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Embryonic Architecture with Built-in Self-test and GA Evolved Configuration Data

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Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The embryonic architecture, which draws inspiration from the biological process of ontogeny, has built-in mechanisms for self-repair. The entire genome is stored in the embryonic cells, allowing the data to be replicated in healthy cells in the event of a single cell failure in the embryonic fabric. A specially designed genetic algorithm (GA) is used to evolve the configuration information for embryonic cells. Any failed embryonic cell must be indicated via the proposed Built-in Selftest (BIST) the module of the embryonic fabric. This paper recommends an effective centralized BIST design for a novel embryonic fabric. Every embryonic cell is scanned by the proposed BIST in case the self-test mode is activated. The centralized BIST design uses less hardware than if it were integrated into each embryonic cell. To reduce the size of the data, the genome or configuration data of each embryonic cell is decoded using Cartesian Genetic Programming (CGP). The GA is tested for the 1-bit adder and 2-bit comparator circuits that are implemented in the embryonic cell. Fault detection is possible at every function of the cell due to the BIST module’s design. The CGP format can also offer gate-level fault detection. Customized GA and BIST are combined with the novel embryonic architecture. In the embryonic cell, self-repair is accomplished via data scrubbing for transient errors.
Rocznik
Strony
211--217
Opis fizyczny
Bibliogr. 24 poz., rys., tab., wykr.
Twórcy
  • U R Rao Satellite Centre, India, M S Ramaiah University of Applied Science, India
  • M S Ramaiah University of Applied Science, India
autor
  • U R Rao Satellite Centre, India
Bibliografia
  • [1] X. Zhang, G. Dragffy, A. G. Pipe, N. Gunton and Q. M. Zhu, ”A Reconfigurable Self-healing Embryonic Cell Architecture”, in Proc. of the International Conference on Engineering of Reconfigurable Systems and Algorithms, 2003, pp. 134-140.
  • [2] G. Martinović and I. Novak, ”A combined architecture of biologically inspired approaches to self-healing in embedded systems”, in Proc. of International Conference on Smart Systems and Technologies, 2017, pp. 17-22, Paper identifier https://doi.org/10.1109/SST.2017.8188663
  • [3] Y. Shanshan, W. Youren, ”A new self-repairing digital circuit based on embryonic cellular array”, 8th International Conference on Solid-State and Integrated Circuit Technology, 2006, pp. 1997-1999, Paper identifier https://doi.org/10.1109/ICSICT.2006.306573
  • [4] Z. Zhang, Y. Wang, ”Method to self-repairing reconfiguration strategy selection of embryonic cellular array on reliability analysis”, in Proc. of the 2014 NASA/ESA Conference on Adaptive Hardware and Systems, 2014, pp. 225-232, Paper identifier https://doi.org/10.1109/AHS.2014.6880181
  • [5] Z. Zhai, Q. Yao, Y. Xiaoliang, Y. Rui and W. Youren, ”Self-healing strategy for transient fault cell reutilization of embryonic array circuit”, NASA/ESA Conference on Adaptive Hardware and Systems, 2018, pp. 225-232, Paper identifier https://doi.org/10.1109/AHS.2018.8541472
  • [6] R. Salvador, A. Otero, J. Mora, E. D. La Torre, L. Sekanina and T. Riesgo, ”Fault tolerance analysis and self-healing strategy of autonomous, evolvable hardware systems”, International Conference on Reconfigurable Computing and FPGAs, 2011, pp. 164-169, Paper identifier https://doi.org/10.1109/ReConFig.2011.37
  • [7] E. Benkhelifa, A. Pipe and A. Tiwari, ”Evolvable embryonics: 2-in-1 approach to self-healing systems”, Procedia CIRP, 11, 2013, pp. 394-399, Paper identifier https://doi.org/10.1016/j.procir.2013.07.029
  • [8] V. Sahni and V. P. Pyara, ”An Embryonic Approach to Reliable Digital Instrumentation Based on Evolvable Hardware”, IEEE Transactions on Instrumentation and Measurement, 52(6), 2003, pp. 1696-1702, Paper identifier https://doi.org/10.1109/TIM.2003.818737
  • [9] K.H. Chong, I.B. Aris, M.A. Sinan and B.M. Hamiruce, ”Digital Circuit Structure Design via Evolutionary Algorithm Method”, Journal of Applied Sciences, 7, 2007, pp. 380-385.
  • [10] E. Benkhelifa, A. Pipe, G. Dragffy and M. Nibouche, ”Towards evolving fault tolerant biologically inspired hardware using evolutionary algorithms”, IEEE Congress on Evolutionary Computation, Singapore, 2007, pp. 1548-1554, Paper identifier https://doi.org/10.1109/CEC.2007.4424657
  • [11] J. F. Miller, ”Cartesian Genetic Programming. Natural Computing Series”, 43, 2011, Paper identifier https://doi.org/10.1007/978-3-642-17310-3
  • [12] G. Malhotra, V. Lekshmi, S. Sudhakar and S. Udupa, ”Implementation of threshold comparator using Cartesian genetic programming on embryonic fabric”, Advances in Intelligent Systems and Computing, 939, 2019, pp. 93-102.
  • [13] E. Stomeo, T. Kalganova and C. Lambert, ”A novel genetic algorithm for evolvable hardware”, IEEE Congress on Evolutionary Computation, 2006, pp. 134-141, Paper identifier https://doi.org/10.1109/CEC.2006.1688300
  • [14] Lucian Prodan, Gianluca Tempesti, Daniel Mange and André Stauffer, ”Embryonics: electronic stem cells”, In Proc. of the eighth international conference on Artificial life, 2003, pp. 101-105.
  • [15] D. Mange, A. Stauffer and G. Tempesti, ”Embryonics: A macroscopic view of the cellular architecture”, Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 1478, 1998, pp. 174-184, Paper identifier https://doi.org/10.1007/BFb0057619
  • [16] Yann Thoma, Gianluca Tempesti and Eduardo Sanchez, ”POEtic: An Electronic Tissue for Bio-Inspired Cellular Applications”, Biosystems, vol. 76, 1-3 (2004).
  • [17] A. Stauffer, Daniel Mange, and Joel Rossier, ”Design of Self-organizing Bio-inspired Systems”, Second NASA/ESA Conference on Adaptive Hardware and Systems, 2007.
  • [18] M. R. Boesen and J. Madsen, ”eDNA: A bio-inspired reconfigurable hardware cell architecture supporting self-organisation and self-healing”, NASA/ESA Conference on Adaptive Hardware and Systems, 2009, pp. 147-154, Paper identifier https://doi.org/10.1109/AHS.2009.22
  • [19] C.E. Stroud, ”A Designer’s Guide to Built-in Self-Test”, Springer, 2002.
  • [20] Gayatri Malhotra, Joachim Becker and Maurits Ortmanns, ”Novel Field Programmable Embryonic Cell for Adder and Multiplier”, 9th Conference on Ph.D. Research in Microelectronics and Electronics (PRIME-2013), June 2013.
  • [21] Z. Zhang and Y. Wang, ”Method to self-repairing reconfiguration strategy selection of embryonic cellular array on reliability analysis”, In Proc. of the 2014 NASA/ESA Conference on Adaptive Hardware and Systems, 2014, pp. 225-232, Paper identifier https://doi.org/10.1109/AHS.2014.6880181
  • [22] M. F. Torquato and M. A. C. Fernandes, ”High-Performance Parallel Implementation of Genetic Algorithm on FPGA”, Circuits, Systems, and Signal Processing, 38(9), 2019, pp. 4014-4039, Paper identifier https://doi.org/10.1007/s00034-019-01037-w
  • [23] Z. Zhu, D. J. Mulvaney and V. A. Chouliaras, ”Hardware implementation of a novel genetic algorithm. Neurocomputing”, 71(1-3), 2007, pp. 95-106, Paper identifier https://doi.org/10.1016/j.neucom.2006.11.031
  • [24] A. AL-Marakeby, ”FPGA on FPGA: Implementation of Fine-grained Parallel Genetic Algorithm on Field Programmable Gate Array”, International Journal of Computer Applications, 80(6), 2013, pp. 29-32, Paper identifier https://doi.org/10.5120/13867-1725
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-e2d9846f-78d8-4912-bddf-b16ed8e9cada
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