Titlebook: Embedded Computer Systems: Architectures, Modeling, and Simulation; 20th International C Alex Orailoglu,Matthias Jung,Marc Reichenbach Conf

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Theorie der Mediensozialisation,nnot be physically accessed once they are deployed (embedded in civil engineering structures, sent in the atmosphere or deep in the oceans). When they run out of energy, they stop executing and wait until the energy level reaches a threshold. Programming such devices is challenging in terms of ensur

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Mediensozialisation von Heranwachsendenh in the time domain, e.g. . to ., and space domain, e.g. core-level. The state-of-the-art for deriving such power information is mainly based on predetermined power models which use linear modeling techniques to determine the core-performance/core-power relationship. However, with multicore process

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https://doi.org/10.1007/978-3-531-92249-2lation is proposed that performs task mapping by jointly addressing task allocation, task frequency assignment, and task duplication. The goal is to minimize energy consumption under real-time and reliability constraints. To provide an optimal solution, the original INLP problem is safely transforme

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Fast Performance Estimation and Design Space Exploration of SSD Using AI Techniques,ed method is faster, the accuracy of the NN-based method depends on the training data set that consists of hardware configurations and performance. The scheduling-based performance estimator is used to generate the training data set fast. The viability of the proposed methodology is confirmed by com

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Combining Task- and Data-Level Parallelism for High-Throughput CNN Inference on Embedded CPUs-GPUs CPUs-GPUs MPSoCs. In our methodology, we ensure efficient utilization of both task-level (pipeline) and data-level parallelism, available in a CNN, to achieve high-throughput execution of the CNN inference on embedded CPUs-GPUs MPSoCs.