Keywords: computing system, actor model, memory-oriented architecture, feasibility, realisability, computability, solvability, enumerability, confidence
Characteristic function of an actor computing system
UDC 004
DOI: 10.26102/2310-6018/2024.47.4.015
The paper is devoted to the study of the problem of determining a complex feasibility indicator for an actor computing system, which can be expressed as a binary characteristic function. This function depends on the solvability and enumerability of the set of intermediate values of the parameters of the computational problem to be solved, the feasibility of the computational system, i.e. its ability to perform the entire set of necessary computational operations for a given limited time interval (computation cycle), as well as on the degree of confidence in the functional reliability and information security of the computational system, expressed in the form of an integral confidence index. The paper presents a description of the actor model of a computing system in the framework of number theory. The proposed description is based on the representation of a computing system in the form of a composition of actors – function carriers, definitions of computability of these functions, as well as solvability and enumerability of numerical sets of parameter values set for a computing system and arising in it in the process of solving the set tasks. Approaches to ensuring solvability, realisability and trust in the computational system are considered. It is stated that the choice of memory-oriented architecture of computations based on the requirement of realisability is also reasonable from the point of view of providing decidability, enumerability and ensuring trust to the computing system.
1. Burgin M. Systems, Actors and Agents: Operation in a multicomponent environment. URL: https://arxiv.org/abs/1711.08319 [Accessed 25th September 2024].
2. Rinaldi L., Torquati M., Mencagli G., Danelutto M., Menga T. Accelerating Actor-Based Applications with Parallel Patterns. In: 2019 27th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), 13–15 February 2019, Pavia, Italy. IEEE; 2019. pp. 140–147. https://doi.org/10.1109/EMPDP.2019.8671602
3. Vereshchagin N.K., Shen' A. Lektsii po matematicheskoi logike i teorii algoritmov. Chast' 3. Vychislimye funktsii. Moscow: MTsNMO; 2012. 160 p. (In Russ.).
4. Leiserson C.E., Thompson N.C., Emer J.S., Kuszmaul B.C., Lampson B.W., Sanchez D., Schardl T.B. There’s plenty of room at the Top: What will drive computer performance after Moore’s law? Science. 2020;368(6495). https://doi.org/10.1126/science.aam9744
5. Gribkov A.A., Zelensky A.A. Priorities for the development of the microelectronic industry in Russia. Part 2. Russian Economic Bulletin. 2024;7(1):67–80. (In Russ.).
6. Zelenskii A.A., Gribkov A.A. Ontological aspects of the problem of realizability of control of complex systems. Philosophical Thought. 2023;(12):21–31. (In Russ.). https://doi.org/10.25136/2409-8728.2023.12.68807
7. Zelenskiy A.A., Kuznetsov A.P., Ilyukhin Yu.V., Gribkov A.A. Feasibility of motion control of industrial robots, CNC machine tools and mechatronic systems. Part 1. Vestnik Mashinostroeniya. 2022;(11):43–51. (In Russ.). https://doi.org/10.36652/0042-4633-2022-11-43-51
8. Zelenskiy A.A., Kuznetsov A.P., Ilyukhin Yu.V., Gribkov A.A. Feasibility of motion control of industrial robots, CNC machine tools and mechatronic systems. Part 2. Vestnik Mashinostroeniya. 2023;102(3):213–220. (In Russ.). https://doi.org/10.36652/0042-4633-2023-102-3-213-220
9. Zelenskii A.A., Gribkov A.A. Configuration of memory-oriented motion control system. Software systems and computational methods. 2024;(3):12–25. https://doi.org/10.7256/2454-0714.2024.3.71073
10. Ashby W.R. The Set Theory of Mechanism and Homeostasis. In: Issledovaniya po obshchei teorii sistem. Moscow: Progress; 1969. pp. 398–441. (In Russ.).
11. Zelensky A.A., Morozkin M.S., Panfilov A.N., Kuptsov V.R., Gribkov A.A. Ensuring confidence in control systems of technological equipment. Computing, Telecommunications and Control. 2021;14(4):71–83. https://doi.org/10.18721/JCSTCS.14407
12. Shah V., Vaz Salles M.A. Reactors: A Case for Predictable, Virtualized Actor Database Systems. URL: https://arxiv.org/abs/1701.05397 [Accessed 25th September 2024].
13. Lohstroh М., Menard С., Bateni S., Lee E.A. Toward a Lingua Franca for Deterministic Concurrent Systems. ACM Transactions on Embedded Computing Systems. 2021;20(4). https://doi.org/10.1145/3448128
14. Connolly M. A Programmable Processing-in-Memory Architecture for Memory Intensive Applications. Rochester Institute of Technology; 2021. 43 p.
15. Ghose S., Hsieh K., Boroumand A., Ausavarungnirun R., Mutlu O. Enabling the Adoption of Processing-in-Memory: Challenges, Mechanisms, Future Research Directions. URL: https://arxiv.org/abs/1802.00320 [Accessed 25th September 2024].
16. Singh G., Chelini L., Corda S., Awan A.J., Stuijk S., Jordans R., Corporaal H., Boonstra A.-J. Near-Memory Computing: Past, Present, and Future. Microprocessors and Microsystems. 2019;71. https://doi.org/10.1016/j.micpro.2019.102868
17. Kalyaev I., Zaborovskii V. Iskusstvennyi intellekt: ot metafory k tekhnicheskim resheniyam. Control Engineering Россия. 2019;(5):26–31. (In Russ.).
18. Mamaeva T. Mikroskhemy mnogoportovoi pamyati firmy IDT. Komponenty i tekhnologii. 2001;(4):32–34. (In Russ.).
Keywords: computing system, actor model, memory-oriented architecture, feasibility, realisability, computability, solvability, enumerability, confidence
For citation: Zekenskii A.A., Gribkov A.A. Characteristic function of an actor computing system. Modeling, Optimization and Information Technology. 2024;12(4). URL: https://moitvivt.ru/ru/journal/pdf?id=1722 DOI: 10.26102/2310-6018/2024.47.4.015 (In Russ).
Received 18.10.2024
Revised 29.10.2024
Accepted 06.11.2024