Bringing DSE to Life: Exploring the Design Space of an Industrial Automotive Use Case

Eder, Johannes; Zverlov, Sergey; Voß, Sebastian; Khalil, Maged; Ipatiov, Alexandra

doi:10.1109/models.2017.36

Cited by 26 publications

(9 citation statements)

References 13 publications

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“…ProMARTES [30] is an approach that combines profiling, analysis and simulation for architecture performance optimisation using Genetic Algorithms (GAs). Eder et al [9] use a dedicated domainspecific modelling language to formulate memory, safety, cost, energy and bandwidth constraints for the mapping/distribution problem, i.e. the allocation of software components to hardware components.…”

Section: Related Workmentioning

confidence: 99%

Automating integration under emergent constraints for embedded systems

Schlatow

Schmidt

Ernst

2021

SICS Softw.-Inensiv. Cyber-Phys. Syst.

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As embedded applications are subject to non-functional requirements (latency, safety, reliability, etc.) they require special care when it comes to providing assurances. Traditionally, these systems are quite static in their software and hardware composition. However, there is an increasing interest in enabling adaptivity and autonomy in embedded systems that cannot be satisfied with preprogrammed adaptations any more. Instead, it requires automated software composition in conjunction with model-based analyses that must adhere to requirements and constraints from various viewpoints. A major challenge in this matter is that embedded systems are subject to emergent constraints which are affected by inter-dependent properties resulting from the software composition and platform configuration. As these properties typically require an in-depth evaluation by complex analyses, a holistic formulation of parameters and their constraints is not applicable. We present a compositional framework for model-based integration of component-based embedded systems. The framework provides a structured approach to perform operations on a cross-layer model for model enrichment, synthesis and analysis. It thereby provides the overarching mechanisms to combine existing models, analyses and reasoning. Furthermore, it automates integration decisions and enables an iterative exploration of feasible system compositions. We demonstrate the applicability of this framework on a case study of a stereo-vision robot that uses a component-based operating system.

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Section: Related Workmentioning

confidence: 99%

Automating integration under emergent constraints for embedded systems

Schlatow

Schmidt

Ernst

2021

SICS Softw.-Inensiv. Cyber-Phys. Syst.

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“…Each parent maintains full control over its arbitrary structured subsystems and defines their inter-relationship, for example by selectively permitting communication between them or by assigning physical resources. Some non-adaptable legacy parts, such as SLAM and navigation, rely on Robot Operating System (ROS) 8 , a robotic meta-operating system, and are so far excluded from the adaption process.…”

Section: Applicationmentioning

confidence: 99%

“…ProMARTES [7] is an approach that combines profiling, analysis and simulation for architecture performance optimization using Genetic Algorithms (GAs). Eder et al [8] use a dedicated domain-specific modeling language to formulate memory, safety, cost, energy and bandwidth constraints for the mapping problem, i.e. the allocation of software components to hardware components.…”

Section: State-of-the-art and Related Workmentioning

confidence: 99%

Demonstrating Controlled Change for Autonomous Space Vehicles

Dorflinger

Albers

Fiethe

et al. 2019

2019 NASA/ESA Conference on Adaptive Hardware and Systems (AHS)

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Recent research discusses concepts of infield changes to overcome the drawbacks of conventional lab-based system design processes. In this paper, we evaluate the concept of controlled change by applying it to a demonstration of a potential future space exploration scenario with mobile robots. The robots are capable of executing several image computations for exploration, object detection and pose estimation, which can be allocated to both FPGA-and processor resources of a System-on-Chip. The demonstrator addresses three scenarios which cover application-, environment-, and platform change. The system adapts itself to any of the named changes. This capability can increase the autonomy of future space missions. Exemplary, the demonstrator executes adaption of applications during operation to fulfill the mission goals, adaption of reliability under changing environment conditions, and adaption to sensor failure.

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“…An important application area of mapping (software functions to hardware resources) problems are automotive systems. One proposed method in the literature represents system models in SysML, and applies design space exploration methods to synthesize deployments from logical (platform-independent) system models to technical (platform-specific) system models [14]. A specialized framework for optimal computer architecture selection and mapping has been presented in [15], but it is restricted to the special case of deep neural networks.…”

Section: Related Workmentioning

confidence: 99%

Optimization of systems with nested design space

Zimmermann

Maschotta

Wichmann

et al. 2018

2018 Annual IEEE International Systems Conference (SysCon)

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Finding a good solution to an engineering problem under given constraints can be formulated as an optimization problem over a set of parameters. Existing (semi-)automatic methodologies for this task usually assume that these design parameters form a homogeneous set. The paper analyses the structure of design space and introduces the formal concept of existence-dependent parameters, which appear for instance in the optimization of system architectures. The corresponding nested optimization problems can be solved more efficiently considering the dependency relations, and will often require a mix of models and optimization algorithms. The paper proposes a completely model-driven integration methodology for such problems and a prototype tool combining several existing domain-specific tools. An application example from the area of distributed embedded systems design of hardware architecture and software mapping demonstrates the applicability.

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Bringing DSE to Life: Exploring the Design Space of an Industrial Automotive Use Case

Cited by 26 publications

References 13 publications

Automating integration under emergent constraints for embedded systems

Automating integration under emergent constraints for embedded systems

Demonstrating Controlled Change for Autonomous Space Vehicles

Optimization of systems with nested design space

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