprocessor systems using ILP: jpeg case study. In CODES/ISSS '08: 6th IEEE/ACM/IFIP international conference on Hardware/Software codesign and system synthesis, pages 1--6, New York, NY, USA, 2008. ACM.
[12]
C.T. King, W.H. Chou, and L.M. Ni. Pipelined data parallel algorithms-i: Concept and modeling. IEEE Trans. Parallel Distrib. Syst., 1(4):470--485, 1990.
[13]
S. Kirkpatrick, C. Gelatt, and M. Vecchi. Optimization by simulated annealing. Science, 220(4598):671--680, 1983. http://www.jstor.org/stable/1690046 Retrieved on 16 January 2009.
[14]
Y. Lin, H. Lee, M. Woh, Y. Harel, S. Mahlke, T. Mudge, C. Chakrabarti, and K. Flautner. SODA: A low-power architecture for software radio. In ISCA '06: 33rd International Symposium on Computer Architecture, pages 89--101, Boston, MA, 2006.
[15]
D.M. Nicol and D.R. O'Hallaron. Improved Algorithms for Mapping Pipelined and Parallel Computations. IEEE Trans. Comput., 40(3):295--306, 1991.
[16]
M. Pelikan. Bayesian optimization algorithm with decision graphs in c++, version 1.1, 2000.
[17]
M. Pelikan. Hierarchical Bayesian optimization algorithm: Toward a new generation of evolutionary algorithm. Springer Verlag, Berlin, 2005.
[18]
M. Pelikan, D.E. Goldberg, and E.E. Cantùpaz. Linkage problem, distribution estimation, and bayesian networks. Evol. Comput., 8(3):311--340, 2000.
[19]
S.L. Shee and S. Parameswaran. Design methodology for pipelined heterogeneous multiprocessor system. In DAC '07: 44th annual conference on Design automation, pages 811--816, New York, NY, USA, 2007. ACM.
[20]
G. Wang, W. Gong, B. DeRenzi, and R. Kastner. Application partitioning on programmable platforms using the ant colony optimization. Journal of Embedded Computing, 1(12):1--18, 2005.
[21]
N. Weng, N. Kumar, S. Dechu, and B. Soewito. Mapping task graphs onto network processors using genetic algorithm. In AICCSA 2008: IEEE/ACS International Conference on Computer Systems and Applications, pages 481--488, Doha, Mar./Apr. 2008.
[22]
W. Wolf. The future of multiprocessor systems-on-chips. In 41st ACM/IEEE DAC 04, pages 681--685, 2004.

Cited By

View all
  • (2018)Communication-aware heuristics for run-time task mapping on NoC-based MPSoC platformsJournal of Systems Architecture: the EUROMICRO Journal10.1016/j.sysarc.2010.04.00756:7(242-255)Online publication date: 29-Dec-2018
  • (2018)Multi-objective algorithms for the application mapping problem in heterogeneous multiprocessor embedded system designThe Journal of Supercomputing10.1007/s11227-018-2442-2Online publication date: 29-May-2018
  • (2016)Novel Heuristic Mapping Algorithms for Design Space Exploration of Multiprocessor Embedded Architectures2016 24th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP)10.1109/PDP.2016.78(801-804)Online publication date: Feb-2016
  • Show More Cited By

Index Terms

  1. Evolutionary algorithms for the mapping of pipelined applications onto heterogeneous embedded systems

      Recommendations

      Comments

      Information & Contributors

      Information

      Published In

      cover image ACM Conferences
      GECCO '09: Proceedings of the 11th Annual conference on Genetic and evolutionary computation
      July 2009
      2036 pages
      ISBN:9781605583259
      DOI:10.1145/1569901
      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]

      Sponsors

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 08 July 2009

      Permissions

      Request permissions for this article.

      Check for updates

      Author Tags

      1. boa
      2. fpga
      3. ga
      4. mapping
      5. pipelining
      6. sa
      7. ts

      Qualifiers

      • Research-article

      Conference

      GECCO09
      Sponsor:
      GECCO09: Genetic and Evolutionary Computation Conference
      July 8 - 12, 2009
      Québec, Montreal, Canada

      Acceptance Rates

      Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

      Contributors

      Other Metrics

      Bibliometrics & Citations

      Bibliometrics

      Article Metrics

      • Downloads (Last 12 months)2
      • Downloads (Last 6 weeks)1
      Reflects downloads up to 11 Jan 2025

      Other Metrics

      Citations

      Cited By

      View all
      • (2018)Communication-aware heuristics for run-time task mapping on NoC-based MPSoC platformsJournal of Systems Architecture: the EUROMICRO Journal10.1016/j.sysarc.2010.04.00756:7(242-255)Online publication date: 29-Dec-2018
      • (2018)Multi-objective algorithms for the application mapping problem in heterogeneous multiprocessor embedded system designThe Journal of Supercomputing10.1007/s11227-018-2442-2Online publication date: 29-May-2018
      • (2016)Novel Heuristic Mapping Algorithms for Design Space Exploration of Multiprocessor Embedded Architectures2016 24th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP)10.1109/PDP.2016.78(801-804)Online publication date: Feb-2016
      • (2013)Literature SurveyPipelined Multiprocessor System-on-Chip for Multimedia10.1007/978-3-319-01113-4_2(21-52)Online publication date: 26-Nov-2013
      • (2011)Run-Time Computation and Communication Aware Mapping Heuristic for NoC-Based Heterogeneous MPSoC PlatformsProceedings of the 2011 Fourth International Symposium on Parallel Architectures, Algorithms and Programming10.1109/PAAP.2011.32(203-207)Online publication date: 9-Dec-2011
      • (2010)Model-based analysis tools for component synthesisProceedings of the 9th international conference on Formal Methods for Components and Objects10.1007/978-3-642-25271-6_6(102-121)Online publication date: 29-Nov-2010

      View Options

      Login options

      View options

      PDF

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader

      Media

      Figures

      Other

      Tables

      Share

      Share

      Share this Publication link

      Share on social media