References for Sleptsov Net Computing (SNC) to read, watch, run, cite, and join
Sleptsov net computing is a novel paradigm based on a completely graphical language of concurrent programming and computing-memory mass parallel hardware yielding hyper-performance and reliable verified systems, using present technology.
Motivation: The low efficiency of modern computers on a real-life mixture of tasks because of the processor-memory bottleneck, which is only partially mended by multilayer cache. After Jack Dongarra, efficiency of the supercomputer Frontier is 0.8%.
ACM Tech News and OLF Fulbright lecture
Sleptsov Net Computing Resolves Modern Supercomputing Problems,
The April 21, 2023, edition of ACM TechNews
Dmitry Zaitsev (2023) Sleptsov Net Computing resolves problems of modern supercomputing revealed by Jack Dongarra in his Turing Award talk in November 2022, International Journal of Parallel, Emergent and Distributed Systems. - in 2 months became the most read paper of IJPEDS
Dmitry Zaitsev, Sleptsov Net Computing, Invited OLF Fulbright lecture at Stony Brook University, New York, USA, Oct 10, 2017. Watch:
Video record
Journal articles, special issue, and book chapter
Bernard Berthomieu, Dmitry A. Zaitsev, Sleptsov Nets are Turing-complete, Theoretical Computer Science, Volume 986, 2024, 114346, ISSN 0304-3975,
Dmitry A. Zaitsev, Strong Sleptsov nets are Turing complete, Information Sciences, Volume 621, 2023, Pages 172-182.
Zaitsev D.A. Sleptsov Net Computing (pp. 7731-7743) Chapter 672 in Mehdi Khosrow-Pour (Ed.) Encyclopedia of Information Science and Technology, Fourth Edition (10 Volumes). IGI-Global: USA, 2017.
Zaitsev D.A., Jürjens J. Programming in the Sleptsov net language for systems control, Advances in Mechanical Engineering, 2016, Vol. 8(4), 1-11.
Zaitsev D.A. Sleptsov Nets Run Fast, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2016, Vol. 46, No. 5, 682 - 693.
Special Issue:
Dmitry A. Zaitsev, David E. Probert (2021) Preface for special issue Petri/Sleptsov net based technology of programming for parallel, emergent and distributed systems, International Journal of Parallel, Emergent and Distributed Systems, 36:6, 495-497.
Tatiana R. Shmeleva, Jan W. Owsiński, Abdulmalik Ahmad Lawan (2021) Deep learning on Sleptsov nets, International Journal of Parallel, Emergent and Distributed Systems, 36:6, 535-548.
Alexander A. Kostikov, Nikolay D. Zaitsev, Oleg V. Subotin (2021) Realisation of the double sweep method by using a Sleptsov net, International Journal of Parallel, Emergent and Distributed Systems, 36:6, 516-534.
Universal constructs and general paradigm:
Zaitsev D.A. Universal Sleptsov Net, International Journal of Computer Mathematics, 94(12) 2017, 2396-2408.
Zaitsev D.A. Paradigm of Computations on the Petri Nets, Automation and Remote Control, 2014, Vol. 75, No. 8, 1369-1383.
Prototype implementation papers
Dmitry A. Zaitsev, Tatiana R. Shmeleva, Qing Zhang, and Hongfei Zhao, Virtual Machine and Integrated Developer Environment for Sleptsov Net Computing Parallel Processing Letters, Online June 06 2023
Qing Zhang, Ding Liu, Yifan Hou, Sleptsov Net Processor, in 2022 IEEE 9th International Conference on Problems of Infocommunications, Science and Technology (PIC S&T), 10-12 October 2022, Kharkiv, Ukraine, doi: 10.1109/PICST57299.2022.10238599
Hongfei Zhao, Ding Liu, Yifan Hou, Compiler and Linker of Sleptsov Net Program, in 2022 IEEE 9th International Conference on Problems of Infocommunications, Science and Technology (PIC S&T), 10-12 October 2022, Kharkiv, Ukraine, doi: 10.1109/PICST57299.2022.10238607
Prototype implementation software
Dmitry A. Zaitsev, NDRtoSN: Converter of Tina NDR Petri net file to Sleptsov Net file.
Qing Zhang, SN-VM: Sleptsov net Virtual Machine.
Hongfei Zhao, HSNtoLSN: Compiler-linker of hierarchical Sleptsov net programs.
Tatiana R. Shmeleva, SN-VM-GPU: Sleptsov Net Virtual Machine on Graphics Processing Unit.
Prototype implementation uses Tina graphical editor nd
Bernard Berthomieu, François Vernadat, Silvano dal Zilio, Tina: TIme petri Net Analyzer.
Paris's MCC winner, modeling system Tina, supports Sleptsov nets:
Maximum Steps Tina, preview release.
Projects looking for funding
"Sleptsov Net Computing for Deep Learning" by Université Côte d'Azur on behalf of Prof. Dr Tatiana Shmeleva, EU MSCA4Ukraine.