Have a personal or library account? Click to login
Two Heuristic Methods of Hardware Threads Interleaving in a Time Predictable Multitasking System Cover

Two Heuristic Methods of Hardware Threads Interleaving in a Time Predictable Multitasking System

Open Access
|Mar 2026

References

  1. Ahn, C.W. and Ramakrishna, R. (2003). Elitism-based compact genetic algorithms, IEEE Transactions on Evolutionary Computation 7(4): 367–385.
  2. Akesson, B. and Goossens, K. (2012). Memory Controllers for Real-Time Embedded Systems, Springer, New York, DOI: 10.1007/978-1-4419-8207-0.
  3. Alander, J. (1992). On optimal population size of genetic algorithms, CompEuro 1992: Proceedings Computer Systems and Software Engineering, The Hague, Netherlands, pp. 65–70.
  4. AlBarakat, L.M., Gratz, P.V. and Jimenez, D.A. (2018). MTB-Fetch: Multithreading aware hardware prefetching for chip multiprocessors, IEEE Computer Architecture Letters 17(2): 175–178.
  5. Alhammad, A. and Pellizzoni, R. (2014). Time-predictable execution of multithreaded applications on multicore systems, Design, Automation & Test in Europe Conference & Exhibition (DATE), 2014, Dresden, Germany, pp. 1–6.
  6. Andalam, S., Roop, P.S., Girault, A. and Traulsen, C. (2014). A predictable framework for safety-critical embedded systems, IEEE Transactions on Computers 63(7): 1600–1612.
  7. Antolak, E. and Pułka, A. (2021). Energy-efficient task scheduling in design of multithread time predictable real-time systems, IEEE Access 9: 121111–121127.
  8. Antolak, E. and Pułka, A. (2020). Flexible hardware approach to multicore time predictable systems design based on the interleaved pipeline processing, IET Circuits, Devices & Systems 14(5): 648–659, DOI: 10.1049/iet-cds.2019.0521.
  9. Antolak, E. and Pułka, A. (2022). An analysis of the impact of gating techniques on the optimization of the energy dissipated in real-time systems, Applied Sciences 12(3): 1630.
  10. Antolak, E. and Pułka, A. (2023). Validation of task scheduling techniques in multithread time predictable systems, IEEE Access 11: 46979–46997.
  11. Antolak, E. and Pułka, A. (2024). Power consumption prediction in real-time multitasking systems, Electronics 13(7): 1347–1366.
  12. Axer, P., Ernst, R., Falk, H., Girault, A., Grund, D., Guan, N., Jonsson, B., Marwedel, P., Reineke, J., Rochange, C., Sebastian, M., Hanxleden, R.V., Wilhelm, R. and Yi, W. (2014). Building timing predictable embedded systems, ACM Transactions on Embedded Computing Systems 13(4): 1–37, DOI: 10.1145/2560033.
  13. Bahn, H. and Cho, K. (2020). Evolution-based real-time job scheduling for co-optimizing processor and memory power savings, IEEE Access 8: 152805–152819.
  14. Bratko, I. (2012). Prolog Programming for Artificial Intelligence, 4th Edn, Addison-Wesley, Harlow.
  15. Broman, D., Zimmer, M., Kim, Y., Kim, H., Cai, J., Shrivastava, A., Edwards, S.A. and Lee, E.A. (2013). Precision timed infrastructure: Design challenges, Proceedings of the 2013 Electronic System Level Synthesis Conference (ESLsyn), Austin, USA, pp. 1–6.
  16. Buttazzo, G.C. (2011). Hard Real-Time Computing Systems: Predictable Scheduling Algorithms and Applications, Springer US, Boston, DOI: 10.1007/978-1-4614-0676-1.
  17. Cazorla, F., Knijnenburg, P., Sakellariou, R., Fernandez, E., Ramirez, A. and Valero, M. (2006). Predictable performance in SMT processors: Synergy between the OS and SMTs, IEEE Transactions on Computers 55(7): 785–799.
  18. Chen, J., Du, C., Han, P. and Zhang, Y. (2019). Sensitivity Analysis of strictly periodic tasks in multi-core real-time systems, IEEE Access 7: 135005–135022.
  19. Chniter, H., Mosbahi, O., Khalgui, M., Zhou, M. and Li, Z. (2020). Improved multi-core real-time task scheduling of reconfigurable systems with energy constraints, IEEE Access 8: 95698–95713.
  20. Clocksin, W. and Mellish, C. (2003). Programming in Prolog, Springer, Berlin/Heidelberg.
  21. Edwards, S.A. and Lee, E.A. (2007). The case for the precision timed (PRET) machine, 2007 44th ACM/IEEE Design Automation Conference, San Diego, USA, pp. 264–265.
  22. Fernández, M., Gioiosa, R., Quiñones, E., Fossati, L., Zulianello, M. and Cazorla, F.J. (2012). Assessing the suitability of the NGMP multi-core processor in the space domain, Proceedings of the 10th ACM International Conference on Embedded Software, Tampere, Finland, pp. 175–184, DOI: 10.1145/2380356.2380389.
  23. Forsberg, B., Benini, L. and Marongiu, A. (2018). HePREM: Enabling predictable GPU execution on heterogeneous SoC, 2018 Design, Automation & Test in Europe Conference & Exhibition (DATE), Dresden, Germany, pp. 539–544.
  24. Gajski, D.D., Abdi, S., Gerstlauer, A. and Schirner, G. (2009). Embedded System Design: Modeling, Synthesis and Verification, Springer US, Boston, DOI: 10.1007/978-1-4419-0504-8.
  25. Glaser, F., Tagliavini, G., Rossi, D., Haugou, G., Huang, Q. and Benini, L. (2021). Energy-efficient hardware-accelerated synchronization for shared-L1-memory multiprocessor clusters, IEEE Transactions on Parallel and Distributed Systems 32(3): 633–648.
  26. Goldberg, D.E. and Goldberg, D.E. (2012). Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, Boston.
  27. Henzinger, T.A. and Kirsch, C.M. (2002). The embedded machine: Predictable, portable real-time code, Proceedings of the ACM SIGPLAN 2002 Conference on Programming Language Design and Implementation, Berlin, Germany, pp. 315–326, DOI: 10.1145/512529.512567.
  28. Ip, N.J.H. and Edwards, S.A. (2006). A processor extension for cycle-accurate real-time software, in D. Hutchison et al. (Eds), Embedded and Ubiquitous Computing, Springer, Berlin/Heidelberg, pp. 449–458, DOI: 10.1007/1180216746.
  29. Kim, D., Ko, Y.-B. and Lim, S.-H. (2020a). Energy-efficient real-time multi-core assignment scheme for asymmetric multi-core mobile devices, IEEE Access 8: 117324–117334.
  30. Kim, Y., Kong, J. and Munir, A. (2020b). CPU-accelerator co-scheduling for CNN acceleration at the edge, IEEE Access 8: 211422–211433.
  31. Kochenderfer, M.J. and Wheeler, T.A. (2019). Algorithms for Optimization, MIT Press, Cambridge.
  32. Lamie, E.L. (2009). Real-Time Embedded Multithreading Using ThreadX, 2nd Edn, Newnes, Amsterdam.
  33. Lee, E. (2005). Absolutely positively on time: What would it take?, Computer 38(7): 85–87.
  34. Lee, E. (2006). The problem with threads, Computer 39(5): 33–42.
  35. Lee, E. and Messerschmitt, D. (1987). Pipeline interleaved programmable DSP’s: Architecture, IEEE Transactions on Acoustics, Speech, and Signal Processing 35(9): 1320–1333.
  36. Lickly, B., Liu, I., Kim, S., Patel, H.D., Edwards, S.A. and Lee, E.A. (2008). Predictable programming on a precision timed architecture, Proceedings of the 2008 International Conference on Compilers, Architectures and Synthesis for Embedded Systems, Atlanta, USA, pp. 137–146, DOI: 10.1145/1450095.1450117.
  37. Liu, I., Reineke, J. and Lee, E.A. (2010). A PRET architecture supporting concurrent programs with composable timing properties, 2010 Conference Record of the 44th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, USA, pp. 2111–2115.
  38. Lutz, M. (2019). Programming Python, 4th Edn, O’Reilly, Beijing.
  39. Michalak, K. (2021). Evolutionary algorithm using random immigrants for the multiobjective travelling salesman problem, Procedia Computer Science 192: 1461–1470.
  40. Moulik, S., Devaraj, R. and Sarkar, A. (2018). COST: A cluster-oriented scheduling technique for heterogeneous multi-cores, 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC), Miyazaki, Japan, pp. 1951–1957.
  41. Oliveira, A.S.R., Almeida, L. and Ferrari, A.D.B. (2011). The ARPA-MT embedded SMT processor and its RTOS hardware accelerator, IEEE Transactions on Industrial Electronics 58(3): 890–904.
  42. Paolieri, M., Quinones, E., Cazorla, F.J., Wolf, J., Ungerer, T., Uhrig, S. and Petrov, Z. (2011). A software-pipelined approach to multicore execution of timing predictable multi-threaded hard real-time tasks, 2011 14th IEEE International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing, Newport Beach, USA, pp. 233–240.
  43. Pathan, R., Voudouris, P. and Stenstrom, P. (2018). Scheduling parallel real-time recurrent tasks on multicore platforms, IEEE Transactions on Parallel and Distributed Systems 29(4): 915–928.
  44. Rehman, A.U., Ahmad, Z., Jehangiri, A.I., Ala’Anzy, M.A., Othman, M., Umar, A.I. and Ahmad, J. (2020). Dynamic energy efficient resource allocation strategy for load balancing in fog environment, IEEE Access 8: 199829–199839.
  45. Reineke, J., Liu, I., Patel, H.D., Kim, S. and Lee, E.A. (2011). PRET DRAM controller: Bank privatization for predictability and temporal isolation, Proceedings of the 7th IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis, Taipei, Taiwan, pp. 99–108, DOI: 10.1145/2039370.2039388.
  46. Schoeberl, M. (2008). A Java processor architecture for embedded real-time systems, Journal of Systems Architecture 54(1-2): 265–286.
  47. Schoeberl, M., Abbaspour, S., Akesson, B., Audsley, N., Capasso, R., Garside, J., Goossens, K., Goossens, S., Hansen, S., Heckmann, R., Hepp, S., Huber, B., Jordan, A., Kasapaki, E., Knoop, J., Li, Y., Prokesch, D., Puffitsch, W., Puschner, P., Rocha, A., Silva, C., Sparsø, J. and Tocchi, A. (2015). T-CREST: Time-predictable multi-core architecture for embedded systems, Journal of Systems Architecture 61(9): 449–471.
  48. Schoeberl, M., Schleuniger, P., Puffitsch, W., Brandner, F. and Probst, C.W. (2012). Towards a time-predictable dual-issue microprocessor: The Patmos Approach, Open Access Series in Informatics 18: 11–21.
  49. Thiele, L. and Wilhelm, R. (2004). Design for timing predictability, Real-Time Systems 28(2/3): 157–177, DOI: 10.1023/B:TIME.0000045316.66276.6e.
  50. Truś, B. (2023). Implementation of the Scheduling Mechanisms of Tasks in a Multicore Real Time System, Silesian University of Technology, Gliwice, (in Polish).
  51. Ungerer, T., Cazorla, F., Sainrat, P., Bernat, G., Petrov, Z., Rochange, C., Quinones, E., Gerdes, M., Paolieri, M., Wolf, J., Casse, H., Uhrig, S., Guliashvili, I., Houston, M., Kluge, F., Metzlaff, S. and Mische, J. (2010). MERASA: Multicore execution of hard real-time applications supporting analyzability, IEEE Micro 30(5): 66–75.
  52. Zimmer, M., Broman, D., Shaver, C. and Lee, E.A. (2014). FlexPRET: A processor platform for mixed-criticality systems, 2014 IEEE 19th Real-Time and Embedded Technology and Applications Symposium (RTAS), Berlin, Germany, pp. 101–110.
DOI: https://doi.org/10.61822/amcs-2026-0012 | Journal eISSN: 2083-8492 | Journal ISSN: 1641-876X
Language: English
Page range: 155 - 172
Submitted on: Mar 25, 2025
|
Accepted on: Oct 30, 2025
|
Published on: Mar 21, 2026
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2026 Andrzej Pułka, Ernest Antolak, Bartłomiej Truś, published by University of Zielona Góra
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.