Sensor data fusion with MPSoCSim in the context of electric vehicle charging stations

Stoychev, Ivan; Wehner, Philipp; Rettkowski, Jens; Kalb, Tobias; Göhringer, Diana; Oehm, J.

doi:10.1109/norchip.2016.7792878

Cited by 4 publications

(4 citation statements)

References 10 publications

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“…On the one hand, we want to evaluate the susceptibility of the ARM SIMD coprocessor (NEON) under neutron irradiation. The ARM architecture is currently one the favourite choices in the embedded market and it is also being used in high-reliability sectors, such as automotive [3][4] or medical [5][6]. In previous work, we have evaluated the sensitivity of NEON to low-energy protons [7].…”

Section: Introductionmentioning

confidence: 99%

Analysis of neutron sensitivity and data-flow error detection in ARM microprocessors using NEON SIMD extensions

Lindoso

García-Valderas

Entrena

2019

Microelectronics Reliability

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This work analyzes the sensitivity to neutrons of SIMD (Single Instruction Multiple Data) microprocessor extensions. To this purpose, the ARM SIMD coprocessor (NEON™) was selected as a case study and neutron radiation experiments were performed on a commercial device running NEON software. In addition, we analyze the benefits of using the NEON coprocessor as a means to efficiently implement data-flow hardening approaches. Experimental results show that SIMD extensions have a great potential to improve performance and reduce the overheads associated to software data-flow hardening.

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Section: Introductionmentioning

confidence: 99%

Analysis of neutron sensitivity and data-flow error detection in ARM microprocessors using NEON SIMD extensions

Lindoso

García-Valderas

Entrena

2019

Microelectronics Reliability

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“…Todays's applications that run on embedded systems such as multimedia (Sanchez et al, 2015 ), automative context (Stoychev et al 2016;Rettkowski et al 2015), signal processing (Meloni et al 2015), and healthcare (Iranfar et al, 2018;El Mimouni & Karim 2014) have performance requirements which can no longer be satisfied by uniprocessor systems (Tafesse & Muthukumar, 2013). Heterogeneous Multiprocessor Systems-on-Chips (MPSoCs) are widely accepted as a solution for future embedded systems (Leupers et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

“…Today'sapplicationsthatrunonembeddedsystemssuchasmultimedia (Sanchez,Agostini,Sousa, &Marcon,2018),automativecontext (Rettkowski,Wehner,Schülper,&Göhringer,2015;Stoychev et al, 2016), signal processing (Meloni, Tuveri, Pani, Raffo, & Palumbo, 2015), and healthcare (Iranfaretal.,2018;Mimouni&Karim,2014)haveperformancerequirementswhichcannolonger besatisfiedbyuniprocessorsystems (Tafesse&Muthukumar,2013).HeterogeneousMulti-processor Systems-on-Chips(MPSoCs)arewidelyacceptedasasolutionforfutureembeddedsystems (Leupers, Aguilar,Eusse,Castrillon,&Sheng,2017).Withtheincreaseofthenumberofprocessingelements inSystems-on-Chip(SoCs),itbecomesverydifficulttocontinuewiththetraditionalnon-scalable bus-basedcommunicationsystems (Mukherjee&Chattopadhyay,2017).TheNetworkonchip(NoC) (Benini&Micheli,2002)paradigmhasbeenintroducedasapromisinginterconnectionsolutionto thesesystems.NoCsofferascalableandflexible-communicationinfrastructurewithhighlysupported modularityandpowerfulperformance (Hesham,Rettkowski,Goehringer,&Ghany,2017).…”

Section: Introductionmentioning

confidence: 99%

Parallel Applications Mapping onto Network on Chip Based on Heterogeneous MPSoCs Using Hybrid Algorithms

Belkacemi

Daoui

Bouzefrane

et al. 2019

International Journal of Distributed Systems and Technologies

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Mapping parallel applications onto a network on chip (NoC) that is based on heterogeneous MPSoCs is considered as an instance of an NP-hard and a multi-objective problem. Various multi-objective algorithms have been proposed in the literature to handle this issue. Metaheuristics stand out as highly appropriate approaches to deal with this kind of problem. These metaheuristics are classified into two sets: population-based metaheuristics and single solution-based ones. To take advantage of the both sets, the trend is to use hybrid solutions that have shown to give better results. In this article, the authors propose to hybridize these two metaheuristics sets to find good Pareto mapping solutions to optimize the execution time and the energy consumption simultaneously. The experimental results have shown that the proposed hybrid algorithms give high quality non-dominated mapping solutions in a reasonable runtime.

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“…Data fusion has become popular recently and various data fusion algorithms have been proposed. [1][2][3][4][5][6] Multi-exposure image fusion is a typical data fusion area, and is considered an effective quality enhancement technique that is widely adopted in consumer electronics. 7 With many multiexposure image fusion algorithms [8][9][10][11][12][13] at hand, it is essential to evaluate their performance.…”

Section: Introductionmentioning

confidence: 99%

Saturation-based quality assessment for colorful multi-exposure image fusion

Deng

Wang

et al. 2017

International Journal of Advanced Robotic Systems

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Multi-exposure image fusion is becoming increasingly influential in enhancing the quality of experience of consumer electronics. However, until now few works have been conducted on the performance evaluation of multi-exposure image fusion, especially colorful multi-exposure image fusion. Conventional quality assessment methods for multi-exposure image fusion mainly focus on grayscale information, while ignoring the color components, which also convey vital visual information. We propose an objective method for the quality assessment of colored multi-exposure image fusion based on image saturation, together with texture and structure similarities, which are able to measure the perceived color, texture, and structure information of fused images. The final image quality is predicted using an extreme learning machine with texture, structure, and saturation similarities as image features. Experimental results for a public multi-exposure image fusion database show that the proposed model can accurately predict colored multi-exposure image fusion image quality and correlates well with human perception. Compared with state-of-the-art image quality assessment models for image fusion, the proposed metric has better evaluation performance.

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Sensor data fusion with MPSoCSim in the context of electric vehicle charging stations

Cited by 4 publications

References 10 publications

Analysis of neutron sensitivity and data-flow error detection in ARM microprocessors using NEON SIMD extensions

Analysis of neutron sensitivity and data-flow error detection in ARM microprocessors using NEON SIMD extensions

Parallel Applications Mapping onto Network on Chip Based on Heterogeneous MPSoCs Using Hybrid Algorithms

Saturation-based quality assessment for colorful multi-exposure image fusion

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