RESEARCH ON SYNCHRONIZATION AND DATA PROTECTION PROBLEMS IN IMPLEMENTING MULTITHREADED PROGRAMS

Authors

  • Zhulkovskyi Oleg
  • Zhulkovska Inna
  • Kostenko Victoria
  • Bulhakova Olha

DOI:

https://doi.org/10.34185/1562-9945-5-148-2023-01

Keywords:

multithreaded computing, parallel programming, thread racing, synchronization mechanisms, mutexes.

Abstract

The issue of shared data usage by threads is especially relevant in modern multi-core and multiprocessor systems. The main problems of implementing multithreaded programs are race conditions, deadlocks, and thread starvation. The aim of the work is to solve the problem of thread racing in multithreaded calculations of resource-intensive tasks with parallel access to shared data using appropriate synchronization mechanisms, such as mutexes. A multithreaded algorithm for implementing a typical task of processing large data arrays with protection of the critical area in concurrent programs running on multiprocessor and multi-core systems has been developed and researched.

References

Almeida S. An Introduction to High Performance Computing / S. Almeida // Interna-tional Journal of Modern Physics A. – 2013. – vol. 28, no. 22n23, 1340021, p. 1–9. https://doi: 10.1142/s0217751x13400216

Tanenbaum A. S. Modern Operating Systems / A. S. Tanenbaum, H. Bos. – New Jersey : Prentice Hall Press, 2014. – 1136 p. ISBN 978-0-13-359162-0

Williams A. C++ Concurrency in Action: Practical Multithreading / A.Williams. – Island : Manning Shelter, 2019. – 592 p. ISBN 9781617294693

Kim S. Finding Semantic Bugs in File Systems with an Extensible Fuzzing Frame-work / S. Kim, M. Xu, S. Kashyap, J. Yoon, W. Xu, T. Kim // Proceedings of the 27th ACM Symposium on Operating Systems Principles (SOSP). – 2019. – p. 147–161. https://doi.org/10.1145/3341301.3359662

Xu W. Fuzzing File Systems Via Two-dimensional Input Space Exploration /

W. Xu, H. Moon, S. Kashyap, P-N. Tseng, T. Kim // 2019 IEEE Symposium on Secu-rity and Privacy (SP). – 2019. – p. 818–834. https://doi.org/10.1109/SP.2019.00035

Xu M. Krace: Data Race Fuzzing for Kernel File Systems / M. Xu, S. Kashyap, H. Zhao; T. Kim. // 2020 IEEE Symposium on Security and Privacy (SP). – 2020. – p. 1643–1660. https://doi.org/10.1109/SP40000.2020.00078

Zhulkovskyi O. O. Evaluation of the Efficiency of the Implementation of Parallel Computational Algorithms Using the Library in C++ / O.O.Zhulkovskyi, I. I. Zhulkovska, V. V. Shevchenko, H. Ya. Vokhmianin // Computer Systems and In-formation Technologies. – 2022. – № 3. – p. 49–55. https://doi.org/10.31891/csit-2022-3-6

Gu Y. Dynamic Data Race Detection for OpenMP Programs / Y. Gu, J. Mellor-Crummey // SC18: International Conference for High Performance Computing, Net-working, Storage and Analysis. – 2018. – p. 767–778.

https://doi.org/10.1109/SC.2018.00064

Verma G. Enhancing DataRaceBench for Evaluating Data Race Detection Tools / G. Verma, Y. Shi, C. Liao, B. Chapman, Y. Yan // 2020 IEEE/ACM 4th International Workshop on Software Correctness for HPC Applications (Correctness). – 2020. – p. 20–30.

https://doi.org/10.1109/Correctness51934.2020.00008

TehraniJamsaz A. DeepRace: A Learning-based Data Race Detector / A. TehraniJamsaz, M. Khaleel, R. Akbari, A. Jannesari // 2021 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW). – 2021. – p. 226–233. https://doi.org/ 10.1109/ICSTW52544.2021.00046

Downloads

Published

2023-12-19