HMB: Scheduling PREM-Like Real-Time Tasks at High Memory Bandwidth (Invited Paper)

Authors Mohammadhassan Gholami Derouei , Paolo Valente , Marco Solieri , Andrea Marongiu



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Author Details

Mohammadhassan Gholami Derouei
  • Università degli Studi di Modena e Reggio Emilia, Italy
  • Minerva Systems srl, Modena, Italy
Paolo Valente
  • Università degli Studi di Modena e Reggio Emilia, Italy
Marco Solieri
  • Minerva Systems srl, Modena, Italy
Andrea Marongiu
  • Università degli Studi di Modena e Reggio Emilia, Italy

Acknowledgements

Authors are grateful to Tomasz Kloda at TUM, and Benjamin Rouxel at UNIMORE, with whom they enjoyed inspiring discussions in the conception of this work.

Cite AsGet BibTex

Mohammadhassan Gholami Derouei, Paolo Valente, Marco Solieri, and Andrea Marongiu. HMB: Scheduling PREM-Like Real-Time Tasks at High Memory Bandwidth (Invited Paper). In Fifth Workshop on Next Generation Real-Time Embedded Systems (NG-RES 2024). Open Access Series in Informatics (OASIcs), Volume 117, pp. 1:1-1:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)
https://doi.org/10.4230/OASIcs.NG-RES.2024.1

Abstract

Current homogeneous and heterogeneous computing systems reach high performance through parallelization. Yet, parallel execution of tasks entails non-trivial latency-vs-throughput issues when it comes to concurrent accesses to shared memory. In this respect, effective bandwidth regulation solutions do exist, and provide a basic mechanism to control the latency of memory accesses. Such solutions, though, are often cumbersome to deploy and to configure to guarantee both bounded latency and high utilization of the memory bandwidth. The problem is that memory latency varies non-linearly with the number and type of concurrent accesses, and the latter may in turn vary with time, often unpredictably. For this reason, previous attempts at memory regulation in scheduling solutions resulted either in poor real-time execution guarantees, or in severe underutilization of the memory bandwidth. In this paper, we outline High Memory Bandwidth (HMB), a scheduling solution that guarantees bounded response times to real-time task sets through memory regulation, while also reaching a high utilization memory bandwidth. Since the complete solution is complex, just like the problem it addresses, this preliminary work defines in full detail only the core mechanism. This mechanism builds on the notion of memory access slowdown experienced by any processor performing back-to-back memory operations; this slowdown is due to the interference generated by other processors also accessing the memory at the same time. The core mechanism assumes that each processor can tolerate a certain amount of slowdown before the timing behavior of the task(s) it is running is compromised. Each processor has a priority assigned: the higher the priority, the more stringent the timing requirements. The slowdown can be controlled by regulating with precision the maximum amount of system bandwidth each processor is allowed to use, based on its priority. The proposed mechanism finds the maximum bandwidth each processor can use such that the highest number of processors simultaneously accessing memory is found (thus avoiding memory bandwidth underutilization) while guaranteeing that the slowdown of each processor is kept within the tolerated limits.

Subject Classification

ACM Subject Classification
  • Computer systems organization → Real-time operating systems
Keywords
  • Heterogenous systems
  • Parallel execution
  • Shared memory
  • Bandwidth regulation
  • Memory access
  • Real-time execution
  • Memory bandwidth utilization
  • High Memory Bandwidth (HMB)
  • Memory access slowdown
  • Memory interference
  • Memory-centric scheduling

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References

  1. Ahmed Alhammad, Saud Wasly, and Rodolfo Pellizzoni. Memory efficient global scheduling of real-time tasks. In 21st IEEE Real-Time and Embedded Technology and Applications Symposium, pages 285-296, 2015. URL: https://doi.org/10.1109/RTAS.2015.7108452.
  2. Arm. MPAM Architecture Reference Supplement, 2022. URL: https://developer.arm.com/documentation/ddi0598/latest.
  3. Stanley Bak, Gang Yao, Rodolfo Pellizzoni, and Marco Caccamo. Memory-aware scheduling of multicore task sets for real-time systems. In Proceedings of the 2012 IEEE International Conference on Embedded and Real-Time Computing Systems and Applications, RTCSA '12, pages 300-309, USA, 2012. IEEE Computer Society. URL: https://doi.org/10.1109/RTCSA.2012.48.
  4. Gianluca Brilli, Roberto Cavicchioli, Marco Solieri, Paolo Valente, and Andrea Marongiu. Evaluating controlled memory request injection for efficient bandwidth utilization and predictable execution in heterogeneous socs. ACM Trans. Embed. Comput. Syst., 22(1), December 2022. URL: https://doi.org/10.1145/3548773.
  5. Jon Perez Cerrolaza, Roman Obermaisser, Jaume Abella, Francisco J. Cazorla, Kim Grüttner, Irune Agirre, Hamidreza Ahmadian, and Imanol Allende. Multi-core devices for safety-critical systems: A survey. ACM Comput. Surv., 53(4), August 2020. URL: https://doi.org/10.1145/3398665.
  6. Jailhouse commmunity, Technical University of Munich, Università di Modena e Reggio Emilia, Boston University, and Minerva Systems SRL. MinervaSys Jailhouse, 2019-2023. URL: https://gitlab.com/minervasys/public/jailhouse.
  7. Björn Forsberg, Marco Solieri, Marko Bertogna, Luca Benini, and Andrea Marongiu. The predictable execution model in practice: Compiling real applications for cots hardware. ACM Transactions on Embedded Computing Systems (TECS), 20(5):1-25, 2021. Google Scholar
  8. Arkadeb Ghosal. A Hierarchical Coordination Language for Reliable Real-Time Tasks. PhD thesis, EECS Department, University of California, Berkeley, January 2008. URL: http://www2.eecs.berkeley.edu/Pubs/TechRpts/2008/EECS-2008-10.html.
  9. Intel. Resource Director Technology Refrence Manual, 2019. Google Scholar
  10. Tamara Lugo, Santiago Lozano, Javier Fernández, and Jesus Carretero. A survey of techniques for reducing interference in real-time applications on multicore platforms. IEEE Access, 10:21853-21882, 2022. URL: https://doi.org/10.1109/ACCESS.2022.3151891.
  11. Jan Nowotsch, Michael Paulitsch, Daniel Buhler, Henrik Theiling, Simon Wegener, and Michael Schmidt. Multi-core interference-sensitive wcet analysis leveraging runtime resource capacity enforcement. 2014 26th Euromicro Conference on Real-Time Systems, pages 109-118, 2014. URL: https://api.semanticscholar.org/CorpusID:12573936.
  12. Jan Nowotsch, Michael Paulitsch, Daniel Bühler, Henrik Theiling, Simon Wegener, and Michael Schmidt. Multi-core interference-sensitive wcet analysis leveraging runtime resource capacity enforcement. In 2014 26th Euromicro Conference on Real-Time Systems, pages 109-118, 2014. URL: https://doi.org/10.1109/ECRTS.2014.20.
  13. Rodolfo Pellizzoni, Andreas Schranzhofer, Jian-Jia Chen, Marco Caccamo, and Lothar Thiele. Worst case delay analysis for memory interference in multicore systems. In 2010 Design, Automation & Test in Europe Conference & Exhibition (DATE 2010), pages 741-746, 2010. URL: https://doi.org/10.1109/DATE.2010.5456952.
  14. Ahsan Saeed, Dakshina Dasari, Dirk Ziegenbein, Varun Rajasekaran, Falk Rehm, Michael Pressler, Arne Hamann, Daniel Mueller-Gritschneder, Andreas Gerstlauer, and Ulf Schlichtmann. Memory utilization-based dynamic bandwidth regulation for temporal isolation in multi-cores. In 2022 IEEE 28th Real-Time and Embedded Technology and Applications Symposium (RTAS), pages 133-145, 2022. URL: https://doi.org/10.1109/RTAS54340.2022.00019.
  15. Gero Schwäricke, Tomasz Kloda, Giovani Gracioli, Marko Bertogna, and Marco Caccamo. Fixed-priority memory-centric scheduler for cots-based multiprocessors. In Euromicro Conference on Real-Time Systems, 2020. URL: https://api.semanticscholar.org/CorpusID:220275158.
  16. Parul Sohal, Rohan Tabish, Ulrich Drepper, and Renato Mancuso. E-warp: A system-wide framework for memory bandwidth profiling and management. In 2020 IEEE Real-Time Systems Symposium (RTSS), pages 345-357. IEEE, 2020. Google Scholar
  17. Muhammad R. Soliman and Rodolfo Pellizzoni. PREM-Based Optimal Task Segmentation Under Fixed Priority Scheduling. In Sophie Quinton, editor, 31st Euromicro Conference on Real-Time Systems (ECRTS 2019), volume 133 of Leibniz International Proceedings in Informatics (LIPIcs), pages 4:1-4:23, Dagstuhl, Germany, 2019. Schloss Dagstuhl - Leibniz-Zentrum für Informatik. URL: https://doi.org/10.4230/LIPIcs.ECRTS.2019.4.
  18. Prathap Kumar Valsan, Heechul Yun, and Farzad Farshchi. Taming non-blocking caches to improve isolation in multicore real-time systems. In 2016 IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS), pages 1-12, 2016. URL: https://doi.org/10.1109/RTAS.2016.7461361.
  19. Gang Yao, Rodolfo Pellizzoni, Stanley Bak, Emiliano Betti, and Marco Caccamo. Memory-centric scheduling for multicore hard real-time systems. Real-Time Systems, 48, November 2012. URL: https://doi.org/10.1007/s11241-012-9158-9.
  20. Gang Yao, Rodolfo Pellizzoni, Stanley Bak, Heechul Yun, and Marco Caccamo. Global real-time memory-centric scheduling for multicore systems. IEEE Transactions on Computers, 65(9):2739-2751, 2016. URL: https://doi.org/10.1109/TC.2015.2500572.
  21. Heechul Yun, Gang Yao, Rodolfo Pellizzoni, Marco Caccamo, and Lui Sha. Memory bandwidth management for efficient performance isolation in multi-core platforms. IEEE Transactions on Computers, 65(2):562-576, 2015. Google Scholar
  22. Alexander Zuepke, Andrea Bastoni, Weifan Chen, Marco Caccamo, and Renato Mancuso. Mempol: Policing core memory bandwidth from outside of the cores. In 2023 IEEE 29th Real-Time and Embedded Technology and Applications Symposium (RTAS), pages 235-248. IEEE, 2023. Google Scholar
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