Automotive Software Development for a Multi-Core System-on-a-Chip

Kopetz, Hermann; Obermaisser, Roman; Salloum, C. El; Huber, Bernhard A.

doi:10.1109/seas.2007.2

Cited by 33 publications

(35 citation statements)

References 5 publications

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“…Recently, Network on Chip (NoC) has been proposed as a base for integrated system architecture for automotive electronic systems in [15]. The authors of that paper argued that the proposed architecture provided the required composability level and error containment to integrate multiple functions on a single ECU.…”

Section: Related Workmentioning

confidence: 99%

Multi-criteria resource allocation in modal hard real-time systems

2017

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In this paper, a novel resource allocation approach dedicated to hard real-time systems with distinctive operational modes is proposed. The aim of this approach is to reduce the energy dissipation of the computing cores by either powering them off or switching them into energy-saving states while still guaranteeing to meet all timing constraints. The approach is illustrated with two industrial applications, an engine control management and an engine control unit. Moreover, the amount of data to be migrated during the mode change is minimised. Since the number of processing cores and their energy dissipation are often negatively correlated with the amount of data to be migrated during the mode change, there is some trade-off between these values, which is also analysed in this paper.

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Section: Related Workmentioning

confidence: 99%

Multi-criteria resource allocation in modal hard real-time systems

2017

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“…To manage the specifics of the new platforms, CBD introduced ways to handle the hardware particularities. We mention the work of Kopetz et al [17] that explores the design alternatives of the AUTOSAR component model when targeting multi-core ECUs. The CPU-FPGA platforms are addressed by Andrews et al [18] that introduce a way to utilize COTS components, by synchronizing CPU-FPGA computations inside the components.…”

Section: Related Workmentioning

confidence: 99%

Parallel Execution Optimization of GPU-aware Components in Embedded Systems

Campeanu

2017

International Conferences on Software Engineering and Knowledge Engineering

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Abstract-Many embedded systems process huge amount of data that comes from the interaction with the environment. The Graphics Processing Unit (GPU) is a modern embedded solution that tackles the efficiency challenge when processing a lot of data. GPU may improve even more the system performance by allowing multiple activities to be executed in a parallel manner. In a complex component-based application, the challenge is to decide the components to be executed in parallel on GPU when considering different system factors (e.g., GPU memory, GPU computation power).In the context of component-based CPU-GPU embedded systems, we propose an automatic method that provides parallel execution schemes of components with GPU capabilities. The introduced method considers hardware (e.g., available GPU memory), software properties (e.g., required GPU memory) and communication pattern. Moreover, the method optimizes the overall system performance based on component execution times and system architecture (i.e., communication pattern). The validation uses an underwater robot example to describe the feasibility of our proposed method.

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“…Furthermore, there are many cost and weight arguments in favor of reducing the number of ECUs and interconnect by integrating different functions, developed by different suppliers, into a single ECU. This leads to the concept of integrated architecture where a single integrated distributed hardware base is used for the execution of jobs from different subsystems [23].…”

Section: The Gap Between Critical and Best-effort System Designmentioning

confidence: 99%

Rigorous System Design

Sifakis

2013

FNT in Electronic Design Automation

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Automotive Software Development for a Multi-Core System-on-a-Chip

Cited by 33 publications

References 5 publications

Multi-criteria resource allocation in modal hard real-time systems

Multi-criteria resource allocation in modal hard real-time systems

Parallel Execution Optimization of GPU-aware Components in Embedded Systems

Rigorous System Design

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