Journal of Electrical and Electronic Engineering
Volume 8, Issue 2, April 2020, Pages: 42-46
Received: Apr. 20, 2020;
Accepted: May 9, 2020;
Published: May 27, 2020
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Amitkumar Mistry, Object Video Labs, McLean, USA
Rahul Kher, Department of Electronics & Communication Engg, G H Patel College of Engg & Tech, Vallabh Vidyanagar, India
Optimization metrics for compiled code are not always measured in execution clock cycles on the target architecture. Modern cellular telephone or wireless devices, which may download executables over a wireless network connection or backhaul infrastructure, it is often advantageous for the compiler to reduce the size of the compiled code that must be downloaded to the wireless device. By reducing the size of the code, savings are achieved in terms of bandwidth required for each wireless point of download. These are metrics correlated to the dynamic run-time behaviour of not only the compiled code on the target processor, but also the underlying memory system, caches, DRAM, and buses, etc. Despite new generation of embedded systems are getting innovative and computationally powerful with upcoming embedded processors, the market demands more computational-intensive embedded software to be developed on embedded systems. It is very essential to implement efficient embedded software to meet the market demand of embedded systems. These embedded systems are special-purpose computing systems and built to perform very specific embedded applications. And, these embedded applications mainly use three key resources of embedded systems: (1) CPU (2) Run-time memory (3) Persistent memory i.e. NAND/NOR flash memory. This paper summarizes several effective embedded software optimization techniques to optimize CPU usage, Run-time memory, and Persistent memory.
Embedded Software Optimization for Computation - Intensive Applications, Journal of Electrical and Electronic Engineering. Special Issue: Soft Computing Methods for Electrical and Electronics Engineering Applications.
Vol. 8, No. 2,
2020, pp. 42-46.
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