Embedded Systems with Component-Based GPU Support: A State of the Art

  • A. Miclaus Department of Computer Science, Faculty of Mathematics and Computer Science, Babes-Bolyai University, Cluj-Napoca, Romania
  • S. Petrescu Department of Computer Science, Faculty of Mathematics and Computer Science, Babes-Bolyai University, Cluj-Napoca, Romania
  • A. Vescan Department of Computer Science, Faculty of Mathematics and Computer Science, Babes-Bolyai University, Cluj-Napoca, Romania

Abstract

In order to deal with extremely large quantities of information, embedded systems need high capabilities in order to process the whole amount of data in real time. Two trends are present in the field: the usage of boards with Graphics Processing Units (GPUs) and the usage of component-based development (CBD). Components with GPU capabilities have the great advantage to be platform-independent. However, developing embedded systems with GPUs by using CBD was considered until very recently a problem with restricted availability and flexibility. By introducing specific GPU support for CBD in the form of flexible components and by improving their communication, a solution was identified and checked. Present paper aims to present a state-of-the-art and highlights the newest knowledge to date, articulating encountered confronted issues and describing existing solution approaches.

References

[1] K. Bimraw, Autonomous cars: Past, present and future, a review of the developments in the last century, the present scenario and the expected future of autonomous vehicle technology, The 12th International Conference on Informatics in Control, Automation and Robotics (ICINCO), Colmar, France, July, 2015, pp. 191–198.
[2] C.Ahlberg, L. Asplund, G. Campeanu, F. Ciccozzi, F. Ekstrand, M.Ekstrom, J. Feljan, A.Gustavsson, S. Sentilles, I. Svogor, and E. Segerblad, The Black Pearl: An Autonomous Underwater Vehicle, Technical report, Mälardalen University, Sweden, 2013.
[3] G. Keramidas, Ultra Low Power GPUs for Wearables, Think Silicon, http://lpgpu.org/wp/wp-content/uploads/2014/09/HiPEAC wearables.pdf, Jan. 2015.
[4] G. Campeanu, GPU Support for Component-based Development of Embedded Systems, Ph. D. Thesis, School of Innovation, Design and Engineering, Malardalen University Doctoral Dissertation 264, Sweden, 2018.
[5] M. Wang, Z.Q. Zhang, Y. Zhu, Z. P. Dong, Y.Y. Li, Embedded GPU Implementation of Sensor Correction for On-Board Real-Time Stream Computing of High-Resolution Optical Satellite Imagery, Journal of Real-Time Image Processing, vol. 15, no. 3, (2018), pp. 565–581.
[6] T. Gajger, P. Czarnul, Modelling and Simulation of GPU Processing in the Merpsys Environment Scalable Computing-Practice and Experience, Scalable Computing-Practice and Experience, vol. 19, no. 4, Special Issue: IS, (2018), pp.: 401–422.
[7] W. Kang, J. Kim, PDDS: Scalable Sensor Data Distribution for Cyber-Physical Systems Using GPGPUs, IEEE Internet of Things Journal, vol. 5, no. 3, (2018), pp. 2025–2036, 2018.
[8] H. Lee, M. Shafique, M.A. Al Faruque, Aging-Aware Workload Management on Embedded GPU Under Process Variation, IEEE Transactions on Computers, vol. 67, no. 7 (2018), pp. 920–933.
[9] G.Campeanu, J. Carlson, and S. Sentille, Flexible Components for Development of Embedded Systems with GPUs, 24th Asia-Pacific Software Engineering Conference (2017), p. 219–228.
[10] G. Campeanu, and S. Mubeen, Scavenging Run-time Resources to Boost Utilization in Component-based Embedded Systems with GPUs, Intl. J. Adv. Software, vol. 11, no 1 and 2 (2018), p. 159–169.
[11] G. Campeanu, J. Carlson, and S. Sentilles, Allocation Optimization for Component-based Embedded Systems with GPUs, The 44th Euromicro Conference on Software Engineering and Advanced Applications, Prague (2018), pp. 101–110.
Published
2019-06-17
How to Cite
MICLAUS, A.; PETRESCU, S.; VESCAN, A.. Embedded Systems with Component-Based GPU Support: A State of the Art. Studia Universitatis Babeș-Bolyai Informatica, [S.l.], v. 64, n. 1, p. 67-76, june 2019. ISSN 2065-9601. Available at: <http://www.cs.ubbcluj.ro/~studia-i/journal/journal/article/view/37>. Date accessed: 29 nov. 2020. doi: https://doi.org/10.24193/subbi.2019.1.06.
Section
Articles