By Antonio Carlos Schneider Beck, Carlos Arthur Lang Lisbôa, Luigi Carro
As embedded platforms turn into extra advanced, designers face a couple of demanding situations at assorted degrees: they should advance functionality, whereas preserving strength intake as little as attainable, they should reuse existent software program code, and while they should reap the benefits of the additional common sense to be had within the chip, represented through a number of processors operating jointly. This ebook describes numerous ideas to accomplish such various and interrelated targets, by means of adaptability. insurance comprises reconfigurable platforms, dynamic optimization options reminiscent of binary translation and hint reuse, new reminiscence architectures together with homogeneous and heterogeneous multiprocessor structures, conversation concerns and NOCs, fault tolerance opposed to fabrication defects and gentle blunders, and eventually, how you can mix a number of of those concepts jointly to accomplish larger degrees of functionality and suppleness. The dialogue additionally comprises tips to hire really expert software program to enhance this new adaptive method, and the way this new type of software program needs to be designed and programmed.
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Additional info for Adaptable Embedded Systems
2 Heterogeneous Behavior of Applications and Systems 19 Fig. 4 Just a small part of the loop can be optimized Considering hot spots passive of optimization as being loops or subroutines, the level of performance gains one can obtain whenever a determined number of hot spots is mapped to hardware is analyzed. In this first experiment, it is assumed that only the common code of a loop or subroutine can be optimized. In the case of loops, for example, this means that the only portion of the code that is repeated in all iterations will be accelerated.
Cores are turned off when not used), energy consumption of such multiprocessor designs tend to be higher than those with fewer cores. As can be seen in Fig. 75). 9), the energy consumed by the 18-Core multiprocessor reaches the same values as the 8-Core design, thanks to the better usage of the available processors. Summarizing, the best scenario for TLP exploitation shows that the 8-Core and 18-Core design outperforms the superscalar processor in the whole spectrum of parallelism in terms of performance and energy.
We consider different amounts of fine- (instruction) and coarse- (thread) level parallelism available in the application code to investigate the performance potentials of both the aforementioned architectures. For this analysis, considering a portion of a given application code, we classify it in four different ways: • α – the instructions that can be executed in parallel on a single processor; • β – the instructions that cannot be executed in parallel on a single processor; • δ – the amount of instructions that can be distributed among the processors of the multiprocessor environment.