Abstract
Embedded system is anything that uses a microprocessor but is not a general-purpose computer such as televisions, video games, refrigerators, cars, planes, elevators, remote controls, alarm systems, printers, and scanners. The end user sees a smart system as opposed to the computer inside the system, but he does not or cannot modify or upgrade the internals. Embedded systems usually consist of hardware and software. Embedded systems must be efficient in terms of energy, code-size, run-time, weight, and cost. An embedded system is any device controlled by instructions stored on a chip. These devices are usually controlled by a microprocessor that executes the instructions stored on a read-only memory (ROM) chip. The software for the embedded system is called firmware. Embedded systems are also known as real-time systems since they respond to an input or event and produce the result within a guaranteed time period [1].
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References
M. Wolf, Computers as Components: Principles of Embedded Computing System Design, 4th edn. (Morgan Kaufmann, Burlington, 2017)
M. Barr, Embedded Systems Glossary (Neutrino Technical Library)
S. Heath, Embedded Systems Design. EDN series for design engineers (2nd ed.) (2003) Amsterdam: Elsevier
C. Alippi, Intelligence for embedded systems (Springer, Berlin, 2014), p. 283
S. Mittal, A survey of techniques for improving energy efficiency in embedded computing systems. IJCAET 6(4), 440–459 (2014)
J. Eyre, J. Bier, The evolution of DSP processors. IEEE Signal Proc Mag 17(2), 43–51 (2000). https://doi.org/10.1109/79.826411
A. Burns, A. Wellings, Real-Time Systems and Programming Languages, 4th edn. (Addison-Wesley, Boston, 2009)
G. Buttazzo, Hard Real-Time Computing Systems: Predictable Scheduling Algorithms and Applications (Springer, New York, 2011)
J.W.S. Liu, Real-Time Systems (Prentice Hall, Upper Saddle River, 2000)
K. Salah, Real Time Embedded System IPs Protection Using Chaotic Maps. In: Ubiquitous computing, electronics and Mobile communication conference (UEMCON), 2017 IEEE 8th annual. IEEE (2017)
S. Hauck, A. DeHon, Reconfigurable Computing: The Theory and Practice of FPGA-Based Computing (Morgan Kaufmann, Burlington, 2008)
J. Henkel, S. Parameswaran (eds.), Designing Embedded Processors. A Low Power Perspective (Springer, Berlin, 2007)
J. Teich et al., Reconfigurable computing systems. Spec Top Iss J 49(3) (2007)
K. Salah, An Area Efficient Multi-mode Memory Controller Based on Dynamic Partial Reconfiguration. In 2017 8th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON). IEEE (2017), pp. 328–331
A. Klöckner et al., PyCUDA and PyOpenCL: A scripting-based approach to GPU run time code generation. Parallel Comput 38(3), 157–174 (2012)
S. Mittal, J. Vetter, A survey of CPU-GPU heterogeneous computing techniques. ACM Comput Surv (2015)
A. Venkat, D.M. Tullsen, Harnessing ISA Diversity: Design of a Heterogeneous-ISA Chip Multiprocessor. In: Proceedings of the 41st Annual International Symposium on Computer Architecture (2014)
W. Yang, K. Li, K. Li a, A hybrid computing method of SpMV on CPU–GPU heterogeneous computing systems. J Paral Distr Comp 104, 49–60 (2017)
M. Kreutzer, G. Hager, G. Wellein, et al., Sparse Eatrix–Vector Multiplication on GPGPU Clusters: A New Storage Format and a Scalable Implementation, in: Proceedings of the 2012 IEEE 26th International Parallel and Distribute Processing Symposium Workshops & Ph.D. Forum, IPDPSW 12, (IEEE Comp Soc, Washington, DC, 2012), pp. 1696–1702
H. Muthumala, Waidyasooriya, M. Hariyama, K. Uchiyama, Design of FPGA-Based Computing Systems with OpenCL (Springer, Berlin, 2018)
J. Long, Hands On OpenCL: An Open Source Two-Day Lecture Course for Teaching and Learning OpenCL (2018), https://handsonopencl.github.io/. Accessed 25 Jun 2018
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Mohamed, K.S. (2020). Reconfigurable and Heterogeneous Computing. In: Neuromorphic Computing and Beyond. Springer, Cham. https://doi.org/10.1007/978-3-030-37224-8_9
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